Market Sizing for Acquisitions: Why Most Estimates Are Wrong
Updated: Sep 29
By
Caizen Co
Published on
September 2026
Market Sizing for Acquisitions: Why Most Estimates Are Wrong
Every investment thesis starts with a market size number. The target operates in a $3.2 billion market growing at 8 percent annually. That number appears on the first page of the CIM, anchors the management presentation, and flows directly into the underwriting model. By the time the deal reaches investment committee, that $3.2 billion has been referenced so many times it has acquired the weight of established fact.
Except it is usually not a fact. It is an estimate and most estimates in M&A due diligence would not survive thirty minutes of serious scrutiny.
The market size number in a typical CIM comes from one of three sources: a published industry report (Frost & Sullivan, IBISWorld, Grand View Research) that defines the market broadly enough to make the number impressive, a management estimate that self-servingly positions the company’s addressable opportunity, or a sell-side advisor’s model that starts with the desired conclusion and reverse-engineers the assumptions. None of these are designed to give the buyer an accurate view of the actual addressable opportunity. They are designed to make the deal look good.
As the transaction advisory practice at BD Emerson noted, a market model that fails scrutiny during commercial due diligence becomes a price reduction or worse, it becomes the foundation for a value creation plan that cannot deliver because the market it assumes does not exist at the stated size. For the broader framework on how market research creates value throughout the deal lifecycle, see our complete breakdown of market research for capital markets.
The Five Ways Market Sizing Goes Wrong in M&A
1. The Market Is Defined Too Broadly
This is the most common and most consequential failure. A company selling cybersecurity software for mid-market healthcare organizations claims to operate in the “global cybersecurity market” a $200 billion figure that includes defense contractors, enterprise IT, consumer antivirus, and every other subsegment the company will never serve. The number is technically accurate. It is strategically meaningless.
The fix: define the market at the level of the actual purchase decision. Who buys this product? In which geographies? At what price point? Through which channels? The defensible market is the one where the target can realistically win business not the one where the target’s product category exists somewhere in the taxonomy.
2. Top-Down Without Bottom-Up Validation
Top-down sizing takes a published market figure and carves it into segments using assumptions: the total market is $5 billion, the target’s segment is 15 percent of that, growth is 10 percent. The result is a number that looks precise ($750 million, growing to $1.2 billion) but rests entirely on allocation percentages that nobody validated.
Bottom-up sizing builds from demand fundamentals: number of potential buyers, purchase frequency, average transaction size, penetration rates. Each variable is sourced or estimated from primary research. The approaches should triangulate top-down providing the ceiling, bottom-up providing the reality check. When they diverge significantly, the gap is where the due diligence work needs to happen.
Most CDD market sizing is top-down only. The bottom-up work is harder, slower, and more expensive. It is also the part that catches errors.
3. Growth Rates Are Assumed, Not Modeled
A published report says the market grew at 12 percent last year. The model assumes 12 percent for the next five years. But growth rates are not constants they are functions of demand drivers, competitive dynamics, regulatory changes, and macroeconomic conditions that shift continuously.
A rigorous growth model identifies each driver separately: new customer acquisition rate, expansion within existing customers, pricing trends, regulatory tailwinds or headwinds, substitute products, and market saturation. Each driver has its own trajectory and its own evidence base. A single growth rate applied uniformly across the hold period is an assumption masquerading as a forecast.
4. Serviceable and Obtainable Markets Are Afterthoughts
TAM gets the headline. SAM and SOM get a single sentence each: “Our serviceable market is 30 percent of TAM” with no explanation of why 30 and not 20 or 40. SOM is often presented as a target share percentage chosen because it sounds reasonable “if we capture 3 percent of SAM over three years” without connecting it to sales capacity, conversion rates, deal cycles, or competitive displacement.
As Zenit Data’s analysis noted, when SOM is disconnected from real pipeline data and commercial capacity, it stops being an estimate and becomes a story. Investment committees increasingly challenge SOM assumptions during due diligence because they have seen how frequently the “credible” share capture turns out to be aspirational.
The fix: SOM must be derived from the ground up how many salespeople, closing at what rate, with what average deal size, over what cycle time. If the math does not support the revenue plan, the thesis has a structural problem that no amount of TAM adjustment can obscure.
5. Numbers Without Sources Are Opinions
A market sizing exhibit that states “The market is $2.4 billion” without citing the source, the methodology, or the confidence interval is not analysis. It is assertion. And yet this is what most CIM market sizing sections contain: a number, a growth rate, and a chart with no way for the buyer to evaluate whether the underlying methodology is sound.
Every number in a defensible market sizing should be traceable: where did the data come from, how was it processed, what assumptions were applied, and what would change the estimate. The model should distinguish between data points sourced from public filings, estimates derived from industry reports, and figures validated through primary research. If the buyer cannot trace a number back to its source, they cannot evaluate its reliability and a number whose reliability is unknown is a number that should not anchor a valuation.
What a Defensible Market Sizing Actually Looks Like
A market model built for acquisition due diligence should meet five standards:
Triangulated methodology. Top-down from industry data and bottom-up from demand fundamentals, with the gap between the two explicitly investigated and explained. If top-down says $800 million and bottom-up says $550 million, the explanation for the $250 million difference is where the insight lives.
