BUSINESS DATA FOR M&A: WHY THERE IS NO SINGLE SOURCE OF TRUTH

There are a wide number of business data suppliers all claiming to have the best and most comprehensive business data, promising a turn-key solution to origination. In this white paper we explore whether this is fact or fiction. Is it any nearer to becoming true, or does it remain a pipe dream?

Unloq has worked with business data for the last ten years, and whilst searching has become easier, and depth has improved, we have yet to find a source that combines the best of all worlds. Until that time, we continue to use multiple data sources to provide the most thorough business information whilst remaining on the look out for the silver bullet for off-market deal flow.

From research carried out in January 2026, it is clear that if you only rely on one source of information you will miss out on the majority of acquisition opportunities, and the most likely outcome is that you will only reach up to 30% of your addressable market. That is, if you manage to contact the entire list.

To achieve coverage beyond 90%, you need to combine at least three data sources, and in this article we will present empirical evidence as to why this is the case.

Business Data: Four Premium M&A Suppliers
Research Methodology: Providing Representative Samples
Search One: SAAS (Software as a Service)
Search Two: Injection Moulding
Search Three: HVAC
Data Analysis and Interpretation: A Mixed Picture
Client Experience: The Qualitative Evidence
Conclusion: There are Six Fundamental Challenges
Challenge 1
Challenge 2
Challenge 3
Challenge 4
Challenge 5
Challenge 6
The Way Forward: To Execute the Best Campaign

Business Data: Four Premium M&A Suppliers

Unloq regularly tests different business data sources covering both local (United Kingdom) and International business data to ensure that we maintain the best possible mix of business data. We have reviewed over 20 different data sources in an effort to find the best coverage of data.

Where we find data sources with similar coverage, we choose the one with the stronger data based on sampling, meaning that our sources are defined by the additional coverage they offer.

Unloq currently subscribes to 6 paid data sources as well as using additional freely available information sources across the Internet. This generates a 90%+ data coverage over time.

The list price of the range of data sources we use is between £50k and £60k per annum.

SEARCH A

One of the most popular sources of UK company data for the purpose of M&A. They use a combination of Companies House data supported by website scraping to provide information. They also have a range of additional sources of data that provide additional depth to their content.

SEARCH B

A European company data supplier primarily using individual countries’ company registries and subsidising it with website scraping and locally-sourced data to provide additional depth of information.

SEARCH C

A global research and data gathering platform of both business and employee data using advanced web scraping technology and realtime data gathering, including signals, to provide a global company data resource which is constantly refreshed.

SEARCH D

An international research platform, which prides itself on the greatest coverage of businesses, it mainly targets M&A, but offers more consolidated business data for a wider range of B2B applications.

Research Methodology: Providing Representative Samples

To move from assumption to evidence, we considered three distinct searches within the UK private business marketplace. In this we have considered different sectors, with different characteristics, but all are popular areas of origination: Software, Engineering and Services.

The data compiled in these lists would be assessed individually through a comprehensive first pass before eventually being filtered down to suit the specific client needs, but the ratios would remain intact. The larger the source list, the greater the number of target companies.

From the searches selected, we listed the resulting businesses and spot checked them to ensure that each list contained the right types of companies. We then compared the lists of companies to consider overall quantity, overlap and scale.

Search One: SAAS (Software as a Service)

Search parameters:

- Active Business
- In the United Kingdom
- More than 5 Employees
- £1-5m ARR

Total List Size: 2173 Unique Businesses

Data	Source A	Source B	Source C	Source D
Total	272	151	250	1579
% of Total	12.5%	7.0%	11.5%	72.7%
Overlap	40	30	37	49
% Overlap of Total	1.8%	1.4%	1.7%	2.3%

Search One Summary

The results revealed striking disparities. Source D captured 1,579 companies (72.7% of total), while Source B identified just 151 companies (7.0%). Most revealing was the overlap: Source D’s extensive list shared only 49 companies (2.3%) with the other sources combined.

To achieve over 90% coverage required three sources, of which one had to be Source D. An acquirer relying solely on Source B would see just 7% of their addressable market.

Search Two: Injection Moulding

Search parameters:

- Active Business
- In the United Kingdom
- More than 10 Employees
- £5-20m Revenue

Total List Size: 431 Unique Businesses

Data	Source A	Source B	Source C	Source D
Total	144	49	155	164
% of Total	33.4%	11.4%	36.0%	38.0%
Overlap	30	20	13	29
% Overlap of Total	9.7%	7.4%	5.8%	9.5%

Search Two Summary

Here, the picture changed dramatically. Source D remained strongest at 38.0%, but Source C delivered 36.0% and Source A contributed 33.4%. The overlap increased to 9.7% between Source A and the total—still remarkably low.

