The LeanScale Podcast · Episode 114

Outbound Isn't Dying. Yours Is.

Joey Gilkey on the reach rate almost nobody measures, the four pillars of outbound, an SDR who isn't allowed to book meetings, and why AI belongs in the back of the house

Joey Gilkey · Founder & CEO · TitanX Hosted by Anthony Enrico
Published Updated 01:07:29 68 min read 13514 words
Outbound & Sales Development Sales Leadership AI in GTM Sales Enablement GTM Strategy
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Executive Summary

The one-paragraph brief, extended

Why this conversation matters — and who should spend the hour.

Joey Gilkey is founder and CEO of TitanX, a phone intent platform that predicts which prospects will answer a cold call before a rep dials. The company exists because of a bet that cost him a business. In August 2023, after a year of negotiating, he bought an obscure, expensive piece of intellectual property from a former competitor to act as a moat around Apex Revenue, his fractional VP of Sales and CRO firm. About six months later, sitting on his 70-acre ranch in Tennessee, he concluded the moat was more valuable than the castle it was protecting. TitanX pre-sold 200 beta users in May 2024 and switched the platform on in June, and Joey shut down a growing services company that Anthony puts at six and a half million dollars in revenue. Updata Partners invested in January, leading what the episode notes describe as a $27 million Series A.

His core claim is that the conversation is the atomic unit of go-to-market. The phone is the only outbound channel that gives instant two-way feedback, and every conversation produces intel that can sharpen email copy, ads and content, not just book a meeting. Outbound, he says, is simple but not easy: it comes down to four pillars — the list, the messaging, the rep and the follow-up — with the conversation diagnosing which one is failing. Because a 10% meeting rate per conversation is good and 15% is really good, most of the value sits in systematic follow-up.

On org design, Joey argues the market is moving from an infantry model of cheap, high-volume SDRs to a special forces model of smaller, better-paid specialists, and that full-cycle AEs should never have left. His own structure adds the MDR, a market development rep who is not allowed to book meetings on outbound. MDRs talk to people below the decision makers and hand intel-gathering reports to the AE. He is equally blunt about data: the list is the strategy, data providers should not be trusted without a quality check, and AI-built account dossiers are often simply wrong once you talk to people inside the company.

TitanX is built on the reach rate. Call a list of 1,000 prospects over and over and you will usually never reach more than 200 of them — at a 4% connect rate that takes roughly 7,200 dials. TitanX identifies those 200 up front, which Joey says gives his own reps a 25% connect rate against a typical 3–5%. The same intent split decides voicemail strategy: skip voicemail on high-intent prospects, leave it on low-intent ones, and treat AI call screeners as a new place to put a message.

The episode's centrepiece is a customer that parallel-dialed 200,000 times over 11 months at a 2% connect rate and a 2% meeting rate. Over the same period, 8,000 single-line dials generated 25% more outcomes, with a 9.8% connect rate and a 12% meeting rate — about a 30x difference per dial. When Joey showed them the numbers, people were fired. He blames the bridge delay in parallel dialing and carriers that score phone numbers like credit. The closing framework is his restaurant analogy: automate the back of the house — CRM hygiene, conversational intelligence, signals, list QA — but keep humans in the front, because the more complex the transaction, the more trust it requires.

Key Takeaways

15 things worth stealing

The load-bearing ideas, each with the business implication and who should care.

01

The conversation is the atomic unit of go-to-market

Joey treats the phone as the only outbound channel with instant, bidirectional feedback — email and LinkedIn return a yes, a no, an unsubscribe or nothing. A conversation yields insight and intel that third-party intent tools and data providers cannot supply.

Why it matters: Judging calls only on whether a meeting was booked throws away the raw material for better email copy, LinkedIn messaging, targeted ads and content for named accounts.

Sales LeadersMarketing LeadersRevenue Executives
02

Outbound is simple but not easy: four pillars decide it

The pillars are the list (right accounts, right contacts, good data), the messaging, the rep (ramped and trained) and the follow-up. The conversation sits at the centre and shows which pillar is breaking.

Why it matters: When outbound underperforms, diagnose the pillar rather than the channel. Joey's claim is that with these four right on the phone, outbound will scale.

Sales LeadersRevenue ExecutivesFounders
03

The fat stacks are in the circle backs

A meeting from 10% of conversations is good and 15% is really good, which means 85–90% of conversations do not convert on the spot. Joey rejects the 'knockout artist' mindset in favour of systematic follow-up.

Why it matters: A large share of future wins comes from the follow-up bucket, so dispositions and notes from every conversation need to be captured in a way the next call can use.

Sales LeadersRevOps Leaders
04

The opener matters less than who says it and how

Joey's team tested ten of the most popular script intros and none outperformed the others. His own script uses two gates — an honest 'first time I've reached you, hoping you can help me out' and a stated reason for calling — then pain bucketing, a tight pitch, a call to action and a correct disposition.

Why it matters: Stop hunting for the perfect hook and train tone, pace and pauses instead. Joey calls dispositioning the call correctly the most important step.

Sales Leaders
05

Don't be memorable until it's time to be memorable

Joey borrows the idea from cold-calling practitioner Ryan Reisert. Someone who answers once will likely answer again within the next five or six dials, so there is no need to force a meeting on the first conversation. His team recently booked a big named account after nine conversations, three of which ended with the prospect telling them to f off.

Why it matters: Take what each conversation gives you and record it properly, so the ninth call arrives with enough context to be relevant.

Sales Leaders
06

The list is the strategy — don't trust your data provider

The ceiling of outbound is always the quality of the list, and good phone data is only a subcategory of good targeting. Commoditised databases have taught teams to trust a simple query to build the list, and they should not.

Why it matters: Use data providers, but put a quality assurance step between the query and the sales floor. Wrong titles or wrong accounts make every conversation useless.

RevOps LeadersSales Leaders
07

AI dossiers look confident and are often wrong

TitanX compared account dossiers built from third-party signal tools and AI against a phone-led motion that talked to people up and down the org chart. The conversations produced richer signals and exposed AI conclusions that were simply wrong — the decision maker was someone else, or the '50 sales reps' were really 19.

Why it matters: Treat AI research as a hypothesis to verify, not a brief to walk into a call with.

Sales LeadersMarketing LeadersRevOps Leaders
08

From infantry to special forces

Joey links the build-out of large SDR organisations in 2020–2021 to stimulus money and near-zero interest rates, and calls the result 'extreme mediocrity' bought through headcount. He agrees the current SDR has no future and that SDR numbers should be cut by at least half.

Why it matters: Build smaller teams — eight potent reps rather than 50 with 10 worth keeping — and pay them more than they could earn anywhere else.

Sales LeadersRevenue ExecutivesFounders
09

Full-cycle AEs should never have left

Joey says an AE can make a fraction of the dials and still get two to three times the meeting rate, a 15–20 point higher show rate and a 20–30 point higher qualification rate, with a higher win rate thanks to continuity. He dates the fragmentation of the AE role to Predictable Revenue.

Why it matters: AEs should still go cold to a larger list, but hyper-focus on the high-value, not-yet-ready conversations SDRs surface rather than leaving those with the SDR.

Sales LeadersRevenue Executives
10

The MDR: an SDR who isn't allowed to book meetings

The market development rep intercepts inbound (where booking is allowed) but mainly goes 'below the line' in target accounts, talking to directors, managers, AEs and SDRs to compile intel-gathering reports for the AE. It is the biggest team at TitanX, based in South Africa at around $35,000, alongside US SDRs on a $120,000 base.

Why it matters: An AE who opens with 'I've talked to 13 people at your company this week' gets a very different conversation from a cold pitch.

Sales LeadersRevenue ExecutivesFounders
11

The reach rate: you'll only ever reach about 200 of 1,000

If you call a list of 1,000 prospects repeatedly, pulling people out as you reach them, the number you ever reach usually never exceeds 200. At a 4% connect rate that takes about seven rounds and roughly 7,200 dials. Every prospect already knows whether they answer cold calls — you just don't.

Why it matters: Without knowing which 200 will answer, reps have to treat every prospect the same. TitanX's model identifies them before the first dial.

Sales LeadersRevOps LeadersRevenue Executives
12

Voicemail strategy should follow intent

On high-intent prospects Joey does not leave voicemails, because he expects to reach them — an 85% chance in the next seven dials — and a voicemail teaches them to ignore the number. On low-intent prospects he leaves voicemails and messages for AI screeners. He says AI screeners have not changed connect rates, and the people adopting them most were never going to answer anyway.

Why it matters: An AI screener turns a low-intent prospect into a new ad surface. Leaving a voicemail on a high-intent prospect can burn the shot at a real conversation.

Sales Leaders
13

8,000 single-line dials beat 200,000 parallel dials

A TitanX customer made 200,000 parallel dials over 11 months at a 2% connect rate and a 2% meeting rate. Reps power dialing on the side made 8,000 single-line dials at a 9.8% connect rate and a 12% meeting rate, generating 25% more outcomes. Joey puts the combined difference at 30x.

Why it matters: More volume adds friction and resistance rather than results. When Joey showed the customer the numbers, people got fired.

Sales LeadersRevenue ExecutivesRevOps Leaders
14

Carriers score your numbers like credit — and volume trains them to flag you

Parallel dialing needs a bridge that detects who answered, hangs up on the rest and patches the rep through, creating a delay that makes people hang up. The bigger problem is carriers such as AT&T, T-Mobile and Verizon, which share data and score outbound numbers. Mass volume tells them you are spam, and almost nobody answers a 'spam likely' call.

Why it matters: Fewer, longer, better-prepared connected calls train the carriers that a number is trustworthy, protecting the channel itself.

Sales LeadersRevOps Leaders
15

AI in the back of the house, humans in the front

Joey would not care if his favourite restaurant automated the kitchen, but would never return if it replaced the waiters with an iPad. In sales, the front of the house is anything that touches customers, prospects and the market. The back of the house is CRM hygiene, conversational intelligence, signal identification and list QA.

Why it matters: Automate administrative, repeatable, rules-bound work for margin and leverage, and keep AI out of the conversations where trust is built. The larger and more complex the transaction, the more trust it requires.

Revenue ExecutivesSales LeadersRevOps LeadersFounders
Frameworks Discussed

16 named models

Every framework Jimmy names, defined and time-stamped.

The Conversation as the Atomic Unit of GTM

10:47

Joey's view that the live conversation is the most valuable unit in go-to-market. Data and dialers are the subatomic particles, and the conversation is the atom you have to stack to build anything valuable. He also calls cold calling 'conversational advertising' — delivering a tailored ad to an intended target and getting a reply.

Conversations yield insight and intel that third-party intent tools and data providers cannot. With conversational intelligence, every transcript can feed a per-account repository of signals that is shared with other channels and departments.

The Four Pillars of Outbound

12:55

Outbound succeeds or fails on four things: the list (right accounts, right contacts, good data), the messaging (right message to the right contacts), the rep (ramped, trained, doing the right inputs) and the follow-up (systematic circle-backs on conversations that did not convert).

The conversation sits at the centre of the flywheel and diagnoses each pillar — whether targeting is right, whether messaging lands in an A/B test, how the rep ramps, and what goes into the follow-up bucket. Joey summarises the follow-up principle as 'the fat stacks are in the circle backs'.

The Two-Gate Opener and Pain Bucketing

15:11

A cold call structure where the first gate is an honest opener that signals a cold call and asks for help, and the second gate declares the reason for the call. It then offers two buckets of pain for the prospect to self-select into, followed by a tight pitch, a call to action and a correct disposition.

Joey's example for VPs of Sales: some are trying to get AEs to self-source pipeline after years of SDR support, and others have a robust SDR motion that isn't getting enough at-bats. If the prospect says neither applies, the rep asks how they solved it, which still yields intel. Pauses and tone are written into the script deliberately.

Don't Be Memorable Until It's Time to Be Memorable

18:35

An idea Joey credits to Ryan Reisert: a rep doesn't need to be memorable on early cold calls, but must not be forgotten when it is time to be remembered.

Prospects who answer once will likely answer again within five or six dials, so early calls should gather what they can, be dispositioned correctly and carry good notes into the next call. The meeting comes when context and timing line up — in Joey's example, on the ninth conversation.

The List Is the Strategy

20:16

The ceiling of any outbound effort is the quality of the list — primarily the targeting of accounts and titles, with accurate contact data as a subcategory — so list building must pass a quality assurance check before it reaches the floor.

Joey argues that commoditised data, from DiscoverOrg and ZoomInfo through Apollo and Clay, has taught teams to trust a simple query to build their list. His rule is to use data providers but never trust them, because most outbound fails 'above the funnel' in list building and messaging.