Segmented by decision-relevant dimensions. Geography, customer type, application, channel, and price tier segmented at the level that the value creation plan will operate. If the post-acquisition strategy targets mid-market healthcare customers in the UK and UAE, the market sizing should show that specific segment, not the global total with a footnote.
Growth drivers modeled individually. Each growth driver with its own trajectory, evidence base, and sensitivity range. The output is not a single growth rate but a range reflecting the uncertainty in each driver and the model should show which driver assumptions have the most impact on the total.
SOM derived from commercial capacity. Based on sales headcount, conversion rates, deal cycle time, and competitive displacement not percentages applied to SAM. The SOM should be walkable: here are the specific customers or customer segments we expect to win, at what rate, through what channels, over what timeline.
Every assumption documented and walkable. The IC should be able to pick any number in the model and trace it back to a source, an assumption, or a primary research data point. If a number cannot be sourced, it should be flagged as an estimate with an explicit confidence interval.
The Primary Research Layer That Changes Everything
Published industry reports provide the starting framework. Primary research provides the ground truth.
Primary research for market sizing means direct conversations with buyers, competitors, channel partners, and industry experts to validate demand assumptions. How many times per year do you purchase this category of product? What do you pay? What alternatives are you considering? Would you switch from your current provider for a 15 percent price improvement? What about a 30 percent improvement?
This is the work that most market sizing exercises skip because it is slow and expensive. It is also the work that catches the errors that top-down models cannot see. A published report might estimate the market at $1.2 billion based on the total spend in the category. Primary research with 20 buyers might reveal that 40 percent of that spend is locked into multi-year contracts with an incumbent, effectively inaccessible to the target. The real addressable market is $720 million. That is a 40 percent reduction that changes the return math for the entire deal.
At Caizen Co., every market sizing engagement includes a primary research component typically 15 to 25 structured interviews with buyers, competitors, and channel participants specifically designed to validate or challenge the demand assumptions underlying the model. The model is the framework. The primary research is the evidence. Without both, the sizing is incomplete. For the deeper methodology discussion, see our overview of market research for capital markets.
How AI Is Changing Market Sizing and Where It Falls Short
AI has meaningfully compressed the secondary research phase of market sizing. Automated scraping of financial filings, patent databases, job postings, and industry publications can build a preliminary market landscape in hours rather than days. AI tools cross-reference company revenue disclosures against industry estimates, identify inconsistencies, and flag areas where published data conflicts with observable market activity.
Modern due diligence tools now include automated stress testers that cross-reference bottom-up demand data against third-party signals API usage patterns, hiring velocity, pricing disclosures, and infrastructure spend. These tools are genuinely useful for identifying market sizing claims that do not hold up against observable evidence.
But AI cannot replace primary research. It cannot call a procurement director and ask whether they are considering switching providers. It cannot assess the credibility of a management team’s growth assumptions by probing for the evidence behind them. It cannot determine whether a market is consolidating around two players or fragmenting into niches a distinction that fundamentally changes the competitive analysis underlying the sizing.
The right approach: use AI to build the framework faster and more comprehensively, then invest the time and budget saved into deeper primary research. AI accelerates the model. Primary research validates it.
What Deal Teams Should Demand from Their Sizing Provider
Five questions that separate rigorous market sizing from decorative arithmetic:
Show me the triangulation. “What does the top-down estimate say, what does the bottom-up estimate say, and why do they differ?” If the provider only ran one approach, the model is not validated.
Walk me through the SOM. “How many customers, at what deal size, closing at what rate, through what channel?” If SOM is a percentage of SAM without operational grounding, it is a guess.
Which assumptions are you least confident in? “What would change your estimate the most?” A provider who presents every assumption with equal confidence has not thought carefully about the uncertainty in their model.
What did the primary research show? “How many interviews, with whom, and what did they say about demand, pricing, and switching?” If the answer is “we did not conduct primary research,” the sizing rests on secondary data that nobody validated.
Where does this model disagree with management’s estimate? “If the CIM says $3.2 billion and your model says $2.1 billion, explain the gap.” The most valuable output of independent sizing is where it diverges from the narrative because that is where the valuation risk lives.
The Valuation Consequence
Market sizing is not an academic exercise. It is the foundation of the revenue forecast, which drives the valuation, which determines the price. An error in market sizing propagates through the entire deal model.
If the market is 30 percent smaller than assumed, the target’s addressable revenue potential is 30 percent lower. The growth rate built into the underwriting cannot be achieved through organic means. The value creation plan’s revenue initiatives have a lower ceiling. And the exit multiple may reflect a market position that does not hold up at the actual market size.
A $100,000 market sizing engagement that reveals a 30 percent overstatement on a $75 million deal prevents $22.5 million in overpayment. The investment in rigorous sizing is not a cost. It is the cheapest form of capital protection in the transaction.
And conversely, rigorous sizing that confirms the market opportunity at the stated level gives the deal team conviction to bid competitively because the commercial foundation has been independently validated, not just assumed from a slide in the CIM.
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