You can book more meetings from outbound all while contacting fewer people.
Earlier this year, we ran outbound on 142 leads that had all shown a buying signal. 12% of them replied, where cold usually sits around 2 to 3%, and we booked 19 meetings in two weeks.
Same on the phone. A recent cold call session on a warm intent list got me an 80% connection rate (I dial everyone twice) and 15% meetings booked.
So what changed? Mostly who we contact, and when. Here are 20 tips to help you do the same with signal-based outbound:
Your ICP first
1. Check it against the deals you actually closed. I did this on our HubSpot and mine was skipping 1-10 employee companies... 178 of my won deals were exactly those.
2. When I split my 500 won deals by industry, size and country, they came out as 3 segments. I'd give each one its own ICP.
3. One campaign per ICP too, or your first line ends up generic for everybody.
4. Before you approve a lead, check it's not already in your CRM. You really don't want to cold pitch someone who's already a customer.
Who goes on the list
5. A job posted for the second time is worth a look. Usually it means they're struggling to fill it.
6. Almost nobody watches public tenders, they're a pain to track. But the budget is there, and the person to contact is at the public body that published it.
7. Look for two different signals on the same account. Someone engaging with your competitor AND a new role opening on that team, that's interesting. Two likes, not so much.
8. A new VP or C-level arriving is the strongest one we've seen. They usually take a fresh look at their vendors in the first 90 days.
9. For every person on the list, write one line on why this week. If you can't, they probably shouldn't be there yet.
Calling
10. Only look up mobile numbers for the people you'll call this week. It's the most expensive thing to enrich, so I leave it for last.
11. Act quickly on a signal. After a funding round I'd say about two weeks, a reorg gives you a bit longer, maybe a month.
12. If an account with real potential opens your emails a few times, I call.
Website visitors
13. Use a visit for timing only. What you say should come from something they did in public, like a post they commented on.
14. And please never mention the visit, it just reads as creepy.
15. Before you act on one, double check you matched the right company and that the page they read has something to do with what you sell.
After that
16. When leads go into your sequencer, keep the signal attached, so whoever writes the email knows why you're reaching out now. Ours go to Overloop AI.
17. Read the source behind each signal before approving, sometimes it says something else than what you expected.
18. Auto-accept on new leads is fine once the fit scores mostly look right to you. Older leads stay manual anyway.
19. When deals close, go back and check which signals they came from, and watch more of those.
20. No CRM connected? Take your last ten wins and write down what was going on at each account in the month before you first spoke.
(bookmark for later)
Introducing an open-source bot on Meta's Muse Wonder that finds people asking on LinkedIn for what you sell... and has the email written before you've even seen their post.
Here's what it does for you:
- Finds people on LinkedIn asking for a provider in your category (through yourmax.ai)
- Drops anyone who doesn't fit your offer or whose timing is off, and tells you why
- Reads their company's site, so the email isn't generic
- Writes the email and two follow-ups
- Sends what you approve through Overloop AI, most urgent first
- Tells you who replied and drafts your answer
Your part is approving the drafts and pasting in the replies.
It runs on your laptop. A lead it drops costs two Muse Wonder calls at most, so you only pay to research and write the ones that pass.
Comment below and I'll send the repo.
Walking the talk!
@elonmusk called it in 2019
Can’t wait to avoid traffic jam while dropping the kids
BREAKING: Tesla’s new Roadster just flew, pulling a barrel roll over a Tesla Semi.
@elonmusk: "I've seen a lot of things, but I've never seen that before."
"We call that the kickflip."
Nicolas Finet retweeted
In partnership with Vinod Khosla (@vkhosla), I’m proud to introduce Reservoir.
Billionaires have owned their cells for years. Starting today, you can too.
Sign up today: withreservoir.com
We tested ChatGPT Ads for Sortlist.
16 days.
2 markets, DE and FR.
1,109 € spent.
510 clicks.
0 briefs.
Most ChatGPT users are on the free plan. Turns out people who don't pay for software rarely hire agencies.
Paused. Lesson learned for 1,109 €.
Hot take: most of what B2B teams spend on enrichment is wasted.
You pay for an email, often a phone, on every row, then skip a big part of the list anyway.
So I would flip it: begin with accounts where something just changed, and only enrich the people there who fit.
And honestly, you don't need their email to judge that. Their role, their company and what just changed are already in front of you, that is all the decision needs.
1. Start from what changed. Someone connected with your competitor's sales team, a sales role opened, a round closed.
If nothing moved, the row stays out, because you would have nothing real to say to them anyway.
2. Check fit, and give a reason for every skip. Right company, and the person who buys?
On yourmax.ai a skip asks you why (wrong company, wrong role, or the timing's off), and we use that to find people closer to your ICP.
3. Only now, enrich what's left. With us an email costs 3 credits and a phone 5, and you only pay for the phone when a number comes back.
If you enrich first, every row you skip has already cost you up to 8 credits.
4. Push them with the reason attached. Map the fit score into your Overloop AI fields, and the campaign arrives with the signal context still in it.