AI Dossier vs. Intel-Gathering Report

23:34

Account research from AI and third-party signal tools, compared with an intel-gathering (IG) report built from real conversations with people across the target organisation.

In TitanX's side-by-side test, conversations produced richer signals — Joey's 'alpha' — and showed that much of the AI output was inaccurate, including the wrong decision maker and a wrong headcount. MDRs build IG reports and pass them to AEs.

Infantry to Special Forces

26:44

A shift away from large, low-paid, high-volume SDR teams toward teams half or a quarter of the size, made up of highly paid specialist conversationalists who stay longer because they are more effective.

Joey would rather have eight potent reps than 50 where only 10 are worth keeping. Paired with full-cycle AEs working the subset of valuable conversations SDRs surface, he sees this as where the market has to move to be effective and profitable.

The MDR (Market Development Rep)

30:03

A role Joey has run for about two years: an SDR who can book meetings from intercepted inbound but may not book meetings on outbound. Their outbound job is to have conversations below the decision-maker level inside target accounts and gather intel for the AE.

MDRs, SDRs and AEs work in a pod with the conversation as the nucleus. Staffing ratios depend on conversation volume. With TitanX's connect rates, Joey says one SDR can support three or four AEs and an MDR team of six can gather intel across the entire book of business.

The Reach Rate

35:26

The share of a prospect list you will ever reach by phone if you keep calling it. Joey says for 1,000 prospects it usually never exceeds 200, no matter how many rounds you dial.

At a 4% connect rate it takes about seven rounds and roughly 7,200 dials to reach those 200. Joey likens it to sifting a haystack for needles. TitanX's premise is identifying the 200 before the first dial so reps can focus phone effort there and use other channels for the other 800.

High Intent, Low Intent, Bad Data

37:54

TitanX's model triangulates telecom and carrier, consumer and professional data to answer three questions about a number: is it the prospect's, is it active, and how does it respond when unfamiliar numbers call it?

Yes to all three means high intent for the phone. Yes to the first two means low intent — the number is theirs and active, but they don't answer. No to the first means bad data. Joey says data providers get the number wrong 15–20% of the time.

Voicemail and AI Screeners by Intent

39:44

Voicemail rules that depend on answer intent: skip voicemail on high-intent prospects, leave voicemails and AI-screener messages on low-intent prospects, and point voicemails to the email you sent.

People recognise a repeated number more easily than a name buried in a voicemail, so a voicemail to a likely answerer can burn the number. The people adopting AI screeners most were never going to answer, so the screener becomes new ad real estate. TitanX is adding high-intent and low-intent segments split by whether AI screening is on, each with its own scripting.

Outbound Is Not Dying — Yours Is

44:31

Joey's position that outbound itself works and a failing motion reflects execution, because outbound is continuous experimentation — much like a PLG motion — run inside the four containers of list, message, rep and follow-up.

He delivered it to Updata Partners' portfolio CROs and VPs of Sales in a webinar titled 'guaranteeing outbound sales success', arguing that anyone who knows what goes into outbound and how to measure it can make it work. He says he has never lost at outbound in close to two decades.

Front of House vs. Back of House (the Restaurant Analogy)

47:45

Automate the back of the house — administrative, repeatable, rule-bound work — and keep humans in the front of the house, where the business touches customers, prospects and the market.

Joey's example is Born and Raised in San Diego: he wouldn't care if the kitchen were automated, but would never return if waiters were replaced by an iPad. In sales, the back of the house is CRM hygiene, conversational intelligence, signals from conversations and list QA, which frees people for the front. He used the same analogy for automation five years ago, before AI.

The 3Es: Effort, Efficiency, Effectiveness

55:37

When channel headwinds reduce effectiveness — blacklisted email domains, LinkedIn throttling, spam-flagged phone numbers — teams try to make up for it with effort, raising volume to recover their previous results.

Joey's warning is that more volume also adds friction and resistance. The 200,000-dial case study is his proof.

Parallel vs. Single-Line (Power) Dialing

58:47

Power dialing places one call from one number to one person. Parallel dialing places several calls at once, connects the rep to whoever answers and hangs up on the rest.

Joey lists what goes wrong with parallel dialing. The rep doesn't know who will answer, so can't prepare. The bridge that detects the answer and patches the rep in creates a pause that makes people hang up. And the volume signals spam to carriers. His 'waiting room' analogy: you would never be ready for a prospect if you didn't know which of five might walk through the door.

Your Phone Number Is a Credit Score

01:01:39

Carriers such as AT&T, T-Mobile and Verizon share data and score outbound numbers, which rise or fall with dialing behaviour — much as Google and Microsoft blacklist spam email domains.

Mass volume feeds carriers data that says 'spam', leading to 'spam likely' labels that almost nobody answers. Fewer dials, more connects and longer talk time train carriers that a number is trustworthy.

Best Quotes

20 lines worth clipping

Pulled verbatim. Copy or share any of them.

“I built a moat around the castle where the moat, I believe, is more valuable than the castle it's protecting.”
Joey Gilkey 05:09
“I make 100 dials. I used to be able to talk to 15 people. I make 100 dials. I could talk to 10 people. And then it was like seven. And then it was five.”
Joey Gilkey 07:56
“the conversation is the atomic unit of go to market, right? If I can get conversations, I can glean insight, intel.”
Joey Gilkey 10:47
“The four pillars are pretty simple. It's list, messaging. It's the rep and it's the follow-up.”
Joey Gilkey 12:55
“that's where follow-up comes in. And we say the fat stacks are in the circle backs”
Joey Gilkey 13:45
“on your first conversation in a cold call, it's okay to be unmemorable”
Joey Gilkey 18:43
“The ceiling of your outbound efforts is always going to be the quality of your list.”
Joey Gilkey 20:16
“the non obvious thing is don't trust your data provider, use them, leverage them.”
Joey Gilkey 22:15
“I think the research has gotten pretty lazy, especially with AI thrown into the mix, too, because it looks so confident on paper”
Anthony Enrico 22:48
“where I think the market is going is we're moving from an infantry model to a special forces model”
Joey Gilkey 26:44
“Can't book a meeting. I just want you to have a conversation. I want you to go gather as much insight and intel as possible”
Joey Gilkey 31:02
“the reach rate is a very simply explained metric that nobody measures.”
Joey Gilkey 35:26
“you may be burning your shot with that high intent person because if you leave a message, then you're only gonna be able to leave so much context.”
Anthony Enrico 41:26
“outbound is not dying, but yours is.”
Joey Gilkey 45:02
“everything in the back of the house in the kitchen was fully automated, steaks were made, same quality, fully automated, etc. I wouldn't care, because I'm there for the experience on the front of the house.”
Joey Gilkey 49:02
“the larger the transaction, the more complex the transaction, the more trust is required.”
Joey Gilkey 54:38
“When I showed them the outcome, people got fired.”
Joey Gilkey 56:58
“it's a 30x difference. So it took 30 times the amount of dials to get the same outcome parallel dialing as it did just single line dialing.”
Joey Gilkey 58:33
“your phone number that you call from out of your dialer is like a credit score.”
Joey Gilkey 01:01:39
“having the posture of I don't need to book a meeting. I don't need to sell this person. I'm here to learn.”
Anthony Enrico 01:03:08
Practical Advice

What should you actually do?

The playbook, split by the seat you sit in.

Sales Leaders

  • Diagnose failing outbound pillar by pillar — list, messaging, rep, follow-up — using what conversations reveal, rather than declaring the phone dead.
  • Stop testing hooks; train tone, pace and deliberate pauses, and make correct call dispositioning non-negotiable.
  • Use a two-gate opener: be honest that it is a cold call, state why you are calling, then offer two pain buckets for the prospect to self-select.
  • Don't force a meeting on the first conversation. Capture sentiment and context in the notes so later calls are relevant.
  • Skip voicemail on prospects likely to answer, and leave voicemails and AI-screener messages that point to your email for those who won't.
  • Prepare before every dial. Single-line dialing lets reps research the people they are actually going to reach.

Revenue Executives

  • Shrink and upgrade the SDR function: fewer, better-paid specialists rather than a volume-driven headcount model.
  • Bring full-cycle AEs back into prospecting, focused on the high-value conversations SDRs surface.
  • Consider an MDR role that is barred from booking outbound meetings and exists to feed AEs intel from inside target accounts.
  • Before scaling dial volume to recover falling results, check whether the added volume is creating friction with carriers and prospects.

RevOps Leaders

  • Put a quality assurance step between the data provider query and the sales floor, covering both targeting and phone accuracy.
  • Measure reach rate alongside connect rate, so the team knows what share of a list is ever reachable.
  • Break call logs down by dial mode and compare connect rate and meeting rate for parallel and single-line dialing.
  • Catalogue call dispositions and outcomes as structured data, so valuable conversations can be routed to AEs and follow-up is systematic.
  • Use AI for back-of-house work — CRM hygiene, conversational intelligence, signal extraction and list QA.

Marketing Leaders

  • Mine sales conversations for insight and feed it into email copy, LinkedIn messaging, targeted ads and named-account content.
  • Verify AI and third-party signal dossiers against what people inside the account actually say.

Founders

  • When one business becomes a moat for another, ask whether the moat is worth more than the castle it protects.
  • Joey concluded he couldn't serve two masters: once the new product took off, he shut down the services business rather than run both.
AI Takeaways

How AI actually changes GTM

LeanScale's signature read on the AI-in-GTM question this episode wrestles with.

The thesis

Joey's view is that AI is not ready to hold sales conversations, and that even if latency disappeared, trust between humans would still decide complex deals. AI's highest-leverage place is the back of the house: making human conversations better prepared, better targeted and better captured rather than replacing them. AI research also needs checking — dossiers built from AI and third-party signals were often wrong once real people inside the account were asked.

Agent & automation ideas

  • Conversational intelligence that scores every call transcript against the signals a team cares about and builds a per-account signal repository for other channels and departments.
  • A list QA agent that checks titles, accounts and phone data from a provider before a list reaches reps.
  • A dossier verifier that compares AI and third-party research with what reps and MDRs hear in conversations and flags contradictions.
  • Campaign segmentation by answer intent and AI-screener status, with the matching script in front of the rep for each segment.
  • Automated CRM hygiene and call dispositioning so reps spend their time on conversations.
Operations Takeaways

By function

The same conversation, filtered for RevOps, pipeline/marketing ops, and customer ops.

Revenue Operations

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Pipeline & Marketing Ops

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Metrics Mentioned

The numbers, with context

$6.5M in revenue
Apex Revenue at shutdown

Anthony's figure for the services business Joey turned off to build TitanX from zero revenue.

200 beta users in May
TitanX beta pre-sale

Pre-sold after a May 1 announcement, with the platform turned on in June 2024.

15 → 10 → 7 → 5 conversations per 100 dials
Connect-rate decline on the phone

Joey's description of falling connect rates as the phone saturated, against TitanX talking to 25 people per 100 dials.

10% good, 15% really good
Good meeting rate per conversation

Which means 85–90% of cold-call conversations don't book a meeting — the case for systematic follow-up.

9
Conversations before a meeting

A big named account booked after nine conversations; three ended with the prospect telling the rep to f off, and the other six were 'not interested'.

2–3x meeting rate, +15–20 pts show rate, +20–30 pts qualification rate
AE vs. SDR funnel advantage

What Joey says a full-cycle AE achieves on a fraction of the SDR's dials.

~$35K MDR (South Africa) vs. $120K base SDR (US)
MDR vs. SDR cost

Joey's arbitrage of the MDR role; he describes the US base as well above market rates.

25% vs. a typical 3–5%
Connect rate with TitanX

One conversation every four dials instead of every 30. Joey says a rep can make 60 dials a day and have 12–15 conversations, where 100 dials would otherwise yield three.

~200 of 1,000 prospects
Reach rate ceiling

Reaching them by repeated dialing at a 4% connect rate takes about seven rounds and roughly 7,200 dials.

Wrong 15–20% of the time
Data provider phone accuracy

Joey's estimate of how often data providers attach the wrong phone number to a contact.

85% within the next seven dials
High-intent reach probability

Why Joey doesn't leave voicemails on high-intent prospects; he later puts the chance of eventually reaching them at 85–90%.

200,000 dials over 11 months; 2% connect rate (4,000 connects); 2% meeting rate
Case study: parallel dialing

A TitanX customer that piloted a year earlier kept parallel dialing despite Joey's warning.

