Target list: definition and practice

Definition

A target list contains businesses selected for consideration under an acquisition mandate. It can begin with client-supplied names, a market-mapping exercise, referrals, or several sources combined. Inclusion means a company is a candidate for assessment, not that it is for sale, qualified, contactable, or willing to engage.

A useful list defines its unit of record and its entry rules. Separate companies, branches, legal entities, and brands should not be mixed without explanation. Identity, ownership, capability, and research status need distinct fields so a row can move through the process without losing uncertainty. A company name and an email address alone do not establish either strategic fit or authority to initiate outreach.

In origination work

Resolve company identity and duplicates before paying for detailed research. Apply disqualifying questions early, then research the remaining criteria with retained supporting material. Keep an explicit state for not yet researched, unanswered, excluded, and ready for review. Docket can research a supplied list or build one; optional outreach still requires approval of each target and messaging. A dated export should make the selection rules and outstanding questions intelligible outside the platform.

What a target list is, and what it is not

A target list is a set of companies identified as potentially suitable for an acquisition mandate. Quality depends on three things: how completely the universe was defined, how accurately each entry represents a single real business, and how well each entry's fit with the criteria has been evidenced. A list can be long and poor, or short and strong.

Completeness is hard to know. Government statistics give totals for an industry by area, such as counts of establishments and firms by size class, which can be compared against the number of distinct businesses in a list. A large gap suggests missing coverage or a different definition. Independent assessments of commercial establishment databases have found significant differences from government data, which is a reminder that no single source is complete.

Building a list that can be audited

Start with the criteria, then choose sources that can supply the relevant facts. For each entry, store a unique company identifier, legal name, location, ownership status, the evidence for each criterion with date and source, and the status of any contact. Avoid free-text notes as the main store; typed fields allow filtering and checking, and free text drifts.

Deduplicate carefully. Branches, brands and affiliates turn one business into many rows, and the reverse mistake, merging two distinct businesses with similar names, is just as costly. Identifiers such as registry numbers, the federal contractor identifier and the legal entity identifier help, and probabilistic matching methods offer a principled way to compare uncertain pairs. Record how each merge was decided so that it can be reviewed.

Keeping the list current

Companies change. Owners sell, names change, entities merge and licences lapse. A list that is not refreshed degrades, with the rate depending on the field: contact details change faster than the date of formation. Decide a refresh interval for each field and record the date of last verification beside it, so that users can see how stale an entry might be.

Finally, measure the list. Track how many entries were verified, how many were found to be ineligible, how many were duplicates and how many resulted in conversations. These figures reveal where the research works and where it does not, and they support honest statements about coverage, such as "this list covers the entities we could identify in these sources, and the following known gaps exist".

Market map — A structured view of a defined market's participants, relationships, capabilities, and research coverage.
Deduplication — Identifying and consolidating repeated records while preserving evidence, history, and genuinely distinct entities.
Screening rubric — A defined set of questions, accepted answers, evidence requirements, and decision rules for assessing candidates.

Sources and further reading

County Business Patterns (CBP), U.S. Census Bureau. Establishment counts, employment and payroll by NAICS code and county. The spine of any honest market map.
Statistics of U.S. Businesses (SUSB), U.S. Census Bureau. Firm counts and employment by enterprise size, which is how you size the population of buyable companies.
An Assessment of the National Establishment Time Series (NETS) Database, Board of Governors of the Federal Reserve System (2017). An independent test of a widely used commercial establishment database against government data, with its accuracy findings.
A Theory for Record Linkage, Journal of the American Statistical Association (1969). The foundational probabilistic model for deciding whether two records describe the same entity.
How to Construct Nationally Representative Firm Level Data from the Orbis Global Database, National Bureau of Economic Research (2015). A careful account of what commercial company databases are missing and how their coverage skews by size and country. Read before trusting any vendor's universe count.

To apply these distinctions to your own acquisition criteria, discuss your research brief or inspect the demo platform.