Founder note
8 min read
Why we built Leama: prospecting should start with fit, not filters
Jessy van den Berg
Founder, Prospactive
I did not build Leama because I could not find contact data.
There are plenty of tools for that.
I built it because the contact data kept arriving before the decision.
We would export companies that looked right on paper, then open every website and discover the same familiar problems:
- The company served consumers, not businesses.
- The industry label was technically correct but commercially useless.
- The employee count was in range, but the business model was wrong.
- The contact was senior, but had nothing to do with the problem.
- The email existed, but there was no credible reason to use it.
- The list was large, but nobody trusted it enough to start outreach.
The software had completed its job. Our work had barely started.
Filters are useful, but they only know what you selected
A filter can apply a clear rule perfectly.
Company size between 50 and 200. Located in the Netherlands. Industry equals software. Title contains sales.
The problem is that an ICP usually contains information that does not fit neatly into those fields.
Perhaps the company must sell to a certain type of customer. Perhaps it needs a considered sales motion. Perhaps it should be expanding, hiring, or changing leadership. Perhaps three adjacent categories look correct but never buy.
People who know their market carry those details in their heads.
The prospecting system usually does not.
That gap becomes list cleanup.
The real cost is not the data subscription
The obvious cost of prospecting is what the database or enrichment provider charges.
The larger cost is attention.
A weak record gets opened, researched, discussed, rewritten, assigned, sequenced, and sometimes contacted before someone confirms that the company never fit.
Multiply that by hundreds of records and the business is not simply paying for bad data. It is teaching the sales team not to trust the list.
Once that trust is gone, good prospects suffer too. Reps skip records, do shallow research, or create their own private lists because the official process feels unreliable.
I wanted the qualification to happen before that handoff.
Fit first, contact data second
The order matters.
The normal process is often:
- Find contacts.
- Enrich the contacts.
- Put them in a CRM.
- Decide whether they are good.
Leama reverses the middle:
- Define who counts.
- Find candidate companies.
- Check whether the company fits.
- Reject weak matches.
- Identify the relevant buyer.
- Find the contact data.
- Deliver the record with the reason.
This prevents the workflow from spending time and data credits on people at companies that should never enter the pipeline.
It also changes the output.
The record is not simply "Jess, VP Sales, Company X."
It can show that Company X sells a relevant B2B product, fits the target size, is hiring an outbound team, and has a VP Sales who likely owns the problem. That gives the user something to inspect.
A reason for every name
This became the product standard.
If Leama cannot explain why a prospect belongs, the prospect should not be accepted.
The explanation does not need to be long. It needs to be specific enough to test.
Weak:
Good company in the target industry.
Useful:
B2B compliance software for mid-market financial teams, 92 employees, expanding into Germany, with a newly hired VP Sales. Fits the target market and current expansion criterion.
The second note can be checked. It can also be challenged.
Perhaps Germany is outside the territory. Perhaps the product serves enterprises rather than the mid-market. Perhaps the new VP Sales is not the buyer for this offer.
Visible reasoning gives the user a way to correct the system.
The agent should be allowed to say no
A prospecting agent becomes useless when it treats the requested quantity as more important than the qualification standard.
If the ICP is narrow, finding 200 real fits may take longer. In some markets, the available pool may be smaller than expected.
The wrong response is to loosen the definition silently.
The agent needs explicit exclusions and a real rejection path.
"Close enough" is how a focused ICP turns back into a generic list.
The product should show rejected or review-needed records where useful, explain the reason, and let the user decide whether the criteria need changing.
Current signals are context, not mind reading
Buying signals make prospecting more useful, but they are easy to exaggerate.
A company hiring SDRs may need better prospecting. It may also have everything under control.
A funding round may create budget. It may have been allocated months ago.
A new executive may reconsider vendors. They may prefer the existing stack.
Leama can identify the observable event and explain why it could matter. It should not claim to know the prospect's private intention.
That is why I prefer "company signal" or "buying trigger" over "this company wants your product."
The signal gives the outreach a relevant starting point. The conversation discovers the truth.
Humans stay in control of outreach
It would be easy to turn prospecting, enrichment, and email sending into one large automatic loop.
