Hey, Ilya here 👋
Your data research is probably broken.
Not your copy. Not your deliverability. The list.
The reply every outbound team knows
An average email to someone who has the problem right now gets replies.
A perfect email to someone who does not have it gets this reply. Polite, flattering, and a no ❌
We saw it on our own campaigns. 34,454 people contacted over 3 months. The emails landed in the inbox.
The copy was not the problem. Who received it was.
Why the standard way breaks
Most teams build lists the same way. Open a database (Apollo, Zoominfo, etc), filter by industry, size, country and title, export, write one message for everyone.
A filter tells you a company exists in a category. It does not tell you if that company has your problem, or has it now.
→ Industry labels are picked once and rarely updated.
→ Keyword search matches words in a profile, not what the company actually sells.
→ "Fintech" returns a payments startup, a bank, and an agency that once built an app for one.
A list that knows nothing specific can only produce a generic email.
"Just set up Clay"
Everyone's next move. And on paper, the right one.
Clay can do everything a good list needs. But it gives you the parts, not the process.
Someone has to choose the providers, order the waterfalls, write the fit prompt, get past blocked websites, build the verification, and stop credits burning on companies that never fit.
That someone is a GTM engineer. You hire one, or you become one.
And this work lands exactly when outbound is not working. You don't know yet if the problem is the list, the offer or the copy. The test that should take a few days waits behind a month of building tables.
Most basic Clay setups end the same way: a better list, a bigger bill, a similar reply rate.
You don't need Clay and a GTM engineer to get a good list
You need the process. Built, tested and run by people who do it every day.
That is our data research.
You send a brief. We run it. You get the list back in days.
How we do it
The order is the whole point. The usual workflow buys contacts first and filters later. We check the company first, and only then pay for people and emails.
→ Find. Every company that matches the brief, from several data sources, merged into one list.
→ Read. Every website in full. Product, pricing, customers, careers. Including the sites that block simple scrapers.
→ Fit check. AI scores each company against your ICP and writes down why. In a typical order, most of the filtered list is removed here. Those are the companies that would have replied "not relevant".
→ Signals and people. The reason to write now (hiring, funding, new leaders, stack changes), then the right decision-makers.
→ Prove. Every email goes through up to three independent checks. One rejection removes it.
What lands in your CRM looks like this:
That first line is the difference. You cannot write it from an export.
Don't take my word for it
I'm not asking you to sign anything.
Send one brief.
We run one batch, around 1,000 contacts, and deliver it within days.
Then put it next to the list you use today and compare two things:
→ Price. What you paid per contact you would actually send to.
→ Quality. How many contacts are at companies that really fit, with an email that works.
If ours doesn't win on both, you lost one batch. If it does, you know exactly what your current list is costing you.
No contract. No subscription. You pay for the batch.
Ilya
Talk to the team that runs this every day
Book a 30-minute call. We look at your outbound and tell you what we would change first.
Ilya AzovtsevCo-founder
Co-founder of GrowthBand. Helped scale lemlist from $20k MRR to $10M ARR and built automation at Expandi; now runs the cold email infrastructure behind 32,000+ mailboxes.
