M&A BUSINESS DATA IS SPLINTERED, FOR GOOD

Every M&A business data supplier promises comprehensive coverage. They claim to have the best, most complete database. The implication is clear: subscribe to us, and you’ll have everything you need.

A compelling pitch, if it were true.

After 10 years working with business data, testing over 20 different suppliers, and conducting detailed research across multiple sectors, the evidence is clear: M&A business data is fundamentally splintered. No single source comes close to comprehensive coverage, and the fragmentation is far worse than most people realise.

The Fragmentation Reality

M&A Business data exists in fragments across multiple suppliers, each capturing different portions of the market.

In a white paper on business data we commissioned in early 2026, we tested four premium M&A data suppliers across three distinct business sectors: Software as a Service, Injection Moulding, and HVAC. We ran identical searches across all four suppliers and compared the results. What we discovered challenges everything data suppliers claim about their scope and depth.

The strongest supplier in one sector became the weakest in another. The supplier that captured 72.7% of SaaS companies managed just 36.6% of HVAC businesses. Meanwhile, a supplier that found only 7% of SaaS targets suddenly captured 53.6% of the HVAC market.

This isn’t about quality differences between suppliers. It’s about fundamental fragmentation in how M&A business data is captured, structured, and maintained.

The Overlap Myth

When you think about M&A business data suppliers, you probably assume significant overlap. After all, they’re all looking at the same market, pulling from similar sources like company registries, website scraping, and local data providers.

Across our three sector searches, the highest overlap between any single supplier and the total addressable market was just 9.7%. That was the best case. The average overlap was just over 5%. In one instance, it fell below 1%.

Think about what this means. When you subscribe to a M&A business data supplier, over 90% of the companies in their database won’t appear in competitor databases. Conversely, over 90% of companies in other databases won’t appear in theirs.

Different suppliers use different scraping technologies that find different websites. They classify businesses differently based on different taxonomies. They refresh data at different intervals, capturing companies at different stages of growth or evolution. They prioritise different geographies and sectors based on their core customer base.

The result is an M&A business data landscape where each supplier represents a partial, distinct view of the market. None of them wrong, but none of them complete.

Why Fragmentation is Inevitable

M&A business data fragmentation isn’t a temporary problem that better technology will solve. It’s inherent to the nature of business itself.

Markets move constantly. Companies are starting, growing, pivoting, merging, and closing every single day. Any database is a snapshot that’s immediately out of date. Different suppliers take their snapshots at different times using different methods, capturing different versions of a constantly shifting reality.

Visibility varies dramatically. Some businesses maintain active web presences that data scrapers easily find. Others operate below the radar with minimal digital footprint. A company might be perfectly viable for acquisition but virtually invisible to automated data gathering. Different suppliers have different methods for finding these hidden businesses, each capturing a different subset.

Classification is subjective. What sector does a company belong to if it manufactures hardware but generates most revenue from software subscriptions? Different suppliers make different judgment calls. Their algorithms prioritise different signals. A business might appear in a SaaS search on one platform and a manufacturing search on another, or neither, depending on how classification rules are structured.

Data sources differ. Companies House provides statutory data but it’s retrospective and often outdated by the time it’s filed. Website scraping provides current information but only for companies with informative websites. Local data providers offer depth in specific regions but limited coverage elsewhere. Every supplier uses a different mix of these sources, creating different strengths and weaknesses.

Evolution outpaces updates. Companies pivot far more than most people realise. When a business finds a new opportunity, it can shift focus in weeks. A company classified as traditional engineering in January might be offering software solutions by March. Data suppliers working on different update cycles will show different versions of that company for months.

This fragmentation is the inevitable result of trying to impose static structure on dynamic reality.

The Cost of Fragmentation

For anyone trying to build comprehensive lists for origination, fragmentation creates serious problems.

Incomplete market views. Relying on a single supplier means operating with partial information. You’re making strategic decisions about market opportunity based on a fragment of what’s actually available. Your assessment of market size, competitive landscape, and opportunity density is systematically skewed.

Missed opportunities. The company that would have been your perfect acquisition target might not exist in your chosen database. You’ll never contact them. You’ll never know they were there. Your competitors using different data sources will find them instead.

False confidence. Perhaps most dangerous is the illusion of completeness. When you run a search and get 200 results, you assume you’ve found most of the market. In reality, you might have found 30%. You’re operating with confidence that isn’t justified by the underlying data quality.

Resource misallocation. When your list is incomplete, your entire funnel is compromised. You’re spreading outreach resources across too few targets. You’re concluding response rates and market receptiveness based on unrepresentative samples. You’re optimising a process built on fragmentary data.

The Multi-Source Imperative

Our research revealed a clear pattern across all three sectors tested. Achieving 90%+ coverage of the addressable market required at least three data sources. Not just any three sources, but the right combination for that specific sector.

To give a useable example, for SaaS, comprehensive coverage required Sources A, C, and D. For Injection Moulding, it required Sources A, C, and D. For HVAC, it required Sources B, D, and one other. The specific combination varied, but the requirement for multiple sources remained constant.

Building comprehensive coverage means subscribing to multiple suppliers, learning the strengths and weaknesses of each, understanding which combination works for which sectors, and developing processes to merge and deduplicate data from different sources with different structures and formats.

For organisations running occasional searches, this investment rarely makes sense. For those running continuous origination across multiple sectors, it’s the only way to achieve comprehensive coverage.

Living With Fragmentation

M&A business data fragmentation isn’t going away. As long as markets evolve faster than databases update, as long as different suppliers use different methodologies, as long as business classification remains partly subjective, fragmentation will persist.

To combat this, some organisations will build internal capabilities: subscribing to multiple sources, developing data integration processes, maintaining the expertise to synthesise information from different suppliers effectively.

Others will partner with specialists who have already made those investments and amortise the costs across multiple clients and projects.

Either way, if you use just one source of data, your efforts will always be compromised.