It works in a sheet too. One column for what changed and when, one for fit, and you only look up contact details for the rows that pass BOTH.
Once you trust your fit score, you can switch on Auto-enrich and it does step 3 for you on new leads above a threshold you pick.
Flipping the order also means you can afford to watch a lot more signals, because the enrichment bill only grows when someone passes fit.
I'm biased here, paying to enrich rows you never email is exactly what we wanted to kill with yourmax.ai. It only holds if your fit criteria are clear though, otherwise a lot of rows will probably just sit there waiting.
(bookmark for later)
I'm open sourcing the outbound bot we built on Claude Haiku 5.5.
The video below is an actual morning run: 912 leads read, the 21 best-fit companies checked, and today's Haiku reading came to 5 cents at API prices.
Every morning it:
- Pulls the people yourmax.ai flagged with a buying signal
- Checks each of their companies for anything new since yesterday
- Has Haiku 5.5 read what changed and flag the real signals, like a new sales role, a new leader or a funding round
- Ranks who to contact now and who to keep watching, and writes down why
- Pushes the ones that clear into your Overloop AI campaign, with that change attached
You run it from Claude Code. One command sets it up, another runs it, and nothing goes to Overloop until you switch it on.
Why Haiku? Our last bots ran on Opus 5.5, Grok 4.7 and GPT-6, and this job doesn't need that much model. It's mostly reading what changed on a few pages and saying whether it's a real signal.
On Haiku that's cheap enough to run on your whole list every morning, and it goes through your Claude Code login, so there's no API key to set up.
The article below has every step. Comment "gtm" and I'll send you the full repo link.
your CRM already knows who your best customers are.
most outbound tools never ask it.
here's the YourMax.ai x HubSpot playbook, step by step:
step 1: connect HubSpot
- your deals, contacts and companies become readable in chat
step 2: ask "what are my real ICPs?"
- YourMax.ai reads your closed-won deals
- breaks them down by industry, company size and country
step 3: get your real ICPs back
- 500 won deals turned into 3 clear segments
- with the buyers to target in each one
step 4: see what your current ICP is missing
- mine skipped 1-10 employee companies
- that's 178 of my won deals
step 5: update your ICP in one reply
- YourMax.ai asks "want me to update your ICP to match this revenue pattern?"
- say yes and your next leads follow what actually closes
HubSpot is in beta, admin access needed to connect it.
bookmark this if you want to set it up later.
🔥🔥
Just did a cold call session on the warm intent list
80% connection rate (I dial twice every time).
15% meeting booked 😳
this is strooooong
getting a phone number usually means export, enrich somewhere else, import again.
here's the phone playbook in YourMax.ai, step by step, without leaving the Leads page:
step 1: pick the leads worth calling
- start from your best ICP fits
- the Phone column shows "Reveal · 5 credits" on each lead
step 2: one lead or a batch
- reveal a single number from its row
- or select several leads and click Find phones
step 3: check the cost before it runs
- the dialog tells you upfront: 5 credits per number found, nothing when none is
- and how many credits you have left
step 4: let it run in the background
- YourMax.ai reveals the numbers it already holds and runs its enrichment waterfall for the rest
- numbers appear in their rows as they're found
step 5: automate it for new leads
- turn on Auto-enrich: it finds phones, or email and phone, for new leads above an ICP-fit threshold you choose
- it's off by default and only applies to new leads sourced while it's on
one setup note: you only pay when a number comes back. no result, no charge.
bookmark this if you want to set it up later.
Damn, X just paid me 533$ for the airport laptop guy!
9.8m views... about 5 cents per 1K.
Saw someone get 2.6k$ for almost the same reach (9.6m).
Turns out X only pays for views from Premium accounts, and apparently my viewers are not on Premium haha
Back to shipping 🚢
(there's also a totally not viral, but super useful article I put together recently - link in replies)
Karpathy put numbers on the AI gap.
0.2% of people are watching software build itself.
The other 99.8% still think the hard part is the prompt.
That gap is the biggest go-to-market opportunity I've seen in 12 years.
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.
- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.
The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.
So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
getting a phone number usually means export, enrich somewhere else, import again.
here's the phone playbook in YourMax.ai, step by step, without leaving the Leads page:
step 1: pick the leads worth calling
- start from your best ICP fits
- the Phone column shows "Reveal · 5 credits" on each lead
step 2: one lead or a batch
- reveal a single number from its row
- or select several leads and click Find phones
step 3: check the cost before it runs
- the dialog tells you upfront: 5 credits per number found, nothing when none is
- and how many credits you have left
step 4: let it run in the background
- YourMax.ai reveals the numbers it already holds and runs its enrichment waterfall for the rest
- numbers appear in their rows as they're found
step 5: automate it for new leads
- turn on Auto-enrich: it finds phones, or email and phone, for new leads above an ICP-fit threshold you choose
- it's off by default and only applies to new leads sourced while it's on
one setup note: you only pay when a number comes back. no result, no charge.
bookmark this if you want to set it up later.