That is not the default product.
Leama prepares the prospect. The user decides whether to contact it.
There are practical reasons:
- The user understands the offer and market better than the agent.
- Business data can be wrong or become outdated.
- The suggested angle may need rewriting.
- Outreach laws and norms vary by market and channel.
- A high-fit account may already have a relationship the system cannot see.
Automation should remove repetitive work, not remove responsibility.
Why give away 200 prospects?
Because the output is the only proof that matters.
I can explain the architecture, the agents, the scoring, and the research process. None of that tells you whether Leama understands your ICP.
The first 200 records do.
You can open them, check them, reject them, correct them, and decide whether you would genuinely contact the people inside.
There is no credit card because I do not want the first decision to be about billing. I want it to be about prospect quality.
After the starter batch, the free account receives 50 prospect credits each month. Teams that need more volume, recurring runs, exports, CRM delivery, or webhooks can upgrade.
What success looks like
The product succeeds when a salesperson opens a prospect and does not have to begin from zero.
They can see:
- What the company does
- Why it fits
- Who appears to own the problem
- Which business data was found
- Which current signal matters
- What uncertainty remains
- What might make a useful first question
The rep still thinks. The rep still decides. The rep still communicates like a person.
They simply begin with better research.
That is the Leama I wanted for my own outreach, and it is the standard we are building for everyone else.
Founder note
8 min read
Why we built Leama: prospecting should start with fit, not filters
Jessy van den Berg
Founder, Prospactive
I did not build Leama because I could not find contact data.
There are plenty of tools for that.
I built it because the contact data kept arriving before the decision.
We would export companies that looked right on paper, then open every website and discover the same familiar problems:
- The company served consumers, not businesses.
- The industry label was technically correct but commercially useless.
- The employee count was in range, but the business model was wrong.
- The contact was senior, but had nothing to do with the problem.
- The email existed, but there was no credible reason to use it.
- The list was large, but nobody trusted it enough to start outreach.
The software had completed its job. Our work had barely started.
Filters are useful, but they only know what you selected
A filter can apply a clear rule perfectly.
Company size between 50 and 200. Located in the Netherlands. Industry equals software. Title contains sales.
The problem is that an ICP usually contains information that does not fit neatly into those fields.
Perhaps the company must sell to a certain type of customer. Perhaps it needs a considered sales motion. Perhaps it should be expanding, hiring, or changing leadership. Perhaps three adjacent categories look correct but never buy.
People who know their market carry those details in their heads.
The prospecting system usually does not.
That gap becomes list cleanup.
The real cost is not the data subscription
The obvious cost of prospecting is what the database or enrichment provider charges.
The larger cost is attention.
A weak record gets opened, researched, discussed, rewritten, assigned, sequenced, and sometimes contacted before someone confirms that the company never fit.
Multiply that by hundreds of records and the business is not simply paying for bad data. It is teaching the sales team not to trust the list.
Once that trust is gone, good prospects suffer too. Reps skip records, do shallow research, or create their own private lists because the official process feels unreliable.
I wanted the qualification to happen before that handoff.
Fit first, contact data second
The order matters.
The normal process is often:
- Find contacts.
- Enrich the contacts.
- Put them in a CRM.
- Decide whether they are good.
Leama reverses the middle:
- Define who counts.
- Find candidate companies.
- Check whether the company fits.
- Reject weak matches.
- Identify the relevant buyer.
- Find the contact data.
- Deliver the record with the reason.
This prevents the workflow from spending time and data credits on people at companies that should never enter the pipeline.
It also changes the output.
The record is not simply "Jess, VP Sales, Company X."
It can show that Company X sells a relevant B2B product, fits the target size, is hiring an outbound team, and has a VP Sales who likely owns the problem. That gives the user something to inspect.
A reason for every name
This became the product standard.
If Leama cannot explain why a prospect belongs, the prospect should not be accepted.
The explanation does not need to be long. It needs to be specific enough to test.
Weak:
Good company in the target industry.
Useful:
B2B compliance software for mid-market financial teams, 92 employees, expanding into Germany, with a newly hired VP Sales. Fits the target market and current expansion criterion.