Achieving 90%+ coverage required three specific sources: A, C, and D. Choosing Source B alone would capture just 11.4% of targets.

Search Three: HVAC

Search parameters:

- Active Business
- In the United Kingdom
- More than 10 Employees
- £5-20m Revenue

Total List Size: 317 Unique Businesses

Data	Source A	Source B	Source C	Source D
Total	58	170	8	116
% of Total	18.3%	53.6%	2.5%	36.59%
Overlap	23	30	3	11
% Overlap of Total	7.3%	9.5%	1.0%	3.5%

Search Three Summary

The third search produced yet another pattern. Source B, weakest in the previous searches, suddenly emerged strongest at 53.6%. Source D contributed 36.6%, while Source C collapsed to just 2.5% coverage.

Again, three sources were required for 90%+ coverage, this time Sources B and D as essential components.

Data Analysis and Interpretation: A Mixed Picture

DATA ANALYSIS – LIST SIZES

The variance in list sizes is significant, with the largest initial list being 1,579, and the smallest just 8.

Within a particular search, the variation is as pronounced with the smallest list being 16% of the largest list in SAAS, 30% in Injection Moulding, and just 5% in HVAC. A further challenge being that in all three cases different combinations of data suppliers were highest and lowest.

Overall Source D seems to offer the largest lists, however it is important to point out that the depth of data provided means that it will need more manual filtering and analysis after compilation. The rest of the data suppliers have strengths and weaknesses that are unpredictable when it comes to which sector they do or don’t perform in.

The highest potential list size is 73% if you chose Source D in SAAS, but if you chose Source C for HVAC you would get paltry 3% coverage. If you randomly chose one of these list suppliers, the average list coverage is merely 29%, which means on average you would get less than a third coverage of your market from one supplier. A much lower figure than you would have predicted, or that they would claim if you contacted them.

DATA ANALYSIS – LIST OVERLAP

The overlap data was a more surprising discovery. List suppliers are chosen to avoid significant overlap, so preferred suppliers are normally analysed around depth of data or extent of list. We knew, therefore, that overlaps would be lower than by randomly selecting two of the better known list suppliers. Even so the data told its own story.

The greatest numerical overlap between one list supplier and the total list was only 49 (2.25%) of a total list size of 2173 companies. The greatest overlap percentage was 9.74% (42 companies) out of a total list size of 431. The average of companies in one list shared with the others was just over 5%. The lowest was under 1%.

The data doesn’t lie: list overlap is much lower than you might expect between list suppliers and the sources providing the strongest ‘fresh’ companies varies depending on sectors targeted.

Client Experience: The Qualitative Evidence

The numbers above are revealing, and certainly they bring into sharp focus the challenges of dealing with business data and client experience confirms it.

A technology client who spent twelve months self-originating before engagement had produced what they considered a comprehensive list of appropriate targets. Within two months, that list was doubled
A specialist business software marketplace client brought a small list of companies for outreach, believing “that was all of them.” Additional research uncovered five more targets within a week—companies they’d never heard of despite operating in and thoroughly researching their super-niche sector
An adhesives industry client with highly specific criteria challenged the thoroughness of a compiled list, sending additional names they believed were “missing.” Fortunately, maintaining records of excluded companies meant sending back the exact criteria and specific reasons for excluding each one
A long-standing HVAC client challenged finding every company within a narrow EBITDA range that was exclusively HVAC with no additional services. The response: confidence that the data represented over 90% of the addressable market. They believed more existed and committed to conducting their own research. Six months later, no additional companies had been identified

WHY 100% COVERAGE REMAINS IMPOSSIBLE

The ‘goal’ of 100% of appropriate businesses is unachievable for a number of fundamental reasons:

Market Dynamics: Companies are starting, growing, and merging every minute of every day. The market is not static
Visibility Limitations: Some companies operate below the radar, particularly in niche sectors. Not every business seeks visibility
Business Evolution: Companies pivot far more than most realise. When they find a seam of opportunity, they change rapidly, often faster than data can track
Data Decay: All business data is out of date, sometimes only by days, but often by months and years

Only by choosing at least three, ideally four, data suppliers is it realistic to build lists of 90%+ of target companies, thereby providing the comprehensiveness that leads to better outcomes for acquisition projects.