8,000 dials; 9.8% connect rate; 12% meeting rate
Case study: single-line dialing

Reps power dialing on the side made 4% as many dials as the parallel dialer and generated 25% more outcomes.

30x
Case study: combined gap

Roughly 5x the connect rate times 6x the meeting rate. In Joey's words, parallel dialing took 30 times the dials to get the same outcome.

~90% vs. ~10%
Research that pays off

Researching a high-intent list means about 90% of the prep is used. Researching 100 random prospects, of whom only nine or 11 answer in the next 500–600 dials, wastes about 90% of it.

Entities

Companies, people & tools mentioned

Auto-extracted and linked into the knowledge graph.

Companies

TitanXSales Intelligence / Phone Intent

Joey's phone intent platform, which predicts before the dial which prospects will answer. It pre-sold 200 beta users in May 2024 and turned the platform on in June. Joey says it gives his own reps a 25% connect rate against a typical 3–5%, and a new platform launch was about six weeks away at recording.

00:00 · 05:36 · 34:25 · 37:54 · 01:07:05Company →
Apex RevenueSales Consulting / Fractional Sales Leadership

Joey's fractional VP of Sales and CRO firm, which had an outsourced sales arm and a large office in downtown Knoxville. It acquired the intellectual property that became TitanX in August 2023, and Joey shut it down to focus on TitanX. Anthony puts its revenue at six and a half million dollars.

01:30 · 02:51 · 04:03 · 05:48Company →
Updata PartnersVenture Capital / Growth Equity

TitanX's investor from January. Joey ran a webinar for its portfolio CROs and VPs of Sales titled 'guaranteeing outbound sales success', where he made the 'outbound is not dying, but yours is' argument.

43:35Company →
ZoomInfoGTM Data / Sales Intelligence

Cited as part of the data-commoditisation arc from DiscoverOrg to ZoomInfo, Apollo and Clay, and as a place teams build the 1,000-contact 'haystack' list. Joey also uses breaking into ZoomInfo as a hypothetical target account to explain the MDR role.

21:49 · 30:41 · 37:05Company →
MetaAdvertising / Social

Contrasted with cold calling as conversational advertising: on the phone, Joey says, he doesn't depend on Facebook's algorithms or whether Meta can target the right person.

10:17Company →
GoogleSearch / Advertising

Cited with Microsoft as the email providers that blacklist spam domains — the same pattern Joey says phone carriers now apply to high-volume dialers.

01:01:10Company →
MicrosoftSoftware / Cloud

Cited with Google, via Outlook, as blacklisting spam email domains — Joey's comparison for how carriers are starting to score outbound phone numbers.

01:01:10Company →
LeanScaleGTM Operations

Anthony's firm. He notes that very few of the B2B SaaS companies LeanScale works with use the phone at all, and relates the front-of-house analogy to running a services business where human interaction with clients matters.

08:56 · 51:18 · 01:05:41Company →

People

Joey Gilkeyguest

Founder & CEOProfile →
Anthony Enricohost

Co-founder of LeanScale and host of The LeanScale Podcast.

Co-FounderProfile →
Ryan Reisertmentioned

Cold Calling PractitionerProfile →
Aaron Rossmentioned

Author, Predictable RevenueProfile →

Tools & software

Apollo.ioSales Intelligence / Engagement

Named in the data-provider lineage from DiscoverOrg and ZoomInfo to Clay, and as a source for building the 1,000-contact list TitanX filters.

Website ↗
ClayGTM Data / Enrichment

Named with Apollo as the current generation of accessible data tools that teams now trust to build a list from a simple query — which Joey says they shouldn't.

Website ↗
CognismGTM Data / Sales Intelligence

Listed with ZoomInfo, Apollo and Clay as a place teams build the 1,000-person 'haystack' that reps sift through by dialing.

Website ↗
6senseABM & Intent

Mentioned in the discussion of signal data as the company that popularised 'buyer intent', just before Joey describes TitanX's test comparing third-party signal dossiers with conversation-led intel.

Website ↗
LinkedInSocial Platform

Cited as a channel whose automation was throttled after years of volume plays, as a channel that — unlike the phone — gives only a yes, no or block, and as where Joey's team ran a LinkedIn Live test of popular cold-call intros. It is also where to find Joey.

Website ↗
SalesforceCRM

Where Aaron Ross came from before writing Predictable Revenue, the book Joey blames for fragmenting the full-cycle AE role.

Website ↗
Methodologies referenced Call dispositions as structured outcomesIntel-gathering (IG) reportsList quality assurance before the floorCall-log breakdown by dial modeIntent-segmented campaigns
Related LeanScale Services

Where this shows up in the work

Sales Enablement Build

Stand up a zero-based, sales-academy enablement motion sized to your span of control and sales complexity.

The four pillars, the two-gate script, dispositioning discipline and the SDR, MDR and AE pod are all enablement and sales process design.

AI for GTM

Agents and workflows that multiply operator throughput — the 'make humans superhuman' thesis, operationalized.

Joey's front-of-house/back-of-house split is a working rule for where AI belongs in a GTM motion, from conversational intelligence to CRM hygiene.

Fractional RevOps

Embedded, field-facing RevOps leadership and execution — the operator model Jimmy describes, delivered as a service.

List QA, reach-rate and dial-mode measurement, and structured call outcomes are the operations layer that makes the outbound motion measurable.

Frequently Asked Questions

Straight answers

Generated from the conversation, marked up for search and AI extraction.

What are the four pillars of outbound?

According to TitanX founder Joey Gilkey, outbound comes down to four things. The list: targeting the right accounts and contacts with good data. The messaging: saying the right thing to those contacts. The rep: someone ramped and trained to deliver it. And the follow-up: systematic circle-backs on conversations that didn't book a meeting. He calls outbound simple but not easy, and says the conversation is the diagnostic at the centre — it shows whether targeting is right, whether messaging lands, how reps are ramping and what belongs in follow-up.

What is the reach rate in cold calling?

Reach rate is the share of a prospect list you will ever reach by phone if you keep calling it. Joey Gilkey says that if you call a list of 1,000 prospects over and over, removing people as you reach them, the total you ever reach usually never exceeds about 200. At a 4% connect rate, reaching them takes about seven rounds and roughly 7,200 dials. He calls it a simple metric that almost nobody measures, and TitanX is built on predicting which 200 people those are before anyone dials.

What is an MDR and how is it different from an SDR?

In Joey Gilkey's model, an MDR (market development rep) is an SDR who may not book meetings on outbound. MDRs can book from inbound they intercept — form fills, opt-ins, website visitors — but their main job is to talk to people below the decision makers in target accounts, such as directors, managers, AEs and SDRs. They compile what they learn into intel-gathering reports for the account executive, who then approaches executives with context. At TitanX the MDR team is the company's largest and is based in South Africa, while SDRs are US-based and do book meetings.

Why did 8,000 single-line dials beat 200,000 parallel dials?

In the TitanX case study, a customer parallel-dialed 200,000 times over 11 months at a 2% connect rate and a 2% meeting rate. Reps power dialing on the side made 8,000 single-line dials at a 9.8% connect rate and a 12% meeting rate, generating 25% more outcomes — about a 30x difference per dial by Joey Gilkey's reckoning. He gives three reasons: parallel-dial reps don't know who will answer and can't prepare, the bridge that connects the rep creates a pause that makes people hang up, and the volume trains carriers to label the numbers as spam.

Should sales reps leave voicemails on cold calls?

It depends on the prospect's intent to answer, according to Joey Gilkey. For high-intent prospects — people likely to pick up, with an 85% chance of reaching them in the next seven dials — he doesn't leave voicemails, because people remember a repeated number more than a name and a voicemail can teach them to ignore it. For low-intent prospects, who are unlikely ever to answer, he leaves voicemails and messages for AI call screeners that point to an email, giving as much surface area as possible. He also says AI screeners have not changed connect rates.

Should you trust your data provider when building an outbound list?

Joey Gilkey's advice is to use and leverage data providers but not trust them. The list sets the ceiling on outbound results, and the most important part of list quality is targeting the right titles at the right accounts, with accurate phone data as a subcategory. Because commoditised databases make it easy to build a list from a simple query, teams skip checks, so he puts a quality assurance step between the export and the sales floor. He estimates data providers attach the wrong phone number 15–20% of the time.

Where should AI be used in sales, and where shouldn't it?

Joey Gilkey uses a restaurant analogy. He wouldn't mind if a restaurant automated its kitchen, but would never return if it replaced waiters with an iPad, because the experience is why he is there. In sales, the back of the house — CRM hygiene, conversational intelligence, extracting signals from conversations and list quality assurance — is where AI adds margin and leverage. The front of the house — conversations with customers, prospects and the market — should stay human, because sales is a transaction based on trust, and the larger and more complex the deal, the more trust it requires.

Is the SDR role going away?

Joey Gilkey agrees the current SDR model has no future and says SDR numbers should be cut by at least half, but he doesn't think the function disappears. He describes a shift from an infantry model of large, lower-paid, volume-driven teams to a special forces model of smaller teams of highly paid specialist conversationalists. In his view the SDR's job should be having conversations rather than only booking meetings, full-cycle AEs should also prospect, and the valuable conversations SDRs surface should move to AEs.

Why did Joey Gilkey shut down a profitable services company to start TitanX?

In August 2023 Joey Gilkey acquired an obscure but powerful piece of intellectual property to serve as a moat around Apex Revenue, his fractional VP of Sales and CRO firm. About six months later he realised clients valued access to that technology more than the services it supported — the moat was worth more than the castle. TitanX pre-sold 200 beta users in May 2024 and launched in June, and because he felt he couldn't run both companies, he shut down the growing services business, which host Anthony Enrico put at six and a half million dollars in revenue, to build the software from zero.

Timeline

Jump through the conversation

Click any chapter to open it in the transcript.

00:00Cold open + intro 01:30Turning off a $6.5M business to start over at zero 04:03The moat is worth more than the castle it's protecting 06:09Why he bet the house on the phone 08:56The only outbound channel that talks back 12:41The four pillars: list, messaging, rep, follow-up 14:35Anatomy of a cold call script 18:31Don't be memorable until it's time to be memorable 20:09The list is the strategy — don't trust your data provider 22:48AI dossiers vs. what people actually tell you 24:52Infantry to special forces: rebuilding the SDR org 29:58The MDR: an SDR who isn't allowed to book meetings 34:25The reach rate: why you'll only ever reach 200 of 1,000 38:58Voicemail, AI screeners, and burning your shot 43:35Outbound is not dying — but yours is 45:20Where AI belongs: the restaurant analogy 51:38What can't be automated out of the front of house 54:45Effort, efficiency, effectiveness: why more volume backfires 56:07The 30x case study: 200,000 dials vs. 8,000 58:41Why parallel dialing breaks: the bridge and the carriers 01:02:34Preparation is the real edge 01:06:47Where to find Joey and TitanX
Full Transcript

The whole conversation

Broken into chapters, searchable, verbatim from the audio. Speakers inferred (not diarized).

Transcript as markdown ↓ Whole episode as markdown ↓
00:00Cold open + intro

0:00 Joining me today is Joey Gilkey, founder and CEO of Titan X and the person who

0:05 decided the most valuable thing in Outbound was not a better message. It was

0:09 knowing which prospects will actually pick up the phone. So I had to make the very painful and

0:14 very financially difficult decision for myself and my family to shut down a

0:18 growing and fairly decent sized services company to go pursue a technology that

0:23 basically was at zero revenue. A lot of people are getting obsessed with just

0:29 getting every bit of efficiency out of their system. I think there's two ways.

0:34 There's effectiveness that you can get with AI power and then there's

0:39 efficiency which really has a diminishing return at a certain point but

0:43 how do you think about that and where do you think it's going to be going in the future?

0:47 So it took 30 times the amount of dials to get the same outcome parallel dialing

0:52 as it did just single and matter. So a lot of it's the infrastructure behind it. So if you parallel dial,

0:57 I'm placing one call from one phone number to one person. It's like the conversation at the

1:02 power cost of going to market because I can get all this stuff that you can't get

1:05 from third-party intent tools, you can't get from data providers, I can get it from the conversation.

1:09 Let's assume it was conversationally there. I do still think there's a difference between

1:14 connecting with someone and knowing that it's trust is on the other side.

1:18 It's trust. I think you and I talked before. Outbound is not dying but yours is.

1:27 [Music]

01:30Turning off a $6.5M business to start over at zero

1:30 Joey, in 2023, you bought a company for its IP and then you looked at these

1:34 six and a half million dollars in revenue you already had in one business and decided to turn

1:40 it off and start a software company at zero. Take me inside the room where you made that call.