The second note can be checked. It can also be challenged.
Perhaps Germany is outside the territory. Perhaps the product serves enterprises rather than the mid-market. Perhaps the new VP Sales is not the buyer for this offer.
Visible reasoning gives the user a way to correct the system.
The agent should be allowed to say no
A prospecting agent becomes useless when it treats the requested quantity as more important than the qualification standard.
If the ICP is narrow, finding 200 real fits may take longer. In some markets, the available pool may be smaller than expected.
The wrong response is to loosen the definition silently.
The agent needs explicit exclusions and a real rejection path.
"Close enough" is how a focused ICP turns back into a generic list.
The product should show rejected or review-needed records where useful, explain the reason, and let the user decide whether the criteria need changing.
Current signals are context, not mind reading
Buying signals make prospecting more useful, but they are easy to exaggerate.
A company hiring SDRs may need better prospecting. It may also have everything under control.
A funding round may create budget. It may have been allocated months ago.
A new executive may reconsider vendors. They may prefer the existing stack.
Leama can identify the observable event and explain why it could matter. It should not claim to know the prospect's private intention.
That is why I prefer "company signal" or "buying trigger" over "this company wants your product."
The signal gives the outreach a relevant starting point. The conversation discovers the truth.
Humans stay in control of outreach
It would be easy to turn prospecting, enrichment, and email sending into one large automatic loop.
That is not the default product.
Leama prepares the prospect. The user decides whether to contact it.
There are practical reasons:
- The user understands the offer and market better than the agent.
- Business data can be wrong or become outdated.
- The suggested angle may need rewriting.
- Outreach laws and norms vary by market and channel.
- A high-fit account may already have a relationship the system cannot see.
Automation should remove repetitive work, not remove responsibility.
Why give away 200 prospects?
Because the output is the only proof that matters.
I can explain the architecture, the agents, the scoring, and the research process. None of that tells you whether Leama understands your ICP.
The first 200 records do.
You can open them, check them, reject them, correct them, and decide whether you would genuinely contact the people inside.
There is no credit card because I do not want the first decision to be about billing. I want it to be about prospect quality.
After the starter batch, the free account receives 50 prospect credits each month. Teams that need more volume, recurring runs, exports, CRM delivery, or webhooks can upgrade.
What success looks like
The product succeeds when a salesperson opens a prospect and does not have to begin from zero.
They can see:
- What the company does
- Why it fits
- Who appears to own the problem
- Which business data was found
- Which current signal matters
- What uncertainty remains
- What might make a useful first question
The rep still thinks. The rep still decides. The rep still communicates like a person.
They simply begin with better research.
That is the Leama I wanted for my own outreach, and it is the standard we are building for everyone else.
8 min read
Why we built Leama: prospecting should start with fit, not filters
Jessy van den Berg
Founder, Prospactive
I did not build Leama because I could not find contact data.
There are plenty of tools for that.
I built it because the contact data kept arriving before the decision.
We would export companies that looked right on paper, then open every website and discover the same familiar problems:
- The company served consumers, not businesses.
- The industry label was technically correct but commercially useless.
- The employee count was in range, but the business model was wrong.
- The contact was senior, but had nothing to do with the problem.
- The email existed, but there was no credible reason to use it.
- The list was large, but nobody trusted it enough to start outreach.
The software had completed its job. Our work had barely started.
Filters are useful, but they only know what you selected
A filter can apply a clear rule perfectly.
Company size between 50 and 200. Located in the Netherlands. Industry equals software. Title contains sales.
The problem is that an ICP usually contains information that does not fit neatly into those fields.
Perhaps the company must sell to a certain type of customer. Perhaps it needs a considered sales motion. Perhaps it should be expanding, hiring, or changing leadership. Perhaps three adjacent categories look correct but never buy.
People who know their market carry those details in their heads.
The prospecting system usually does not.
That gap becomes list cleanup.
The real cost is not the data subscription
The obvious cost of prospecting is what the database or enrichment provider charges.
The larger cost is attention.
