The problem with most M&A prospecting lists is not the format. It is the source.
If your targets come from a PitchBook filter, a SourceScrub export, or a data broker list built off NAICS codes and Dun & Bradstreet estimates, a list nearly identical to yours is also sitting in the inbox of every other buyer running a similar thesis.
By the time your outreach hits a $12M revenue HVAC distributor's email, that owner may have already heard from four other advisors this quarter. The companies that surface at the top of a standard platform filter surface at the top of every standard platform filter.
Differentiated deal flow comes from a differentiated list.
01. Start With the Criteria That Matter, Not the Filters That Exist
Most target lists are shaped by what the data provider can filter on: revenue range, employee count, NAICS code, geography, SIC classification. These are fine as a starting universe, but they are inputs, not criteria.
Before touching a data platform, write out what you are looking for in plain language:
- Profile the ideal seller as a person, not just a company: age, tenure, ownership percentage, and decision-making authority.
- Specify the operational characteristics that matter: single-site versus multi-site, family-owned versus PE-backed, asset-heavy versus service-based.
- Identify signals that suggest an owner is closer to a transition mindset: years in business, age of key equipment, whether the company has a named successor or second-generation leadership.
This plain-language profile will contain criteria that no data platform filters on. Your job is to find proxies for those criteria across multiple sources.
02. Build a Multi-Source Data Stack
No single data provider covers the lower-middle-market well. Each has coverage gaps.
PitchBook is strong on PE-backed and VC-backed companies, recent fundraises, and advisor relationships. It is weak on true owner-operated, non-institutional businesses, which form the core of the lower-middle-market.
SourceScrub covers more of the sub-$100M space and has good integration with intermediary transaction data. Its coverage weakens below $10M revenue, and ownership contact data requires significant enrichment.
Grata performs well on filtering by business characteristics that do not live in standard databases: website content signals, keyword-based industry classification, growth indicators. It surfaces companies that PitchBook and SourceScrub miss, particularly in fragmented verticals.
Secretary of State filings are free, underused, and often more current than any commercial database. In most states, filing data includes officer names with job titles, registration date (a proxy for years in business), and registered agent changes that can signal ownership transitions. The limitation: pulling and structuring this data at scale takes real work.
LinkedIn is the best source for verifying ownership contacts and tenure. A founder listed as "Owner, President" on LinkedIn for 17 years, whose profile shows no education or experience after age 22, is almost certainly the original founder still running the business. That tenure signal does not live in any commercial database at scale.
The firms building proprietary lists are triangulating across at least three of these sources and enriching the overlap, cross-referencing company records from SourceScrub with officer filings from state databases and LinkedIn profile tenure to build a record set that no single vendor can produce.
03. Enrich Before You Outreach
A list with a company name, a NAICS code, and an estimated revenue figure is not ready to dial.
Before outreach, each record should have:
- Verified owner name. Not "CEO" from a database — a name that appears in state filings, a news article, or a LinkedIn profile connected to the company's domain.
- Direct contact. Email and phone. The email should be verified (not guessed), tested against a validation tool, and matched to the actual domain of the business, not a generic Gmail. The phone should be a direct or cell number, not a general office line.
- Tenure estimate. How long has this owner been running this business? This requires triangulating LinkedIn join date, state filing registration date, and any news coverage that names the founder.
- Ownership percentage estimate. Public databases almost never have this. But some signals are proxies: whether the company has received institutional investment, whether there are co-founders or partners named in filings, and the business entity type.
The enrichment step is where most outreach programs fail. They build a large list and immediately load it into a sequencer. The resulting campaigns hit wrong emails, bounce off general inbox addresses, and reach people who are not the actual decision-maker.
Data decay compounds the problem. Validity's 2025 State of CRM Data Management research, which surveyed more than 600 CRM users, found that 76% of respondents said less than half of their organization's CRM data is accurate and complete. B2B contact data decays at roughly 22% per year, meaning a list cleaned twelve months ago has roughly one in five records that are now incorrect. Any list that has not been validated in the last 90 days should be re-verified before a live campaign touches it.
04. Apply an Event Layer
A static list contacts everyone simultaneously regardless of whether they are likely to engage this quarter.
The firms building proprietary pipelines add an event layer on top of their static universe, a scoring function that prioritizes outreach based on signals that predict engagement readiness:
- Operator age and tenure. Owners who are 55+ and have run the business for 10+ years are more likely to be in a transition horizon than a 42-year-old who took over four years ago. Flag these records for higher-priority outreach.
- Recent filing activity. An amendment to corporate officers, a change in registered agent, or a new certificate of assumed name can signal organizational change worth investigating.
- Industry consolidation signals. In verticals seeing active platform-building by PE sponsors, operators in adjacent companies often begin receiving outreach from multiple acquirers simultaneously, compressing their decision cycle.
- Debt maturity. For businesses with commercial real estate or equipment financing, approaching debt maturity can create a decision point around refinancing versus selling.
The event layer does not replace the core list. It changes the send order and the outreach cadence so that the contacts most likely to be in a transition mindset receive the first touches.
05. Maintain, Don't Archive
A list built once and used until the well runs dry is a campaign, not a sourcing asset.
The firms that produce consistent deal flow treat their target universe as a living database. That means:
- Monthly refreshes on officer filing data for the highest-priority targets
- Quarterly re-validation of email and phone data across the full list
- Removal of companies that have sold, merged, or gone to market through intermediaries. Once a company has entered a formal process, it is no longer a proprietary target.
- Addition of new companies that hit the criteria as the universe naturally grows and as thesis refinement opens new segments
A 3,000-company target list that is actively maintained is worth more than a 30,000-company list that was pulled eighteen months ago and has not been touched since.
06. The Quality Test
Before a list goes into outreach, run it against this checklist:
- Can you name the owner of every company on the list? If not, the records missing owner names should be enriched or removed.
- Are the emails verified? Unverified emails will bounce. Bounce rates above 3% damage sender reputation and pull down deliverability for the entire domain.
- Does the list contain duplicates across ownership entities? A holding company and its three operating subsidiaries might appear as four records, but they have one decision-maker. Consolidate before sequencing.
- Does the criteria match the brief? Pull a random sample of 50 records and read them. Do these look like the companies you are trying to reach? If not, find where the filter logic broke down.
Good lists are not large. The best M&A sourcing programs we run operate against lists of 500 to 3,000 highly qualified targets, not scraped databases with 50,000 records that have never been touched by a human.
Volume is a quality problem waiting to happen. Precision is a pipeline strategy.
Sources
- Validity, "The State of CRM Data Management in 2025" (B2B contact data accuracy and CRM health statistics)
- Grata (lower-middle-market company intelligence and deal sourcing platform)
- SourceScrub (M&A deal sourcing data for the sub-$100M market)
- PitchBook (PE/VC-backed company data and advisor relationship coverage)
- Secretary of State business filing databases (publicly available, state-level)
We build proprietary target lists for M&A buyers as part of our leads program, sourced from state filings, verified contact data, and enriched ownership signals. See how Leads works.