Conclusion: There are Six Fundamental Challenges

The three sectors samples and four data suppliers tested present a good representation of the data available to the market at the moment. It challenges the promises of data suppliers as to the level of scope and depth of actionable data they possess.

Challenge 1

DON’T CHOOSE JUST ONE

If you want to build your own lists, if you choose one list supplier, then you will probably find on average 30% of your addressable market. It could be as high as 70%, but equally it could be under 10%. This has a trickle-down effect when it comes to outreach: fewer companies makes the whole deal process a lot tougher.

Challenge 2

NO ‘TRY BEFORE YOU BUY’?

When you choose a list supplier they are understandably protective about their data before you commit, but then it can be difficult to work out what the level of coverage is. Even if they give you a number, it is difficult to work out what proportion you will receive from the addressable market.

Challenge 3

BEING FOUND ≠ BEING THERE

Many data suppliers claim high coverage figures (90%+), but often the numbers do not translate into actionable companies. Business data is partial, therefore being in a database does not mean that the businesses are properly identified within the sectors they operate in. So the overlap figures may well be higher when compared with an entire data warehouse, but not for practical use and in a usable form for origination.

Challenge 4

THE COSTS RACK UP

To have all four of these sources combined will cost over £40k a year. This is a significant premium to pay before even accounting for the additional costs that come with originating. The only way in which this makes commercial sense is if the total cost is amortised over a number of projects rather than just one.

Challenge 5

SLEEPING WITH THE ENEMY

All data suppliers need as many clients as they can possibly get. They therefore offer breakfasts, talks, webinars and coaching to help you maximise their resources. The challenge is they are equipping your competition in the same way. Don’t look now, but the person sitting alongside you tucking into a croissant may be from the same company competing with you in a few months’ time.

Challenge 6

THE LIST IS JUST THE BEGINNING

This paper just covers the starting point for any origination journey. Getting the data right is crucial, but the rest of the process needs to be optimised. Bad data leads to bad outcomes. Limited data leads to limited outcomes. However, to have a comprehensive approach to origination means a much heavier investment in the process of outreach, the cost and time investment is much greater than you have been led to believe.

The Way Forward: To Execute the Best Campaign

The three sector samples and four data suppliers tested present a good sample of the data currently available to the market. The findings challenge the promises of data suppliers regarding the scope and depth of data they possess, revealing several clear implications.

The mathematics are unforgiving: single-source strategies deliver incomplete market views, creating blind spots that competitors exploiting multiple sources will fill. The variation in supplier strength across sectors means that even choosing the “best” supplier leaves vast portions of the market invisible.

For acquirers serious about comprehensive origination, the choice becomes clear: invest in multiple data sources and the expertise to synthesise them effectively, or accept that you are limiting your opportunity.

There is an alternative: by partnering with specialists such as Unloq, who have already made these investments and developed the methodologies to extract maximum value from combined sources, you have access to a different calculus. One which is performance-based but gives you and your team the freedom to focus further down the pipeline and on integration.

The data doesn’t lie. Neither should your origination strategy.

If You Want Ideal Flow Let’s Talk

There is only so much you can tell from reviewing our website, the best way to explore is to have a short meeting with one of our team.

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Unloq the Numbers

47%

On average 40%
of business owners
we contact are
Interested in meeting

For 90%+ market
data coverage
you need at least
four different sources

1:5

For every 1
target approached
we analyse at least
5 companies

Only 2% of
companies are
for sale at
any one time

100%

All the companies
acquired through us
are still trading or
part of a successful group

85%

Over 85% of the
transactions we
completed were
off market

The fixed cost
of in-house
origination is
4 times higher

15+

We are currently originating
in over 15 countries
for cross-border
work for clients

16%

Over a sixth of
introductions
result in a
written offer

20 Introductions
with the right businesses
will lead to a great
fitting acquisition

Recent Case Studies

Rapidly Growing, PE Backed
Fire & Security Group

Completed

Their 3rd Acquisition Sourced by Unloq

They seek to grow through completing strategic acquisitions.

MBI with extensive Investment experience
and property maintenance experience

Acquired

Plumbing & Heating Company in the South-East

Targets: 219
Contacts: 51
Introductions: 12
Deals: 1

Boutique Investment Group
focused in the IT industry

acquired

A leading IT Managed Service Provider
based in the Midlands

Targets: 200
Contacts: 79
Introductions: 26
Offers: 7
Acquisitions: 1

UK Adhesives Conglomerate

acquired

Specialist Adhesive Company

Targets: 50
Introductions: 18
Offers: 3
Acquisitions: 1

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