The businesses that will sell you their data are already raising their hand.
You just can't see them.
The Data Hunter by MyNewStaff.
We find established businesses ready for a conversation about selling their data to train AI. Your affiliates take it from there.
Your network isn't the bottleneck.
Guessing is.
Your company buys years of business records to train AI. Your affiliates need owners who have those records and will discuss a new revenue stream.
Customer files. Transactions. Call logs. Documents. Support tickets. Operating history creates the raw material.
But a business name on a list tells you almost nothing about readiness. Every wrong contact costs money, attention and time your affiliate could spend closing.
You pay to discover who was never a fit. Meanwhile, someone who is interested today can go cold tomorrow.
Stop buying chances.
Build a signal.
The usual way
- Buy a list. Hope the owner is on it.
- Run cold ads. Wait for the right click.
- Chase replies. Qualify everything by hand.
- Start over when the list goes stale.
The engine
- Find businesses with the right history.
- Prioritize owners researching now.
- Verify, scrub, then start a conversation.
- Deliver qualified owners. Learn every week.
MyNewStaff runs the full engine. Your network gets the conversations.
Start with businesses
worth talking to.
US businesses. 20+ employees.
5+ years in operation.
An owner or C-level decision-maker.
We look for businesses that have spent years producing useful records, then identify the person who can approve a deal.
You begin with a plausible data seller, instead of paying to discover a business is too small or too new.
Years of work.
Years of data.
Industry, headcount and operating history are the starting filters. The actual data opportunity is qualified in conversation.
Follow the
public money trail.
Government programs leave a public business footprint. We use it to find established companies.
Free SBA PPP releases include business name, address, industry code, jobs reported and loan size. Jobs reported helps filter for 20+ employees.
We also use SBA 7(a)/504 loans and federal grants and contracts through USAspending and SAM.gov.
These businesses participated in a government money program, kept records for it and went through federal verification. That is evidence of responding to money on the table, not proof they will sell data.
A useful footprint
- Business identity
- Name + address
- Industry
- Industry code
- Size signal
- Jobs reported
- Program history
- Loan size
Historical records are a starting point. Current company size and decision-maker details still need checking.
IRS claimant information is confidential. ERC appears only as a live search-intent signal in the next step.
A good fit is useful.
Good timing is better.
Our intent engine sees named decision-makers researching relevant topics right now. We pull fresh signals daily.
A recent search gives us a reason to prioritize someone today. It signals interest, not consent or a guaranteed sale.
Measured people in individual intent audiences. One export contained 93,000 rows. These are source audiences before filtering, not qualified businesses or promised pilot volume.
Three signals.
One better shortlist.
We match government history, current interest and company facts.
A 20+ employee, PPP-verified business whose owner searched a relevant topic this week goes to the top.
Size alone misses timing. Interest alone misses fit. The overlap removes noise before outreach starts.
Priority match
- Company fit
- 20+ staff, 5+ years
- Public footprint
- PPP record
- Fresh interest
- This week's search
- Next action
- Find the owner
Illustrative match, not an individual prospect.
Find the person.
Then verify the route.
We ask contact sources in order. The first verified hit wins. Then we stop looking.
We verify that the mobile line is wireless and the email is deliverable, so your message has a usable route to the decision-maker.
Several sources cover each other's gaps. Stopping at the first verified hit improves coverage while avoiding redundant lookups.
The best send
can be no send.
Every number is checked against federal and state Do-Not-Call lists and known TCPA-litigator lists before contact.
A shared suppression list keeps opted-out contacts out of future outreach. The system refuses to send to an unscrubbed list.
Checks happen before a message leaves. Your affiliates inherit a controlled process, not a cleanup job.
Scrubbing is one control. Applicable consent requirements and outreach rules still apply.
Measured on a real 2,532-person roster, before a single text.
This measured removal rate is specific to that roster.
Ask for a reply.
Start a conversation.
A short, personal text and email ask for a reply, not a click.
Reply YES and an AI assistant calls within minutes, asks real qualification questions and books the owner with a human closer.