1:46 Yeah, I think you have to back up to my full career. I've been an entrepreneur since 2017.

1:51 I did sell a company in 2020 which was also a services company.

1:56 Since then, I hate this word because I think it doesn't actually mean that much. Being a serial

2:02 entrepreneur, I think that means something if you keep stacking companies and you have a bunch of

2:06 successes over decades. But I think if serial entrepreneur means you just start a bunch of

2:11 companies over a couple of years, it doesn't mean that much but that was me.

2:16 So I started a number of companies. I could admittedly say that they're all "successful"

2:20 financially but not both from a purpose perspective and for me,

2:29 services can only go so far. I've never lost that edge of services. I'm very passionate about

2:35 services but the vehicle in which you deliver services really matters to me from a scale

2:39 perspective. If we go into that time, I had this exit in 2020. I had some side ventures that were

2:47 doing well, spending off good cash flow for me and the family and it was great.

2:51 But then I built Apex Revenue which was the services company you talked about that

2:56 eventually acquired the IP. That company was going well. We had a lot of momentum and motion

3:01 around what we were doing. Building a pretty sizable team at the time. We had a big office

3:07 in downtown Knoxville. It was moving people to Knoxville and all these things were happening.

3:12 But in that time of running the services company, you run into a lot of bottlenecks.

3:17 You start to see a lot when you start getting inside, deep inside of Org. We were a fractional

3:21 VP of Sales and CRO company that had an outsourced sales arm to it. As we started to get deeper into

3:28 Org, we started to realize that there were some serious headwinds coming in the market that were

3:31 actually accelerated through COVID that actually started back in the early 2010 area. We got a

3:39 hold of this really obscure technology through a partnership. He's actually a foe of mine in an old

3:47 life. We were competitors. We both exited about the same time. He went and solved a different

3:51 problem than I did. We kept in touch and eventually started using this super boutique,

3:56 obscure, very expensive, very slow, but very powerful intellectual property that he possessed.

04:03The moat is worth more than the castle it's protecting

4:03 The more that I built Apex, the more I realized if I want to have a moat around this services

4:08 company, I need to go buy that thing. I need to own the property. I did that by a year of negotiating.

4:14 Finally got a struck a deal, cut them a check in August of '23 and acquired it. In hindsight,

4:23 I seem brilliant. I was not. I thought I'm going to have this intellectual property. I'm going to

4:26 shut it off from the market, take it down to zero in revenue, and it's going to be the moat around

4:30 Apex and allow Apex, the service company, to scale. About six months in that endeavor, I realized that

4:36 yes, that was true. It was unique, but what people loved about Apex was our access to this very unique

4:42 intellectual property. People started asking about like, can we just have that? Can we have access to

4:47 that? I sat down and you asked what was the conversation going on in the room? It wasn't

4:53 in a room. It was actually on my farm. I live on a 70 acre ranch in Tennessee. I'm sitting outside.

4:58 I'm just looking at the pasture. It had recently been hayed by the farmers that we trade hay with,

5:03 and I was looking at all these bales of hay and just sitting and thinking. I started to realize

5:09 I built a moat around the castle where the moat, I believe, is more valuable than the castle it's

5:14 protecting. Fast forward to early '24, made the decision to say, "Well, let me just go kind of

5:21 precede the idea to a few people," and instantly lashed on because the problem became so acute in

5:26 the market. I was like, "Man, there's something to this," and so I went and found a CTO that I could

5:30 bring in who would kind of build an MVP for me. We decided to tell the market we were doing at May 1st

5:36 to pre-sale beta users. We sold 200 beta users in May. June, we turned the platform on, and from

5:42 there, we just took off. The moment we took off, it became very evident to me that I can't serve two

5:48 masters, so I wasn't going to run Apex and this company at the same time. I had to make the very

5:53 painful and very financially difficult decision for myself and my family to shut down a growing

5:59 and fairly decent-sized services company to go pursue a technology that basically was at zero

6:04 in revenue but had a lot of potential. Longer answer, but that's the background.

06:09Why he bet the house on the phone

6:09 No, I love it, and those are such difficult decisions to make, especially when the opportunity

6:15 cost is potentially as high as it is. I'm curious, outside of, "Hey, this is a tech that can scale.

6:23 This is a moat that I can plug in anywhere," was there anything in the market that was leading you

6:28 to believe that, "Hey, the next two potentially five-year horizon, this is why this bet is going

6:35 to really pay off"? Yeah, there's two big ones, one of which was automation in the late 20s into the

6:43 early 2020s. Shot out like a cannon. You had all these different tools that essentially made volume

6:49 the play. Like, "Okay, well, effectiveness isn't great, but volume can kind of make up for the

6:53 effectiveness gap." You get automation tools that allow you to send an insane amount of emails and

6:58 do LinkedIn automation and all the things until LinkedIn throttled everybody and shut down

7:02 everything. But what I started to see was there's this big frontier that's like, you know how it's

7:08 like what is now new or what is now the best thing in the market is actually something of old.

7:15 The only way forward is to look into the past. I started to see that there's, and I've always

7:22 been a phone guy, right? Go to market. I think the phone is the most powerful channel. I've got

7:26 reasons behind that. I could talk about that, but I started to see this like skepticism and or like

7:31 just general flatness around email, not delivering. And people basically abandoned the phone for the

7:37 most part for years. And I started to see this resurgence of people going back to the phone.

7:42 And so there's this wave of that where people are running back to this channel that I know the

7:46 most about. And I had this technology that can solve a problem around. Simultaneously, just like

7:51 with email and LinkedIn, when saturation comes about, commoditization comes about. And so then

7:56 you start to see connect rates on the phone. I make 100 dials. I used to be able to talk to 15 people.

8:01 I make 100 dials. I could talk to 10 people. And then it was like seven. And then it was five. And

8:05 you're watching this trend of the connect rate. How many people I can talk to on the same amount of

8:08 dials dropping. And we had this solution that changed that entire economic model and flipped

8:14 it on its head where it's, well, you can make $100 and talk to 25 people. What does that do for the

8:18 economics of the business? And so I think it was the right time, the right place, call it providence.

8:25 It was where you see people moving to a channel. And you also simultaneously see the headwinds and

8:30 the big wave coming at that channel at the same time. And so I think we're just at this perfect

8:35 intersection. And so that was ultimately what I saw and then what I decided to just bet the house on.

8:42 Literally, actually, I did bet the house. I lost millions of dollars over the past couple of years

8:49 until I made a lot more than that. But yeah, it was a painful sacrifice, but a worthwhile bet.

08:56The only outbound channel that talks back

8:56 Yeah, those tend to be the best ones to make, though. I would love your perspective on

9:03 phone. I think we work with a ton of B2B SaaS companies. I think very few of them

9:09 are even leveraging phone or even know it feels like it kind of got lost after 2020

9:16 because email and LinkedIn was probably working OK. And then the art of how to do the dials,

9:23 even even what to do on the phone. But I would love to hear your perspective on

9:27 why it's such an effective channel and how to do it right.

9:31 Yeah, so I'll start just philosophically. I think the phone is the only I'll say I'll say outbounds,

9:36 but you could probably apply this to a lot of channels. But it's the only outbound channel

9:39 which I get to deliver and add to an intended prospect where I will get instant bidirectional

9:47 feedback in a conversation. I don't get that with email. I get a yes, I get a no, I get an unsubscribe,

9:52 I get nothing. LinkedIn, very similar. Yes, no, don't message me, block me, whatever. But the phone

10:00 is a unique channel which I get to actually converse in live time and catch someone where

10:04 I can deliver an ad. All cold calling is it's telemarketing, telephone marketing. And so it's

10:11 we call it conversational advertising is like I have the ability to deliver a tailored ad to my

10:17 intended target. I'm not worried about Facebook's algorithms on or whether meta can actually target

10:22 this person. I'm not worried about LinkedIn and their cost per whatever. It's I can I can deliver

10:26 this about the right phone number for them to this person if they pick up and I can have a conversation

10:31 that that I can glean insight, Intel and interest from. Yes, I can generate a meeting, but also I

10:37 can generate insight and Intel. And so I think that's why that's my philosophy around the phone

10:42 is it's the only channel which I get that and that if I if I treat that sacred, which is I think that

10:47 the conversation is the atomic unit of go to market, right? If I can get conversations, I can

10:52 glean insight Intel. If I can glean insight Intel, I can then write better email copy, I can then

10:57 send better LinkedIn, I can then create more targeted ads after I can create better content

11:01 for my for my named accounts. And so I think that's the biggest thing around the phone.

11:06 One one of the things you mentioned, I don't think people are even thinking about.

11:09 I think they would judge all of the success on did I book a meeting? And I'm not even sure if

11:14 they're capturing the intelligence to feed their marketing engine to use that as a huge, huge,

11:21 but it's a huge mess. It's a mess. I mean, now that we have AI and we have conversational

11:25 intelligence, you have every transcript of every call. You have AI that can make sense of it,

11:29 you have AI that can be trained on what signals matter to you, and it can be creating a repository

11:33 of signals per account that you can then feed to other. This is why I say it's the it's like the

11:38 mitochondria, the powerhouse of the cell, like the conversation at the powerhouse of go to market,

11:43 because I can get all this stuff that you can't get from third party intent tools,

11:46 you can't get from data providers, I can get it from a conversation. So we get it from a

11:50 conversation, I can now distribute that insight in those signals to other channels, other departments

11:55 within the organization, and so on. And so when it comes to doing it well, one, you have to have

12:01 this core belief that the conversation is of extreme value. That's why I say it's the atomic

12:07 unit of go to market, because if you think about physics, you have subatomic particles,

12:11 which is like your data, your dialers, the protons and neutrons. Then you have your matter,

12:17 which is the most important thing, which is like the table, we're sitting in front of the microphone,

12:21 but you can't have the really valuable stuff unless you stack the atoms, which is the conversation.

12:28 And so how do you do this? Well, as one, you believe that the conversation holds immense

12:32 value outside of just booking appointments, it's not just the tip of the spear for for

12:35 setting appointments or meetings. And so what we talk about without bound is outbound in itself

12:41The four pillars: list, messaging, rep, follow-up

12:41 and phone specifically, phone that outbound is simple, but it's not easy. And I have to give that

12:47 caveat of the difference in the two. Why is it simple is because it comes down to getting four

12:51 things right. If you get the four pillars about bound, right with the phone, you will absolutely

12:55 scale the crap out of, of, of outbound. The four pillars are pretty simple. It's list messaging.

13:03 It's the rep and it's the followup. Right. So list is am I targeting the right accounts and the right

13:08 people and contacts within those accounts? And do I have good data quality on those contacts?

13:12 The messaging is am I saying and delivering the right message to the right contacts at the right

13:18 accounts? The rep is who is delivering that message? Are they ramped correctly? Are they

13:21 trained correctly? They're doing the right inputs to deliver the right message to the right list.

13:25 And then because we're not knockout artists, where we believe that everything's about setting

13:28 the meeting, then you have to have systematic followup in there, right? In outbound specifically,

13:33 it's pretty good if you can book a meeting 10% of the time you have a conversation. 15 is really

13:38 good. So therefore that the inverse is true. I failed 85, 90% failed. And so what do I do with

13:45 those people? Well, that's where followup comes in. And we say the fat stacks are in the circle backs

13:48 is how do you do systematic followup? So the reason I say it's important is the conversation

13:54 at the core of this flywheel, if you will, these four pillars is the conversation gives me feedback

14:00 on whether or not my list and my targeting is good. The conversation gives me feedback on whether

14:04 this messaging is landing, or if I tweak this messaging, AB tested these two different scripts,

14:08 this one works better than that one. The conversation is what actually ramps the rep and

14:12 gets them better at delivering the message to the right list. And the conversation,

14:16 because we're not knockout artists, is going to feed a massive follow bucket where a lot of our

14:20 future wins are going to come from. And so when you do outbound well, it's you have an attention

14:24 to detail to these four pillars. And you leverage the conversation in the middle of that to diagnose

14:30 what is going right or wrong or who is going right or wrong within this flywheel.

14:35Anatomy of a cold call script

14:35 What does the anatomy of a script look like, especially, as you put it, you're not designing

14:41 it just to be a knockout artist, but you're designing it to capture more? How do you structure

14:45 that conversation? Yeah, I mean, there's always this argument like to do permission based openers,

14:51 or do you know, like there's, we ran this test years ago, and we did a live like LinkedIn live

14:56 on this. And we were like, Hey, let's take 10 of the most popular intros to a script. And let's

15:02 see if any of them outperform the others. It doesn't. It doesn't. So there's no hook. That's

15:07 like the hook. I mean, the king, there's a bad way to do it. But there's a lot of good ways.

