Market Analysis & Customer Research
Foundations of Business Development - NIT Northern Institute of Technology / TUHH, Hamburg · part of my Technology Management MBA · study notes for revision.
Once you have an idea and a rough sense of the value it creates, two blunt questions decide whether it is a business or a hobby: is the market big enough, and do you actually understand the people you want to serve? This chapter is about answering both with evidence instead of hope - first by sizing the opportunity, then by segmenting the customers, and finally by going out and researching them directly.
1 · Why market analysis matters
Section titled “1 · Why market analysis matters”When start-ups die, the single biggest category of reasons is not a weak team, tough competition, or even running out of money on its own - it is market and customer-related: building something that too few people actually wanted, or wanted enough to pay for. The money runs out because the demand was never really there.
There’s a useful phrase for the thing you’re chasing: product-market fit - the moment your product clearly solves an urgent problem for a well-defined group of customers who will pay for it. Founders describe failure again and again in those exact terms: “we failed for the same reason 90% of tech start-ups fail - we didn’t find product-market fit before the cash ran out.”
The failure usually runs as a chain, not a single event:
The famous E10 fuel launch in Germany (a petrol with ten percent bio-ethanol) is a textbook case. The product was technically fine - independent scientists found roughly a two percent rise in consumption and no damage to almost any modern car - yet drivers boycotted it. Why? Nobody explained the risks and benefits, gas-station staff couldn’t answer questions, and the perceived risk was never reduced. Politics and industry assumed “green, eco and bio” would sell it on their own. It didn’t. A good product with no understanding of the customer’s fears is still a failed launch.
2 · Sizing the market: TAM, SAM, SOM
Section titled “2 · Sizing the market: TAM, SAM, SOM”Before you commit, you want a number for the prize. The standard way to express market potential is three nested figures, each smaller and more realistic than the last.
total demand for the whole category - everyone who could ever buy this type of thing
the slice your specific product actually fits - the product-market-fit portion
what you can realistically win in the first years, given your resources and reach
| Level | What it measures | How you narrow to it |
|---|---|---|
| TAM - Total Addressable Market | Total demand for the wider category or type of product/service | Start here: the whole pie |
| SAM - Serviceable Available Market | The demand your particular offering can best satisfy (the product-market-fit portion) | Filter TAM by what your product is actually suited to |
| SOM - Serviceable Obtainable Market | The share you can realistically capture given your resources and targets | Filter SAM by your sales reach, budget, channels and segment focus |
A worked example - private EV charging stations. Sizing the German market for 11 kW home wall-boxes ran roughly like this:
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TAM - take the forecast number of battery-electric cars in use by 2025 (about 3.3 million), assume a ratio of chargers to cars, multiply by an average station price (about 2,500 €). Result: a multi-billion-euro category.
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SAM - only some of those chargers are the 11 kW wall-box type your product serves. Apply that share (about sixty percent) to the TAM. The number shrinks to the part your product actually fits.
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SOM - you can only reach four major cities plus suburbs (about a quarter of the population) and only customers willing to buy online (about thirty percent of buyers). Multiply those filters onto the SAM. You land at a realistic first-years figure - tens of millions, not billions.
Top-down vs bottom-up
Section titled “Top-down vs bottom-up”There are two directions you can travel when you estimate these numbers, and they tend to disagree in a telling way.
- Start from the big category number (from market studies, statistics) and cut it down with assumptions: TAM → SAM → SOM
- Fast, uses published macro data
- Danger: “we only need one percent of a huge market” - easy to say, rarely true
- Best when the industry is established and well-measured
- Start from one thing you can actually count - visits a salesperson can make, one region, one customer group - and build upward
- Slower, but grounded in real capacity
- Ties the forecast to what you can do, not to what the market theoretically holds
- Usually more credible for a start-up
A third handy trick is analogy: when your market is too new to measure, borrow data from an established, similar market. A jet-surfboard maker sized its market by starting from worldwide JetSki sales and a comparable firm’s market share. And in practice most real estimates are a mix - a bit top-down, a bit bottom-up, a bit analogy - cross-checked against each other. The point is never a single perfect number; it is a defensible range built from stated assumptions you can later test and correct.
3 · Defining the target customer
Section titled “3 · Defining the target customer”A market is not one uniform blob of buyers. It is a mix of people and organisations with different needs, budgets and buying habits. Segmentation means slicing that population into groups so that inside each group people are as alike as possible, and between groups they are as different as possible. Get that right and every later decision - product, price, message, channel - has a clear addressee.
Bases for segmenting
Section titled “Bases for segmenting”The classic split is between describing who customers are and what they want. The first is easy to measure but crude; the second is more useful but harder to observe.
| Identifier variables (a priori - who they are) | Response variables (post-hoc - what they want) | |
|---|---|---|
| B2C (consumers) | Demographics (age, gender), socio-economics (income, job, education), psychographics (values, lifestyle, attitudes) | Benefits sought (price, reliability, service), usage situation and frequency, price sensitivity, loyalty and switching, openness to new things |
| B2B (businesses) | Company size, industry, location, financial situation, level of internationalisation | Same behavioural and needs-based cuts, applied to the buying organisation |
Choose a beachhead
Section titled “Choose a beachhead”You cannot serve everyone at once, and trying to is a classic start-up trap. The move is to pick one narrow but big-enough, underserved, profitable segment that fits your firm and product - a beachhead you enter first, prove yourself in, then expand from.