The owner can respond where they already are. A fast follow-up keeps the conversation moving while interest is fresh.
Illustrative message. Launch copy and contact eligibility are checked for the pilot.
Measured time for the AI voice to speak first. Preparing the call while it rings cut 18 seconds of dead air.
Real intakes lasted 3 and 7 minutes. Every call is recorded with required notices and consent. A watchdog automatically stops the dialer if calls stop reaching humans.
Your affiliate gets
a qualified conversation.
A quiz or call confirms the fit. Consent is captured with a timestamp. The qualified handoff goes instantly to the team.
The affiliate begins with context and permission. Only qualified, consented conversations reach the network.
What gets handed over
- Owner or decision-maker identified
- Company size and operating history checked
- Available records and interest discussed
- Consent captured with timestamp
- Qualification answers + booked next step
A qualified conversation starts due diligence. It is not a completed data purchase or a determination of data rights.
Keep the signal.
Cut the waste.
Every topic gets a fixed 72-hour test window. Losers are frozen. Winners are scaled weekly.
Every topic faces the same test window. Spend follows observed results, instead of a hunch about which audience should work.
The weekly report follows the whole journey: contacts, replies, qualification and booked conversations. A reply alone is not the finish line.
Every layer
removes noise.
The whole engine, assembled.
Stage widths are illustrative, not measured conversion rates.
Do the math.
Then test it.
$0.39 per record + $0.025 first text = $0.415 per contacted business.
At 1%, that is 10 replies per 1,000 contacts and about $41.50 of contact cost per reply. This is what we measured on our proven system, not a promise for this vertical.
Contact cost = businesses × ($0.39 + $0.025)
Replies = businesses × reply rate ÷ 100
Contact cost per reply = contact cost ÷ replies
Scenario calculator, not a forecast. Contact cost covers the presented record and first text only, not a complete campaign budget. Replies are not qualified conversations, bookings or data deals.
More control.
Less waiting.
The advantage is the whole sequence: fit, timing, verified contact and a fast handoff.
| What matters | The Data Hunter | Paid search / social | Trade shows / sales teams |
|---|---|---|---|
| Cost per conversation | Qualified conversation cost: established in pilot. Measured contact cost per reply: about $41.50 at 1%. | Industry estimate: B2B leads commonly cost hundreds of dollars. Qualification adds steps. | Industry estimate: often far more per conversation, from hundreds to thousands of dollars. |
| Freshness | Daily intent pulls | Live clicks, when ads win attention | Event schedules or rep research cadence |
| Intent | Recent research + company fit | Search can be explicit; social often inferred | Interest discovered in conversation |
| Compliance | Pre-send scrubbing, suppression and consent controls | Ad, form and follow-up controls required | Collection and outreach controls required |
| Speed | YES to AI call within minutes | Depends on form and follow-up | Depends on event timing and rep capacity |
Channels vary by market and execution. A pilot measures the result that matters here: qualified, consented conversations for your network.
Built by
Luka Lah.
Founder of MyNewStaff.
“Proven outreach systems that made my clients $10,000,000+ this year.”
Luka Lah. Founder statement; not a projection for your pilot.
Worked with Kris Jenner on a two-year media campaign.
Played a role in launching Good American.
Worked on the Slovenian Government COVID campaign.
A focused pilot.
A clear answer.
Start with a defined audience and measure what reaches your affiliates.
Build the target + pull
Agree on industries, company fit and qualification criteria. Combine the public footprint with fresh intent and find decision-makers.
Scrub + outreach
Verify contacts, apply suppression and required consent checks, then launch the approved outreach. Test topics in 72-hour windows.
Deliver + learn
Deliver qualified, consented conversations and a weekly report. Review the results together, freeze weak topics and scale what works.
Your next data seller
is out there.
Let's find the right ones.
And give your network a reason to call.
We onboard a limited number of partner networks at a time. A pilot is how we establish fit and measure the opportunity.
Start a pilotSee the engine again ↑