15:11 Right. And so I'll give an example of ours. So ours is very simple. And there's a psychology

15:16 behind it. The reason I say that it didn't really matter what you said, it's who said it, and how

15:20 you said it is more important. So the tone, the pace, etc. So we bake in things that you would not

15:26 normally put in a script, pauses, um, etc. And so I'll say, Hey, Anthony, this is Joey Gilkey over at

15:33 Titan X. It's actually the first time I've reached him. I was hoping I put that word in there

15:38 specifically, hoping that you could help me out here for a brief moment. Right? It's a gate,

15:42 the gate is I want to let them know that this is a cold call, in the sense that I don't want them

15:48 thinking the back of the brain. What's this about? Why is he calling me, etc. It's like, I haven't

15:51 reached you. I'm hoping you can help me out. People want to be helpful. And so I'm hoping that's a

15:57 psychological word to help people want to be helpful. So then they get past that gate and they

16:01 say, Oh, yeah, sure. What you got? Or yeah, what, you know, tell me what you got. And the next part

16:07 is the second gate, which I read it back to him said, perfect, Anthony. Appreciate that. Again,

16:12 Joey Gilkey, Titan X reason I'm calling. And I want to declare why I'm even here. And then I

16:19 want to kind of get into resonating with them or making it relevant to them. I talked to VPs of

16:25 sales and CROs all day, every day at this point. And I'm kind of hearing like one of two things

16:30 from them. And then I call it what we call pain bucketing. I want to put two buckets of pain in

16:35 front of them for them to self-select which one they live in. So so yeah, I talked to VPs of sales

16:41 and CROs all day, every day. And I tend to hear one of two things. So one is, you know, VPs,

16:46 if I'm talking to VPs, I'll say it this way. VPs are trying to get their account executives to

16:51 self-source their own pipeline, but they're out of the game. They've not been doing that. They've

16:54 had SDRs kind of supporting them. The second thing is they have a pretty robust SDR motion,

16:59 but they're just not getting enough at bats for those SDRs for all the effort they're putting in

17:02 this either those sound like your world at all. And then they either bucket themselves into one or

17:08 both of those buckets, or they tell me no. And I say perfect. That's why I'm calling regardless of

17:12 the answer. So you could say, honestly, no, I've, I'm not experiencing this like, Oh, interesting.

17:18 Well, perfect. It's the reason I'm reaching out. You know, I do talk to a lot of folks who have

17:22 those problems. I'd be curious, how did you go about fixing that? And then it opens up the

17:26 conversation where I can now get intel on the account, they tried this new dialer or whatever,

17:32 or they bucket themselves into the pain that I want and have a talk track that goes all the way

17:35 through. And then you got to have a tight pitch, you got to have a call to action. And then you

17:40 have to disposition the call correctly. That's the most important thing. So that's my general

17:45 framework. It could get a lot more deep, but I'm sure people aren't following entirely.

17:49 No, I think that's super helpful. Just, um, one, knowing it doesn't have to be

17:56 an exact hook formula that you found on LinkedIn somewhere. Um, I think emphasis on tone. And I

18:04 think also what I was reading in there, a bit of emphasis on authenticity. So not lying about the

18:12 reason why you're calling, not doing, you know, respecting the person that you're calling and then

18:18 also being authentic. And I do think it helps saying, Hey, I'm not here just to book a meeting.

18:22 So if I just learned something on this call, that's totally cool too. Yeah.

18:25 I think it helps give whoever's making that phone call a bit of empowerment there too.

18:31Don't be memorable until it's time to be memorable

18:31 I think it does. Yeah. You have to realize that you don't want to be actually a buddy of mine,

18:35 Ryan Reisert, who's pretty well known in this cold calling space. He talks about you don't

18:39 want to be memorable until it's time to be memorable, but you also don't want to be forgotten

18:43 when it's time to be remembered. And so you need to know that in the sales process. And on your

18:47 first conversation in a cold call, it's okay to be unmemorable, right? Because if someone answers,

18:52 they have the propensity to answer a call. You're likely to talk to them again, at least in the next

18:56 five or six styles. And so don't feel the need to rush into and force a meeting. It's take what you

19:03 can get from the conversation, disposition it correctly. So you know what you're doing next

19:06 time you call that person have good notes that you take notes are not connected with Anthony,

19:11 not interested on a note. So what, what did I get? Well, I wasn't interested. I was a sentiment,

19:18 whatever. And then you can leverage that in your next conversation. Anthony, we talked three months

19:24 ago, it was probably like the worst time I could have called you. But we talked about was boom,

19:28 boom, boom. They're gonna be like, Oh, yeah, I don't remember that. But yeah, go ahead.

19:32 Because you're not memorable. You don't need to be. And so just keep chipping away at these

19:35 conversations. Eventually, you'll have an open we had a, actually, yesterday, we booked a meeting

19:40 with a big named account. And if you look at the call logs, we had nine conversations with this

19:45 person. We were told to f off three of those nine. We were told not interested six of the

19:51 the other six. And then finally, you catch them at the right time, you have enough context, you've

19:55 built enough signals around the account or from previous conversations, whereas like, you know

19:58 what, actually, this does sound interesting. At that point, you are memorable, right? You've had

20:02 nine conversations. Makes a ton of sense. Any other non obvious things in the list building in the

20:09The list is the strategy — don't trust your data provider

20:09 follow up that people are just doing wrong? It lists what we talked about is the list is

20:16 the strategy, right? The ceiling of your outbound efforts is always going to be the quality of your

20:22 list. And I don't mean quality of the list, like I have good data for them, meaning I have the right

20:27 phone number. That is certainly a piece of it. But it's a subcategory underneath the targeting

20:32 itself. You know, the challenge that we ran into, and again, back to what you said earlier about

20:36 2020, and some of these is back to 2011, when you had predictable revenue come out by Aaron Ross,

20:42 who came out of Salesforce and had a nice, a nice time there and wrote a book about it.

20:47 That was like the deterioration of outbound was around that time. Because we fractionalize what

20:53 used to be a full cycle account executive role, which is like a very intentional, very smooth,

20:59 very like cohesive relationship you're building with your prospect, there's continuity there.

21:04 And predictable revenue came out and basically said, no, let's fractionalize and specialize.

21:08 Let's have, you know, a ease who used to open, you know, do their own prospecting, build their own

21:12 list, would then go into they do their own hunting, they would do the own, they're, they're

21:17 gathering, if you will, and they would nurture deals, they close and they'd even do retention

21:21 and upsells and account management. And nowadays, it's like you have an SDR, you have an AE, you

21:27 might even have a sales engineer, you probably have account managers and CX employees, you

21:31 fractionize is one role into like five. And so you lose stuff there. But nonetheless, when you create

21:37 all these different roles, you then have to create enablement for each of these roles. And one of the

21:42 enablements that has come out of the 20 teens into the 2020s is the accessibility of data.

21:49 There's, you know, it started off with discover or which then became zoom info, it then became like

21:54 Apollo, and then it now it's like the clays of the world and some of these other CLI tools.

21:59 And what we did was we commoditized data so much, and these databases are filled with hundreds of

22:04 millions of contacts that we now and it's so accessible for us, that we now trust those

22:09 systems to build us the list based off a very simple query. And they don't. And so to your

22:15 question, the non obvious thing is don't trust your data provider, use them leverage them.

22:20 However, there needs to be a process in play, where you cannot trust what comes out of there,

22:26 it has to go through a quality assurance check before it gets to the floor, because your ceiling

22:30 is going to be how quality that list is, if I'm targeting the wrong titles, then I can have all

22:34 the conversation in the world, but it's useless. If I'm targeting the right titles of the wrong

22:37 accounts, then it's useless. And so I think that's where people really fail and outbound is they

22:42 they fail at the very, very what we call the above the funnel work, which is list building and

22:48AI dossiers vs. what people actually tell you

22:48 messaging and things of that nature. Yeah, I think the research has gotten pretty lazy,

22:53 especially with AI thrown into the mix, too, because it looks so confident on paper, too,

23:00 if I as an example, if I'm going to do a brief before a sales call, and I'm going to ask it to

23:06 research the company, research the person, it's going to bring in all these things. And if I just

23:11 take it at face value, there's going to be something that I come to that call with that is

23:14 completely not relevant or just wrong. And I think that laziness has shown up like signal data is very

23:21 interesting. In theory, it sounds great, you know, six cents came out and was like, oh, buyer intent,

23:26 and then they came out recently like, well, and they've had a tough couple of years. But,

23:34 you know, we ran a side by side test of let's go gather all the signals that we think are important

23:39 from these third party signal tools for accounts we want to get into. And we built these dossiers

23:44 of what AI and what these platforms tell us. And then we simultaneously ran that same the same

23:50 accounts through a phone led motion where it's like, hey, our team is going to go talk to people

23:55 up and down the org chart, not for the purpose of booking meetings, but for the purpose of

23:58 conversations and getting Intel. And the signals are not only richer. When you have the conversations,

24:05 like the insights and the alpha, if you're familiar with like the cryptocurrency finance

24:09 term of getting alpha, the alpha you can get from those conversations is substantially richer and

24:14 more valuable. But you also find out that a lot of the AI stuff is inaccurate entirely.

24:20 Because you hear it from the people in the org that are telling you. And so, you know,

24:24 AI is going to tell you that this person in this department, because they have this title,

24:28 is probably decision maker. Well, you talked a little Jimmy over here, and Jim is like, oh,

24:31 no, it's actually Sally who's over here. And you're like, what? They're nowhere in this dossier that

24:35 we've had AI build. Or it's like, okay, they say they have 50 sales reps with AI. And you talk to

24:41 them like, no, we have 19. You know, okay, well, that I bucket you differently, though. So I think

24:47 that's where we just can't trust a lot of these things. And we have to verify. Yeah, you still

24:52Infantry to special forces: rebuilding the SDR org

24:52 have to talk to people. I'm curious, operationally, because there is a big move from the fractional

24:59 ized roles to full cycle AEs. Who, who do you put the responsibility on to do the outbound?

25:09 And what does it look like? So if you have a full cycle AEs, what percentage of their day

25:14 typically should they be spending, doing this, focused on this? And is there still a world where

25:20 you have SDR teams? And then last one, I'm stacking questions here. But then how do you,

25:26 if you're looking for intelligence, do you do anything different with the comp model if you

25:29 have an SDR team too? Yeah, I'm about to just, I'm gonna machine gun a bunch of stuff to you,

25:35 because this is something I think about. So where we have gone in the market is we're gonna go scale

25:41 headcount, right? And namely in the SDR function. This is largely due to stimulus money in 2020,

25:47 2021 from the government, create a bunch of fake money in the market and interest rates are next

25:52 to zero. So a bunch of money went into growth and go to market and go and capture demand and

25:56 go capture market share. Well, naturally that flowed itself into the SDR budget. We built this

26:01 massive orgs of SDRs. And so we went down this path of basically accepting extreme mediocrity at best

26:10 by scaling headcount. And people have gotten a lot smarter. And I sit in some of these,

26:15 you know, board meetings with these large private equity groups, I sit in with their like CRO and

26:19 residents and I sit in with their value creation team. And it's super common where it's like,

26:23 I just don't think that the SDR has a place in the future, to which I say the current SDR doesn't,

26:30 I agree. And the number of SDRs that are currently in the market, I would also agree should be cut

26:38 down to at least half if not more. So I'll try to answer the questions, probably not in order. But

26:44 what I'll say is where, where I think the market is going is we're moving from an infantry model

26:48 to a special forces model, which is historically we've gotten away with an infantry, right? It's

26:54 like go hire anybody, never they can enlist in the SDR role. We're going to pay them 60 grand,

26:58 70 grand a year. Maybe they make 90 grand after OT. To where we're no, it's like, no, we're going

27:03 to have a team that's half or a quarter of the size, but we're going to pay them a lot more

27:08 because they're special. They're like true specialists. They're conversationalists. They're

27:12 really, really good. They're going to make more money in this role than they could have made

27:16 anywhere else. And they're going to be far more effective and stay around longer because they're

27:19 more effective. And we're heavily invested in them. So that's one thing is I think that we're

27:23 moving in this direction of SDRs being a volume play to SDRs being a more strategic special forces.