The project-software firm HQ Labs learned this the hard way. Version 1.0 targeted “SMEs in any industry” with generic features - and drowned: it had to learn the language of every industry, fight low software-affinity, and run long cold-sales cycles. Version 2.0 narrowed to agencies alone, with features built for exactly them (shared projects, freelancer integration, agency benchmarking). Suddenly the value was obvious, acceptance was high, and marketing could run inbound instead of cold-calling. Narrow won.
Build a persona - and know who’s who
Section titled “Build a persona - and know who’s who”Once the segment is validated, you make it vivid with a persona: a rich, semi-fictional portrait of a typical customer in that segment, based on real research. Segmentation proves the sub-group exists; the persona keeps a busy founding team focused on it and makes internal and pitch communication concrete.
- 47, married, two kids; a lifelong learner, short on time
- ”I care about the environment - as long as it doesn’t hurt my wallet.”
- Trusts scientific proof and numbers; not very tech-savvy; dislikes social sharing
- Wants precise, visual energy-saving reports he can trust, with zero effort
Design implication: sell “saving green” as much as “being green”; show progress visually; respect his time.
A crucial subtlety, especially in B2B and complex markets: the person who uses your product, the person who pays for it, and the person who decides are often not the same. In healthcare, a new drug has patients (users), physicians (deciders/prescribers), hospitals and pharmacies (buyers/channel), and insurers and regulators (who control reimbursement and approval). Sell to the wrong one and nothing moves. So map the value chain and ask, for your opportunity: who is the user, who is the buyer, and who is the decision-maker?
4 · Customer research methods
Section titled “4 · Customer research methods”Now the real work: replacing assumptions with evidence. Two foundational distinctions organise all of it.
Secondary vs primary. Secondary (desk) research reuses data that already exists - market reports, official statistics, competitor sites, trade journals, forums. It’s cheap and fast, so you almost always start here. Primary (field) research collects fresh, first-hand data for your specific question - because not everything you need is sitting in a web page or a tweet.
- Existing data: market studies, government and industry statistics, competitor websites, journals, forums, Google Trends
- Cheap, quick, broad - do it first to frame the market
- Watch-out: don’t behave like a keyword-typing algorithm; be creative, follow different paths
- New, first-hand data collected for your specific question
- Interviews, observation, surveys, experiments
- The only way to reach needs, fears and reasons that were never written down anywhere
Within primary research, the deeper split is between depth and measurement.
- Interviews, observation/ethnography, focus groups
- Answers why: reasons, feelings, needs, the buying and usage process
- Best early, when you don’t yet know the right questions
- Output: customer profile of pains, gains and jobs-to-be-done, backed by quotes
- Surveys, experiments, analysis of secondary data
- Answers how many: frequencies, averages, correlations
- Best later, to size and confirm a hypothesis on a representative sample
- Output: market size, segment shares, measured behaviour
Here’s how the main methods compare in practice:
| Method | Good for | Watch-outs |
|---|---|---|
| Secondary data | Market size, structure, trends; cheap first pass | Ages fast; not tailored to your question; may not exist for a new market |
| Interviews (qualitative) | Reasons, feelings, complex buying/usage processes; discovering unknown needs | Needs access and interviewer skill; small, non-representative sample; time-consuming |
| Observation / ethnography | Watching what people actually do, not what they say | Slow; you see behaviour but not always the “why” behind it |
| Surveys (quantitative) | Measuring known, not-too-complex issues on a representative sample | Only as good as the questions; low response quality; self-reported; can’t discover the unknown |
| Experiments | Testing cause and effect; validating willingness to pay | Setup effort; artificial settings can mislead |
Doing customer interviews well
Section titled “Doing customer interviews well”Interviews are where beginners waste the most opportunity, because it feels like selling and the instinct is to talk. Flip every instinct:
| Don’t | Do instead |
|---|---|
| Talk most of the time | Listen most of the time |
| Pitch and defend your idea | Focus on their pains and gains; be ready to hear what kills your idea |
| Ask “what would you do if…?” or “what do you plan to change?” | Ask about actual past behaviour: what they do, what they’ve already tried |
| Ask leading questions (“Wouldn’t you agree that…?”) | Ask neutral, open-ended questions; ask “why” |
| Run through 20 fixed questions identically each time | Build on about 5 core questions and adapt as you go |
| Hear what you want to hear; interpret on the spot | Take notes on what they actually said |
Two traps deserve their own warning. The first is confirmation bias - going in wanting the idea to be right, so you hear agreement everywhere and quietly discount objections. The cure is to try to invalidate your idea, not confirm it. The second is the gap between what people say and what they do: stated intentions (“yes, I’d definitely buy that”) are notoriously unreliable, which is exactly why you ask about real past behaviour and, where you can, observe instead of just asking.
5 · The mindset: get out of the building
Section titled “5 · The mindset: get out of the building”All the tools above share one attitude, and it is the real lesson of the chapter. Market and customer research is straining and awkward - which is precisely why founders skip it and stay at their desks polishing the product. Don’t. Market research is the systematic, objective collection and interpretation of data to reduce the risk in your decisions, and most of that data lives with real people, not in your assumptions.
So: start desk-side with secondary data to frame the market and rough out your TAM/SAM/SOM; pick a narrow beachhead segment and sketch a persona as a hypothesis; then go out, interview and observe real target customers to test it - and be genuinely willing to change your idea when the evidence says so. That loop, run early and cheaply, is what separates the ventures that find product-market fit from the ninety percent that don’t.
Revision summary
Section titled “Revision summary”Next: Entrepreneurial Strategy: The Four Choices → - the hard choices every young venture must make.