Having more leads than you can work through feels like a good problem.
Hundreds of emails later… and the replies don’t come. So you send more because there are always more names waiting.
The list keeps you busy enough to avoid asking why any of those businesses would want to hear from you today.
That’s why I was intrigued when Jasper Vanu | Claude for GTM, who’s obsessed with finding useful things to do with Claude, explained how he finds the names on that list with an actual reason to buy now. 👇🏻
In July, a client rang me. He sells scheduling software and pays for one of those B2B data tools that does what the demo says it will.
He got the business to seven figures without a sales team. He shared his screen. There were 500 companies sitting in a spreadsheet, every one matching his filters.
I asked him who he was emailing first. He went quiet for a second. “I’m working through them alphabetically.”
His tool did its job and handed him the names. He had no way to pick between them, so he sorted by column A and started typing.
A match is not a reason
A match tells you a company looks like your customer. To prioritise it, you need to know what changed there recently.
Software finds matches brilliantly. Spotting useful signals takes more work.
Your data tool knows a company has 80 staff, sells software and is based in Manchester. It has no idea the operations lead walked out six weeks ago and nobody replaced her.
The operations lead leaving gives you something useful to open an email with.
The same filters produce the same list
You pick an industry, headcount band, region and maybe a tech tag. So does your competitor.
You run the query on Tuesday. He runs it on Wednesday. You both get the same 500 companies, and then you both email them.
Your advantage is the reason behind the list.
That reason is in data no vendor holds: your closed deals, call recordings, the customers who bought inside a fortnight and the ones who took nine months.
Your competitor cannot see any of it.
What your sales tool can’t decide
Which change costs somebody money?
A company opens a second site. So what? For that founder, it means shift planning falls apart because one manager can no longer keep two rotas straight in her head. He knows that from watching his own customers. His data tool doesn’t.
Start with your best customer
Look at the customer who bought quickly and later sent you two referrals. Then look at what was happening there in the month before they signed.
Look backwards from the sale
The pattern is sitting in your own history, in the last ten deals you won. Nobody else can read it.
Build the list from your own history
Put your last ten to twenty closed deals in one place: call transcripts, CRM exports, email threads and whatever notes you kept.
I used Claude Code to read a local folder containing eighteen deals in one go.
Then ask one narrow question: For each of these companies, what changed in the 90 days before they first replied to us?
Use the deal material to find the first clues, then check them against public sources. Tell it to look for hires, launches, new sites, leadership moves and tooling switches.
Ask which changes appear most often. You’re looking for what was happening inside those companies before they bought. Build the pool using the data tool you already pay for.
Use broad filters at this stage. You want a few hundred companies because this is only the starting pool. Take the pool and score every company against the changes you found in your closed deals. Ask for one line explaining each score. Only award a score when you can show the evidence behind it.
The evidence should come from places you can check, such as job boards for hires, local press and planning notices for new sites, or the company’s careers page for the volume of open roles.
That one line does the heavy lifting. It becomes the opening of your email, and it answers the question he couldn’t answer in July.
Weak buying signals
Some changes create more noise than buying intent.
Funding rounds attract sellers quickly, so the buyer’s inbox fills up at the same time. A raise shows that money has arrived. It doesn’t reveal a problem your product can solve.
Headcount growth is too broad to tell you much. Look for the hire that points to a specific gap.
Check the age of the evidence too. A role posted in March is filled or forgotten by July. Signals go stale, so set a window of about six weeks and bin the rest.
What happened when we rebuilt the list
For the scheduling software company, we rebuilt the list around three signals tied directly to the problem it fixes.
A new Operations Manager or Regional Director, because new leaders pull apart old systems in their first 90 days.
A second site announced or leased, which is the point where spreadsheet shift planning stops working.
Five or more part-time or hourly roles posted at once, which means the workforce is growing faster than anyone can schedule it.
About 4,000 companies fit the broad filters. In any month, a few hundred showed one of those changes. Those few hundred became the list, and for the first time we had something useful to write about.
Each email opened on the change found at that company. The volume barely changed: roughly 1,000 emails in June and another 1,000 in August.
August is the worst outbound month of the year in Europe, which makes the increase harder to dismiss. His reply rate went from 0.9% to 7.6%. We filtered out bounces and out-of-office responses, so every reply was written by a person.
Cleaner addresses will have helped the reply rate. The copy got better because the list gave him something to say.
Find your reason to write
Pick one company from the list your data tool gave you this morning and say out loud why it needs you this month.
If you can’t answer, open your last ten won deals and look for what changed before those customers bought. Find twenty companies where that same change is happening now.
⚒️ Want the five Claude GTM skills founders use to win new clients without hiring more sellers? Get them free at claudegtmskills.com
👤 Jasper Vanuytrecht is a fractional GTM lead who helps B2B founding teams use Claude Code to research prospects and build outbound systems they can run themselves. He has spent a decade working in sales and writes Founder’s GTM, where he shares practical ways to win new clients without hiring more sellers. Connect with Jasper on LinkedIn.
Going back through your own closed deals to find what changed before people bought is a great idea. That data's just sitting there.
A good reason to reach out beats a big list every time.