27:29 I want smaller teams that are far more potent. I don't want to do the whole Pareto principle

27:33 where I have 50 reps and only 10 of them are worth a damn. You know, I want to have eight

27:38 and I want those eight to all be potent. Yes, there'll be a Pareto somewhere in there,

27:42 but the disparity is not that big. But they're all highly effective and very profitable.

27:47 So that's one thing. The second thing is I think full cycle AEs should have never left the market.

27:52 Like if you look mathematically or if you look from a metrics perspective at a funnel,

27:57 the SDR is always going to have a lower meeting rate. They're going to have a lower show rate.

28:01 They're going to have a lower qualified opportunity rate. And they're likely it's going to be on par

28:06 with maybe slightly lower win rate. So yes, they can do more volume of setting more meetings,

28:11 but their meeting rates can be lower. So that requires more volume, less they're going to show

28:14 up lesser to be qualified, less they're going to close. If you look at the AE, they can make a

28:19 fraction of the dials and have two, three times the meeting rate. They can have a 15, 20 point

28:24 higher meeting show rate. They can have a 20, 30 point higher qualification rate because they're

28:29 more selective of who they put on their calendar. And then naturally their win rates higher because

28:33 they there's continuity throughout this whole process. So my view is that it should have never

28:38 left. It's more effective, even at the substantially less volume. And where I think that the world

28:43 should move to, and where I'm starting to see glimmers of this, and I've been running this play

28:47 for 10 years, is the SDR's job is not to book meetings, just to book commerce, it's to have

28:52 conversations. Will meetings come from that naturally? But what about the rest? There should

28:57 be categories of conversations that we're cataloging, we call these dispositions or call

29:01 outcomes, where there's a subset of the conversation. So think of conversations as a subset of the

29:08 total contacts that I went after. And then think of subsets of those conversations as being highly

29:13 valuable, not on calendar people, right? So I might have a conversation with Anthony. We have a six

29:17 minute conversation. He's not ready to take a meeting with a random stranger yet, but we had

29:21 a great conversation, great insight, great intel. Should that stay in the camp of the SDR's

29:25 responsibility? Or should it go to the AE who's far more likely to have a better conversation

29:29 with that person? It should go over there. And so because the AE can't do as much activity,

29:34 you should narrow down the pool of people they go after, so that they can go be as lethal as

29:38 possible in that seat instead of keeping in the SDR's camp. So I think it's the shared responsibility

29:44 of they both need to be doing it. I still think full cycle AE should go cold to a larger list,

29:48 but I think they should hyper focus on this subset list that the SDR's are surfacing conversations

29:53 on. And I think the unification of those two plays is where the market has to move to,

29:58The MDR: an SDR who isn't allowed to book meetings

29:58 if you want us to be effective and profitable. And there's a third variation of this that I'm,

30:03 I've been playing with for about two years now called the MDR. It's the market development rep.

30:08 Let's hear it. So this is my favorite team. This is my biggest team, actually, in my company.

30:12 The MDR's role is to be an SDR. That's not a lot of book meetings.

30:16 Full style. So that's a hard, hard rule. Not a lot of book. Yep. So the MDR's role,

30:21 it's a marketing development rep. Their job is twofold. One is to do inbound intercepting.

30:27 They can book on those because those are inbound, but they intercepts form fills, opt-ins, content,

30:32 people that are on the website, et cetera. But predominantly their job is to go what we call

30:37 below the line inside of accounts that we want to break into. So let's just say let's just break an

30:41 account. I want to break into Zoom info. And Zoom info is a massive organization. Yes, there's a

30:49 handful of decision makers at the top, like James and Henry and Molly and some of these folks.

30:55 But the MDR's job is to go and talk to the directors, the managers, the AEs, the SDRs for us.

31:02 Can't book a meeting? I just want you to have a conversation. I want you to go gather as much

31:06 insight and intel as possible to then go feed a true dossier, like we talked about before,

31:10 the AI dossier versus the conversation one. And that dossier needs to get fed directly to the AE.

31:17 And so you have SDRs that do book meetings and have good conversations that pass to the AE.

31:21 You have the MDR that only has conversations and they pass these super valuable dossiers and intel

31:25 gather. We call it IGs. These IG reports to the AEs so that when the AE does go up to Henry or

31:31 James or Molly or any of these folks, they're now equipped with all this alpha signal from

31:36 down below. Like imagine I called you at the org. I said, hey, Anthony. Anthony Joe Gilkey at Tynax.

31:41 You and I haven't talked before. This is going to feel very random, but I've actually talked to 13

31:46 people at Zoom info in the past week. And I found out some super interesting facts. Do you have a

31:51 minute for me to kind of share some things I think would be interesting to you? Yeah, sure. Cool.

31:56 And then boom. Hey, we talked to a VP. He said this. We talked to a director. He said that we

32:00 talked to three SDRs. They had the same thread to the conversation that said this. It sounds like

32:05 this problem is starting to bubble up in the org. Is that something that's on your radar?

32:09 Like how is that conversation going to go? Except, yeah. And so I, you know, to wrap this in a bow,

32:17 I think there's MDRs that only have conversations and they build Intel gathered reports. You have

32:21 SDRs that are a little more senior. By the way, I arbitrage that MDR role. They're all in South

32:27 Africa. Good accents, super well educated, very talented people cost you 35 grand. SDR, for me,

32:36 U.S. based $120,000 base salary, which is way above market rates. So I get the best talent

32:42 and the AEs are on top of them. And so I think there's MDRs, there's SDRs, there's AEs

32:46 in a pod structure. And the conversation is kind of the nucleus, if you will.

32:52 One-to-one ratios between those roles or does it matter depending on

32:56 ACD? It matters based off of conversation volume. So I am very in a very fortunate position. I have

33:02 infinite access to my own tool, which means that, you know, when the market, the typical market's

33:07 getting three, four, 5% connect rates, we get 25. So I'm arming every employee. I basically turn

33:12 them into a super employee where they all have 25% connect, which means mathematically they're

33:16 talking to someone every four dials versus 30 dials. So they can make $60 in a day, but they

33:22 can have 12, 15 conversations. I can do a lot with that versus they can make $100 a day and have three.

33:29 And so we call them like super SDRs or super MDRs where it's like I can take one rep that has the

33:36 same capacity as someone else over here, someone else's org that has a 3% connect rate and they can

33:40 do five times the work in the same amount of activity. And so we just arm them with this

33:46 ability to talk to more people and therefore they can then, one SDR can handle three AEs, four AEs.

33:51 You can have a MDR team of six that is doing the entire book of business Intel gathering.

33:58 And so it's, it's pretty powerful when you compound it together.

34:02 Yeah. And I think what a lot of people don't realize is that leverage, if you just get

34:08 a handful of conversion rate points increase, it could mean millions of dollars, tens of millions

34:15 at scale. So every little bit of intelligence you can get from those conversations, empowering the

34:20 AE with the right strategy, and then they can be the special forces person to go in and figure out

34:25The reach rate: why you'll only ever reach 200 of 1,000

34:25 how to, how to use that. Highly, highly effective. Yeah. I would love to hear tight necks. How

34:35 technically, how are you helping teams get higher connect rates, helping them operationalize this

34:42 whole part of their business? Yep. I will start this with Anthony. Do you answer cold calls yourself?

34:49 I do not. Okay. And if I called you five times over the next two months, because Anthony,

34:54 I've determined as a rep, you're important to me. Am I going to change the fact that you don't

34:58 want to answer cold calls? I think there's a handful of times where I have. So sparingly.

35:06 Yeah. So what we just saw was an example of human behavior, right? I do answer cold calls.

35:12 I'm a psycho and I guess I like doing that, but most of the people in the market would answer the

35:17 question. No. And the funny thing is every prospect we have has an answer to that question. You just

35:21 don't know the answer. So we have to start with that basis. Tight necks is founded on this idea

35:26 of what we call the reach rate. So the reach rate is a very simply explained metric that nobody

35:30 measures. Um, or if they do, they call something else. They don't pay attention to it, which is

35:35 if I have a thousand prospects out of those thousand people, if I just call through that

35:39 list of a thousand over and over and over again, seven, eight, nine times all the way through,

35:43 pull people out as I talk to them and I just call the remaining and I just keep calling and keep

35:46 calling the number of the thousand I will ever get ahold of is usually never going to excite exceed

35:51 200. So mathematically speaking, if I have a thousand prospects and let's say I have a 4%

35:56 connect rate, if I called those thousand people over and over and over again on a diminishing

36:01 rounds equation, which is I call a thousand, I talked to 44%. Um, I call the remaining nine 60,

36:08 I talked to 36 or whatever it is. If I do that through seven rounds, I will have probably reached

36:13 about the 200, but it would have taken me about 7,200 aisles to do it. So 7,000 dials to talk to

36:20 200 people. So Tynex is built on this idea that there is human behavior in all of us and that

36:26 human behavior dictates whether or not we answer, we might answer, or we don't answer a cold call.

36:32 Morbid curiosity is the role you're in. It's the season you're in, whatever.

36:37 The challenge that presents the teams is if 80% are unlikely to answer and 20% are ever,

36:43 and I don't know the answers to that question, what do I have to do as a rep? I have to treat

36:47 every single prospect the same because I don't know the answer. Anthony might answer, so I'm

36:51 gonna have to call him. First is Tynex, the data that we've built a model around is, is knowing who

36:57 are those 200 people that would have answered if you would have just called this list over and over

37:01 again. I know who they are before you hit dial. We use the analogy, super cheesy, but we use the

37:05 analogy of Neils in a haystack. You go to zoom info or Cognizum or Apollo or clay and you build a list

37:10 of a thousand people. That's a haystack. Every straw of hay is a contact with data attached to it.

37:15 My rep's job today is to sift through hay all day through dialing. Usually if they have a 4%

37:22 connect rate, they're going to sift through 24 straws of hay to finally pick up the one needle.

37:25 It's highly inefficient. It's very expensive. What Tynex essentially is, is where this cheesy

37:30 magnet, said it was cheesy, that goes in there and we pull out the 200 of those thousand

37:35 off the jump. And so now I can say, great, all 1000 are still important to me, but I would never

37:40 reach these 800. So I'm going to focus my phone efforts on these 200 because I would have gotten

37:44 them eventually. Why not get them right now and get them extremely efficiently. And every four dials

37:48 talk to one of them. And so that's what Tynex built was this, this model arounds analyzing

37:54 a metric ton of data, um, looking at telecom and carrier data, consumer data, professional data,

37:58 and we're triangulated to answer three questions. One is, is Anthony's phone number? Yes or no.

38:02 Data providers don't get it right all the time. In fact, they're wrong like 15 to 20% of the time.

38:07 Two is, is this an active number for Anthony, right? Is this one that is actively being

38:11 receiving and giving calls? And the third is when phone numbers call this phone number that we've

38:17 now attached to Anthony, when phone numbers call this phone number, what is the, what is the

38:22 propensity or the activity level against a phone number that does not commonly call this phone

38:26 number you can assume is a cold call. And from there, we take all these sources, we pulled into

38:31 a lake, we then say, great, run the model against it and say, we know yeses. It's a yes to all three

38:36 of these questions. Anthony's high intent for the phone. Or it's yes for the first two. We know it's

38:41 his, we know it's active. He doesn't answer. It's low intent for the phone. Or it's a no, it's not

38:46 Anthony's number. It's bad data. You can't even call that number because even if someone answers

38:49 it, it's, we call it Anthony and someone in jail answers. So that's the model we built. That's the

38:54 technology behind it is we know who's likely to answer the phone before you picked out or you hit

38:58Voicemail, AI screeners, and burning your shot

38:58 dial. Do you have an opinion? I'm going to be a data point of one. So I don't know if this is

39:06 common behavior. When I do get calls, I do actually listen to or read because it will

39:15 transcribe them on my iPhone. I will read every message that somebody leaves me. Do you commonly

39:21 leave messages? Do you avoid leaving messages? What's your, what's your thought on that?

39:26 So when we run a model and we say, hey, thousand prospects, here's the 200. They're high intent.

39:32 They're high intent regardless of whether they have their AI screener on or whatever.

39:39 That hasn't changed their behavior, actually. The AI screener has not changed connect rates,

39:44 believe it or not. People think it has. The second is, okay, if they're high intent, we're going to

39:48 keep calling them. If they're low intent, we're still going to call them because the definition

39:51 is it's low intent. It doesn't mean no. It doesn't mean they won't answer in 50 dials. It just means

39:56 that they're low intent to answer. So to your question, do I leave messages and stuff? If it's

40:02 AI screening, you leave a message on high intent regardless. If it's low intent, you leave a message

40:06 regardless. I don't leave voicemails on high intent because I know I'm going to get them eventually.