A weak record gets opened, researched, discussed, rewritten, assigned, sequenced, and sometimes contacted before someone confirms that the company never fit.
Multiply that by hundreds of records and the business is not simply paying for bad data. It is teaching the sales team not to trust the list.
Once that trust is gone, good prospects suffer too. Reps skip records, do shallow research, or create their own private lists because the official process feels unreliable.
I wanted the qualification to happen before that handoff.
Fit first, contact data second
The order matters.
The normal process is often:
- Find contacts.
- Enrich the contacts.
- Put them in a CRM.
- Decide whether they are good.
Leama reverses the middle:
- Define who counts.
- Find candidate companies.
- Check whether the company fits.
- Reject weak matches.
- Identify the relevant buyer.
- Find the contact data.
- Deliver the record with the reason.
This prevents the workflow from spending time and data credits on people at companies that should never enter the pipeline.
It also changes the output.
The record is not simply "Jess, VP Sales, Company X."
It can show that Company X sells a relevant B2B product, fits the target size, is hiring an outbound team, and has a VP Sales who likely owns the problem. That gives the user something to inspect.
A reason for every name
This became the product standard.
If Leama cannot explain why a prospect belongs, the prospect should not be accepted.
The explanation does not need to be long. It needs to be specific enough to test.
Weak:
Good company in the target industry.
Useful:
B2B compliance software for mid-market financial teams, 92 employees, expanding into Germany, with a newly hired VP Sales. Fits the target market and current expansion criterion.
The second note can be checked. It can also be challenged.
Perhaps Germany is outside the territory. Perhaps the product serves enterprises rather than the mid-market. Perhaps the new VP Sales is not the buyer for this offer.
Visible reasoning gives the user a way to correct the system.
The agent should be allowed to say no
A prospecting agent becomes useless when it treats the requested quantity as more important than the qualification standard.
If the ICP is narrow, finding 200 real fits may take longer. In some markets, the available pool may be smaller than expected.
The wrong response is to loosen the definition silently.
The agent needs explicit exclusions and a real rejection path.
"Close enough" is how a focused ICP turns back into a generic list.
The product should show rejected or review-needed records where useful, explain the reason, and let the user decide whether the criteria need changing.
Current signals are context, not mind reading
Buying signals make prospecting more useful, but they are easy to exaggerate.
A company hiring SDRs may need better prospecting. It may also have everything under control.
A funding round may create budget. It may have been allocated months ago.
A new executive may reconsider vendors. They may prefer the existing stack.
Leama can identify the observable event and explain why it could matter. It should not claim to know the prospect's private intention.
That is why I prefer "company signal" or "buying trigger" over "this company wants your product."
The signal gives the outreach a relevant starting point. The conversation discovers the truth.
Humans stay in control of outreach
It would be easy to turn prospecting, enrichment, and email sending into one large automatic loop.
That is not the default product.
Leama prepares the prospect. The user decides whether to contact it.
There are practical reasons:
- The user understands the offer and market better than the agent.
- Business data can be wrong or become outdated.
- The suggested angle may need rewriting.
- Outreach laws and norms vary by market and channel.
- A high-fit account may already have a relationship the system cannot see.
Automation should remove repetitive work, not remove responsibility.
Why give away 200 prospects?
Because the output is the only proof that matters.
I can explain the architecture, the agents, the scoring, and the research process. None of that tells you whether Leama understands your ICP.
The first 200 records do.
You can open them, check them, reject them, correct them, and decide whether you would genuinely contact the people inside.
There is no credit card because I do not want the first decision to be about billing. I want it to be about prospect quality.
After the starter batch, the free account receives 50 prospect credits each month. Teams that need more volume, recurring runs, exports, CRM delivery, or webhooks can upgrade.
What success looks like
The product succeeds when a salesperson opens a prospect and does not have to begin from zero.
They can see:
- What the company does
- Why it fits
- Who appears to own the problem
- Which business data was found
- Which current signal matters
- What uncertainty remains
- What might make a useful first question
The rep still thinks. The rep still decides. The rep still communicates like a person.
They simply begin with better research.
That is the Leama I wanted for my own outreach, and it is the standard we are building for everyone else.