40:11 Mathematically speaking, I will reach Anthony in the next seven dials. 85% chance. If they're high

40:17 intent, if they're low intent, it's super unlikely they're ever going to answer. And so I want to give

40:21 as much surface area to get them to answer as possible. So there is, like, I really want to

40:25 care about the AI screening. I really want to care about the voicemail I leave. I really want to care

40:28 about the voicemail pointing to the email I sent them because my probability of giving them a phone

40:32 is very low. And so you'll notice this. You're low intent. You have the AI screener on. The people

40:39 who are adopting AI screening the most are the people who were never going to answer in the first

40:43 place. So it's actually a benefit to you because now you have a new ad channel which shows up on

40:47 here, which is a new ad, a pop-up, you know, called a push notification, right, that you never

40:56 had that real estate before. So now you have the real estate to maybe turn someone who's low intent

41:00 and wouldn't have answered a blank cold call with no context and now seeing a message they might now

41:04 answer. And so that's how we look at that is you have to, you know, we talk to people who say this

41:11 all the time, prospect to people the way they like to be prospected to. Like, let me answer the phone.

41:16 Just keep calling them. They'll answer. If they don't leave voicemails, do the AI screening, shoot

41:21 the emails, point to that in your in your voicemails and so on. So that would melt long-winded answer to

41:26 that. No, I think one of the nuances there, a lot of people, you may be burning your shot with that

41:32 high intent person because if you leave a message, then you're only gonna be able to leave so much

41:39 context. You're not gonna get the back and forth. But then you kind of burned your chance at having

41:43 a real conversation with that person. Yeah. So I think the ability to shift your strategy with

41:50 that intelligence is huge. Yeah, and something we built end of last year and we're really doubling

41:56 down on with our new platform launch in about a month and a half is we know who has AI turned on.

42:05 So now we're gonna have a subcategory of subcategories where it's like, hey, they're

42:08 high intent, no AI, they're high intent AI. So therefore, you know, we're building a platform

42:14 now where we can actually have you have scripting or messaging in front of you of like, hey, when

42:18 I run this high intent AI campaign, this is what I say. So I can start testing what works to give

42:23 me three eye screeners. And the same thing goes for low intent. They're low intent without AI

42:28 screening on, they're probably never gonna answer. They're low intent with AI screening. I have a

42:31 shot by dropping something with AI screening. So an AI screening is very different than voicemail,

42:36 right? You definitely don't want to leave a voicemail with high intent, because you will

42:41 probably blow your shot more than likely. Because people people recognize phone numbers more than

42:45 they recognize a conversation out the gate. It's just a weird thing. Like, remembering a name

42:50 amongst a bunch of words you said is harder than just constantly seeing the same four digits come

42:55 through. And if you leave a voicemail, and I saw it's a salesperson, and I saw it's a 4886

43:00 last four, I'm just not answering 4886 in the future. So at that point, then you got to like

43:04 call on different numbers. And that's a whole other technical game you got to play. So I'd rather

43:09 just not burn that conversation. Yeah, and these are all of the I'm sure you have a list of a

43:15 million other techniques and things to get this really dialed in. But these are all the things

43:20 that I know teams are not doing. And then they're saying phone doesn't work. Correct. And they're

43:26 not even trying or even doing the fundamentals right. Yeah, I mean, I was just on with you

43:35Outbound is not dying — but yours is

43:35 mentioned the intro, but updated partners is who invested in us back in January. And I read a

43:41 webinar for their portfolio, a lot of CROs and their VPs of sales and stuff. And the title of

43:49 the webinar was guaranteeing outbound sales success. And the whole thing was like, I know that's a bold

43:54 statement. But I've done this for almost a decade and 1.75 decades this one come up on two decades

44:02 here. And I've never lost it outbound. And so therefore I can with conviction and a backbone

44:08 say that you can guarantee and I've done them in many different types of companies, some with

44:12 product market fit, some without it, some in really hard markets, some in easier markets,

44:16 you can get up on to work if you just know what goes into that. And just most people just don't

44:21 know what goes into it. And then if they do know what goes into it, they don't know how to measure

44:25 against it and actually run this, this continuous game of improvement. Outbound is very similar to

44:31 like a PLG motion in the sense that it's a constant experimentation. Look at the data.

44:35 What's it tell me? Red work better. Placement here work better. Right. This, this list work better.

44:41 This messaging work better. This rep is actually delivering this message this way. We should train

44:45 the other reps to do that. When we do this type of follow up after this type of conversation,

44:49 we get this type of outcome. It's a game of constant experimentation, iteration. And if you

44:53 know how to run those experiments and you know which containers to run them in on list and message

44:58 and rep and follow up, you can guarantee the success. And so I'll tie that above with what I

45:02 told this group was outbound is not dying, but yours is. And then I have to walk them through.

45:09 Why is that? Right. It's not that outbound is wrong or that SDR motion is wrong or full cycle

45:14 is better than SDR and all these things. It's that the way that you're doing it today is what is wrong.

45:20Where AI belongs: the restaurant analogy

45:20 Well, and I think what a lot of people have done, they've loaded up their AI cannon and

45:26 spam their entire TAM and market. I know you have a lot of strong opinions on how AI should be used

45:33 in, in GTM. Where do you think it fits with the focus on phone and conversations and just outbound

45:41 in general? Well, fortunately, AI is not conversationally ready yet. Latency is there. You can tell it's AI.

45:50 Even the best of AI you can tell. For sure. And then also on that note, though, even

45:58 let's assume it was conversationally there. I do still think there's a difference between

46:03 connecting with someone and knowing that it's trust on the other side. It's trust. You know,

46:07 I think you and I talked about this before is outbound or excuse me, even sales in general,

46:13 and outbound being a subcategory of sales. It's a transaction between two people or two parties

46:19 based on trust. And so there's different types of trust. There's like trust you to get me the

46:24 right answer I want and trusting you inherently with helping guide this conversation and us trying

46:28 to collectively solve this problem that you have and I can solve for you. I think it's a big piece

46:33 of it. And I think with AI, like, even with like my script right there, it's really it's gonna be

46:40 really difficult for AI to emote what a human can emote perfectly. And I do think there's something

46:47 I'm not a big woo guy at all. Like, you know, very traditional, you know, Christian type of

46:53 background, but there's something to like, energy, AI doesn't have energy, like humanity does. And

47:00 there's something about sensing someone's energy and donation and what they're saying and why

47:05 they're saying it when they say it, that you're not going to be able to, to replicate. And I think

47:11 that if we take that out of sales, specifically, but a lot of go to market, then I think that we're

47:15 going to miss out on a lot of abilities to build trust and trust leads to transactions. That's just

47:21 my two cents on them on the whole thing. But I have a much larger one we talked about around my

47:25 analogy. But no, I'd love to get into that. I think the analogy you shared on our prep call

47:32 has been stuck in my head since that conversation. And I think it's framed how I think about

47:38 leveraging AI and go to market so much. Yeah. So how do I view AI and where does it live?

47:45 And I give the story of there's a restaurant in San Diego that my wife and I adore. And we go to

47:51 it every time we met in San Diego. And every time we go back, which is usually a couple of times a

47:55 year, we go to this restaurant. It's called Born and Raised. It's in little Italy district in San

48:01 Diego. And it's you go in and it's great Gatsby vibes, right? It's gold and mahogany. And you go

48:09 in and everyone's wearing tuxes. Like all the waiters and waitresses are dressed to the nines.

48:15 And then you sit down on these beautiful tables and the vibes are great. And you sit down and the

48:21 service and the experience that the people give you is pretty incredible, which is, you know,

48:25 they have cocktail bars, they mix, they do like, what do they call it? Mixology in front of you.

48:32 They have conversations. If you go up and go to the bathroom, you come back,

48:35 your drinks filled, your napkins folded, or you have a new napkin. You have new silverware.

48:39 It's perfect. You know, if you want dessert, they will have this ice cream thing where like

48:44 nitrous nitrous oxide or whatever they call it is like this fog is flowing on the table as they

48:48 mix this ice cream in front of you. It's like this incredible experience. And you're like, okay,

48:51 for two people, I'm, I'm super happy to pay 450 bucks for the night. Because the food is great,

48:57 but the experience is what I care about. And so the analogy I use for AI is if I was to go back to

49:02 that restaurant and you were to tell me that everything in the back of the house in the

49:07 kitchen was fully automated, stakes were made, same quality, fully automated, etc. I wouldn't care,

49:16 because I'm there for the experience on the front of the house. But if you told me that they're not

49:21 doing waiters anymore, and you order on an iPad, and it's faster, though, and I can be in and out

49:27 quicker, or I can get what I want with the click of a button, etc, but I miss this like human energy

49:31 and all this things that come with it, then I'll never come back ever again. Right. And so I use

49:38 that with AI, because I think that there is that what we call front of front of house AI in back of

49:42 house. And I use the same analogy five years ago, when it was front of house automation and back of

49:46 house automation, when AI wasn't really a thing yet. And so when it comes to sales, there are things

49:52 in the front of the house, you just can't remove the human from less you ruin the experience or

49:57 lessen the experience, whether you don't gather trust, or you don't build the relationship and so

50:02 on, that we're just not gonna be able to get rid of. And that's the conversations. It's things

50:06 that actually interface and touch the public market, your whether it's your customers, your prospects,

50:11 your market in general. If AI is doing all of it, I think you're gonna lose this experience in the

50:16 front end. That is what makes it special. That said, it's incredibly powerful and high leverage

50:21 to have it in the back of the house, right? The CRM high, the things that take me away from the

50:26 front of house. Like imagine if I went to born and raised and the guy who was the waiter who gave me

50:30 great experience also had to go spend his time in the back cooking the steak. I would lose time with

50:34 him and I'd lose this everything. So how do we get him in the front of the house more for the

50:38 experience and create better experiences by automating stuff in the back of the house?

50:42 Right? So it's CRM hygiene. It's the conversational intelligence. It's identifying signals that came

50:47 from the conversations. It's quality assurance on your list. It's all these things that you can have

50:52 in the back of the house that's administrative, that's very repeatable and process driven,

50:57 has strict guardrails and rules. Go to town, right? Like figure out how to have AI in the

51:03 back of the house to remove. If it can have a relatively similar efficacy as effective and you

51:09 can make it more efficient, then that's margin and that's leverage. It's just, if you want that to

51:14 creep its way into the front of the house, I think you're gonna have some degradation to your funnel

51:18 that you don't want. Yeah, the metaphor speaks to me on a lot of levels. One, running a services

51:26 business. I know how important the human interaction is with our clients and how important that part

51:32 is. I spent six years in a restaurant and I did every front of house position you could think of.

51:38What can't be automated out of the front of house

51:38 Busboy to bartender and I agree. I'm curious. What's the essence of that though? What is

51:48 there that cannot be replaced, that cannot be mechanized by AI? And if you were to put it into

51:57 a few words, what's in that front of house experience that has to be human?

52:03 If you and I had this podcast right now and I was able to give you all the same answers,

52:08 would we have the same conversation and connection? If you ask me, every question you've asked me and

52:14 my AI avatar could give you the exact same answers, would you feel differently about this

52:19 conversation than you and I have in this conversation right now? 100%. Yeah. So it

52:25 can be transactional. It can get you an outcome and get you an answer. AI can be very transactional

52:32 in nature and can get you answers faster, but there's an element of trust that I think only

52:38 comes through human connection. All right, there's different types of trust, but there's this human

52:42 connection trust where, you know, oftentimes when I'm deep into procurement with trying to buy

52:48 something for tight necks, it's silly to think that you could put any sales rep that says the

52:55 same thing to me as the sales rep that I've grown affinity towards and it's going to get the deal

53:01 done the same way, if at all. And so I think the same thing with the AI is AI can replicate all

53:06 the right answers, maybe even give better answers in some ways, but you lose this interaction that

53:11 I think is inherently human that you're just, it's never going to replace. If it does, we're in

53:18 trouble. I mean, let's be honest. Where I think this whole thing falls apart is when you're an AI

53:24 and I'm an AI in the sales process and you fully trust the AI to be autonomous to buy for your

53:30 company and I fully trust the AI to autonomously sell for my company and all they do is interact.

53:36 Okay, we're in trouble. But so long as there's a human element on either side of the party,

53:42 of the aisle and in a transaction, I think that there needs to be a jersey matching of humanity

53:48 there. I think that's the essence. Is there something there that I don't even know how to

53:52 explain outside of we're all created beings and there's something between knowing that you're a

54:00 dad or a husband or a wife or a mother or a sister or a brother and you have hobbies that are outside

54:05 of your title that you wear at work, the jersey you walk into the office with. Knowing that about

54:13 someone is, it's unique. It's part of the unique human experience that I don't think you can

54:19 necessarily automate out. At least in like B2B, higher transaction stuff, do I think AI is

54:25 touching PLG and more consumer-based? Of course, because it's a very transactional sale. But if

54:32 you get into a sale that has any level of complexity or any level of value or expense to it or cost,

54:38 I think that the larger the transaction, the more complex the transaction, the more trust is required.

54:45Effort, efficiency, effectiveness: why more volume backfires

54:45 Really, really well said. I think a lot of people are getting obsessed with

54:51 just getting every bit of efficiency out of their system. I think there's two ways. There's

54:56 effectiveness that you can get with AI power and then there's efficiency, which really has

55:04 a diminishing return at a certain point. But how do you think about that and where do you think

55:08 it's going to be going in the future? Yeah, I think that what we have seen from the 20-teens

55:15 to the 2020s is a massive move towards because things have become less effective. Headwinds have

55:21 entered the market. With email, it's blacklisting domains. With LinkedIn, it's throttling how many

55:26 connections you can send. With phone, it's spam carriers, spamming phone numbers and saying spam

55:31 likely. Where there is an increase or a decrease in effectiveness, people tend to then try to solve

55:37 that with effort. There's effort, there's efficiency, and there's effectiveness. It's the

55:44 3Es. They've tried to up the volume. If I used to get these results on 100 dials, for example,

55:54 and now I'm getting half those results on the same amount of dials, then naturally, if I want

55:57 to get back to where I was, I need to make double the amount of dials to get back to where I was or

56:01 triple if I want to get past that. The challenge with that is when you increase the volume,

56:07The 30x case study: 200,000 dials vs. 8,000

56:07 you increase the friction and the resistance as well. I have a case study. We just ran this with

56:13 a customer of ours that they came and piloted us a year ago. I said, "Hey, if you continue to know

56:18 this path, here's what's going to happen." They didn't believe me, naturally. I told you so,

56:24 guy, I'm just going to show you the data. They ended up going for 11 months straight,

56:28 running the same path they were running. They came back to me like, "You were right,

56:32 but we can't pinpoint what was wrong." I was like, "I told you what was wrong. I'll do it again."

56:36 I said, "How about this? Give me your call logs," because they were obsessed with parallel dialing.

56:42 "Give me your call logs for the last 11 months and I will tell you in the next 30

56:44 minutes what's wrong." They have call logs where they made 200,000 dials parallel dialing,

56:51 mass volume. They only made 8,000 dials single line dialing, meaning they did the power

56:58 function, which is one to one dialing, not five to five to five. When I showed them the outcome,

57:08 people got fired. What happened was they got fired because I told them a year ago and they

57:13 would avoid the last year. What happened was they made 20 times the amount of dials, so 200,000

57:21 versus 8,000. What happened in those 200,000 dials was they had an average connector of 2%.

57:30 2% connect rate on 200,000 dials, 4,000 connects. Their meeting rate was 2%. They had 2% meetings

57:40 on 2% dials on 200,000 dials. I then showed them power, which they had been paying attention to.

57:48 Some reps were starting to do power dialing on the side. They had 8,000 dials attributed.

57:52 So it was 4% the amount of dials. Generated 25% more outcomes. So the 8,000 dials had a

58:02 9% connect rate, 9.8. So it was almost a 5x difference in connect rate. But here's the

58:09 crazy part, was because parallel dialing creates such a terrible user experience for the person

58:12 answering. Their meeting rate was so low. The meeting rate for power dialing, which was slow,

58:18 1 to 1, slowest, smooth, smoothest, fast. Their meeting rate was 12% versus 2%.

58:24 So if you combine those two, it's 5 times higher connect rate. So I'm getting 5 times the amount

58:28 of it bats on the same amount of dials. And it was 6 times the amount of a meeting rate. You

58:33 combine those two, it's a 30x difference. So it took 30 times the amount of dials to get the same

58:41Why parallel dialing breaks: the bridge and the carriers

58:41 outcome parallel dialing as it did just single line dialing. What's happening there? If you could

58:47 break down the Y behind both of those. So a lot of it's the infrastructure behind it. So if you

58:53 parallel dial. Power dialing is simple. I'm placing one call from one phone number to one person.

59:00 Parallel dialing is I'm placing five calls to five people at one time. The person that answers

59:04 wins. Everyone else gets hung up on. So if you think about that experience in the first place,

59:11 one, let's sequentially, here's the bad things that happen. One is I don't know who's about

59:16 the answer of the five. So I'm not prepared. So that's going to hurt my meeting rate regardless.

59:21 Second is there's a mechanical aspect to parallel dialing where if I call five people at a time,

59:26 you have to have some sort of detection of voice of who answers. So let's just say the third person

59:32 on this list of five answers, it has to know the answered. And then it's going to hang up on the

59:37 other four to patch me. It's called a bridge to bridge me into the one that answered. There's a

59:42 delay that I don't know if you ever answered a cold call and you don't hear someone for like two or three seconds.

59:47 I'm thinking I've had that experience. And then I've had somebody calling me that hangs up in like

59:52 two rings. And I was wondering why that was happening. It's multiple. One is they could

59:58 just be spoofing or they could be doing some, see if you answer type of thing for a database. But

1:00:03 the main reason for the long pause is this, it's the mechanical aspect of this bridge. There's a

1:00:10 time delay between knowing who answered, hanging up on the rest and patching you through the one

1:00:14 that did that. It's like, you go, this is Joey. Hello. And then you go, Hey, Joey, you know, like

1:00:23 then someone jumps on to like, it's the worst user experience. So now I've degraded my, my opportunity

1:00:28 to actually have a conversation with this person. Plus you get hung up a lot in that, like I hang

1:00:33 up all the time. If I say hello and there's even a one second pause, I'm done. So I lost my bat

1:00:38 or they lost their bat. So that's the big thing. The biggest contributor to this though,

1:00:43 is telcos and carriers. So AT&T, T-Mobile, Verizon, all the European ones, all the Australian ones,

1:00:49 heavy in the US. They care about two things, regulation, and they care about user experience.

1:00:56 Just like, it's just like Facebook, right? Or LinkedIn is the algorithm is going to tune to

1:01:01 keep you on the platform and give you the best user experience possible. If they're giving you

1:01:05 terrible ads that make you log off, they had the data to support that, then they're going to stop

1:01:10 doing that. On cold email, Google and Outlook or Google and Microsoft are looking at how much spam

1:01:16 email is coming into my inbox. I hate logging into my email because I have all this spam. Well,

1:01:19 they're going to figure out a way to blacklist domains that are spam. Well, telcos and carriers

1:01:23 are doing the same thing and we're doing it to ourselves. What we hated about email getting done

1:01:27 to us with Google and Outlook. And so AT&T, T-Mobile, Verizon, they're now sharing data

1:01:32 and they're starting to find who is doing mass telemarketing, who is doing spam, and they have

1:01:39 this whole scoring system of how they, your phone number that you call from out of your dialer

1:01:44 is like a credit score. You either heard it with stuff you do or you help it with stuff you do,

1:01:49 right? Or you heard it with things you don't do or you help it with things you don't do.

1:01:54 And so the biggest thing that's happening is when you do volume, you are shoveling all this data to

1:01:58 the carriers that is basically saying this is spam. Blacklist the number. Blacklist the number.

1:02:04 Blacklist the number. And when that happens, like I guarantee Anthony, you don't like to

1:02:08 answer cold calls, but you say you'll answer them every now and then. If you get spam likely,

1:02:12 what is the odds you answer a spam likely? 0% chance. Right. So there are people who will answer

1:02:19 a clean number, but they won't answer spam, myself included. I will answer a clean number,

1:02:23 I won't answer spam. And so because you're doing all this volume, you are creating a larger wave

1:02:30 that comes at you from telcos and carriers, not to mention all the mechanical and infrastructure

01:02:34Preparation is the real edge

1:02:34 stuff I mentioned. So that's what happens. It makes a ton of sense. And even let's assume

1:02:43 technically all of those things get figured out. Let's assume you could take out the delay. Let's

1:02:48 assume you could warm up your numbers with the telcos or something. Let's just assume all that.

1:02:53 I think the thing that stuck out to me the most was being prepared for when that person answers,

1:03:00 being ready, being meaningful, intentional, thoughtful. And also before that call was even

1:03:08 dialed, having the posture of I don't need to book a meeting. I don't need to sell this person. I'm

1:03:14 here to learn. And if it's helpful, I'll move to a meeting that changes the entire thing.

1:03:20 Entirely. Yeah, we accept a lot of degradation to everything around

1:03:26 getting into a connect in exchange for getting the, you know, getting the connect. And we do

1:03:30 that through volume. And so I think it's a, it's a vortex that we're in that a lot of people find

1:03:36 themselves in, but not knowing. I mean, think about it from a sales perspective. If I told you,

1:03:40 hey, there might be five prospects in the waiting room. I'm not going to tell you

1:03:47 if none of them are there or if all five are there or if just one's there and the door opens

1:03:53 and one comes in, how prepared are you going to be for that prospect? You're not. And so that,

1:04:01 that is parallel dialing is you've got a waiting room that has a who knows who's in there. If

1:04:06 anyone's in there and the moment someone finally comes in, I don't know who it is. Right. And so

1:04:11 when you make a ton of volume, too, this is the benefit of Titan X is if I know who's going to

1:04:15 answer, I can sit down and methodically think through Anthony, Sarah, Johnny, everyone on this

1:04:22 list. And I can prepare for each of those because my odds of talking to them is not 25% in total.

1:04:27 It's 25% every time I try them. It's 85 to 90% chance over time that I will talk to this person.

1:04:34 So none of that is in vain. I'm, you know, every ounce of research I put into these calls,

1:04:40 90% of that's worthwhile versus if I have a hundred people and I research all 100 of them,

1:04:45 but only nine or 11 of them are ever going to answer in the next 500, 600 dials.

1:04:52 Most of that was waste. 90% of that was waste. And so that's, that's a fundamental difference

1:04:56 is not only can I be more prepared, I can also know they're likely to answer and I'm going to

1:05:00 reach them in the next seven dials. Mathematically speaking, I don't have this awkward pause in the

1:05:05 way. And because I'm making less dials and I'm having more conversations, more connected calls,

1:05:10 and I'm having longer conversations and more prepared, I'm training the telecoast to say

1:05:14 they're trustworthy. Don't spam that number. They have talk time that connects four out of,

1:05:19 you know, one out of four times they call someone. It's slower. They're making less dials. And so you

1:05:26 don't create the spam issue as easily. You don't have the pause that hurts the performance.

1:05:30 And you can be more prepared, which increases the performance when you get on the call.

1:05:35 It's very easy pitch. This is why we do well.

1:05:41 I've learned a ton on this and I know I'm working in high growth B2B SAS and AI companies that are

1:05:49 trying to scale quickly. They're not doing phone well. They're not, first of all, likely

1:05:56 not even leveraging because they don't even know where to start. Second, if they are doing it,

1:06:00 they're doing it completely wrong. And then just loading up the spam cannon for their,

1:06:05 for their dialers. And they're definitely not putting in the prep or having the posture and

1:06:10 perspective of what this even means for the business. So I've had probably 10 mind blowing

1:06:17 perspective changes throughout this conversation. So I really appreciate everything you share. One,

1:06:23 empathizing with the problem from the beginning through your story. And then the level of

1:06:28 commitment you have based on the size of bet you made. And the proof is in all the momentum

1:06:35 that Titan X is having right now. So I'm really, really excited for our customers to watch this,

1:06:42 for our audience to watch this, for my team to watch it. And I really enjoyed this. So thanks

01:06:47Where to find Joey and TitanX

1:06:47 for sharing everything you did. I'll just leave last thing, best way to get, if they didn't get

1:06:52 called by you, best way to get in touch with your team or, or find that next. Yeah. If you want to

1:06:58 find me, I'm pretty active on LinkedIn, linkedin.com/in/joagilkey. And then if you're interested in

1:07:05 Titan X, Titan X.io. We got a big launch coming up here in about a month and a half where I'm going

1:07:10 to take all this stuff we're talking about and force it to be a decision the market has to make.

1:07:15 So stay tuned to that. Can't wait. Can't wait. Well, Joey, thank you so much for everything.

1:07:21 I can't wait to see what you and Titan X do next. Thanks, brother. Thanks for having me on.