ISSUE 007

Where First Customers Actually Come From

I set out to find evidence on how new businesses get their first customers, expecting it to be a well-studied question. It is not. Almost everything that came back was written by somebody who sells marketing services, usually citing a survey whose sampling frame is never published. What survived the filter is two papers about a bank in Germany and a free federal file that counts the businesses in your county. That is a thinner answer than I wanted, so this entry is partly about the thinness.

An idea worth thinking about

A referred customer stays as long as the person who referred them stays

Four researchers got access to a German retail bank's referral programme and analysed 1,799 pairs of referrer and referred customer, acquired between January and October 2006 and tracked through 2008, alongside 3,663 customers the bank acquired by other means. They were testing two competing explanations for why referred customers are known to be more valuable: better matching, meaning the referrer sends people who genuinely fit, or social enrichment, meaning the relationship between the two people is itself part of what holds the new customer in place.

The result is the sort of finding that changes what you would actually do. Referred customers whose referrer was still with the bank had a churn hazard roughly 40 percent lower than nonreferred customers. Once the referrer had left, the same referred customers had a churn hazard roughly 280 percent higher than nonreferred customers. These are hazard ratios rather than probabilities — a ratio on a small base is still a small absolute number — but the direction is unmistakable. The loyalty is not a property of the referred customer. It is a property of the pair.

A second result from the same data is quietly practical. Referrals tended to have higher margins when the referrer was themselves a higher-margin customer, was older, and had been with the bank for more than a few months. No referrer characteristic predicted how fast the referral would churn. The authors' recommendation to the bank is to invite referrers from among higher-margin customers who have been around at least six months, rather than asking everybody.

Now the limits, which are large. One bank, one country, one year's cohort, twenty years ago, in a product category the authors describe as high-involvement and hard for customers to evaluate. Whether any of this transfers to a heating company in Cape Girardeau is an open question that the authors do not claim to answer. What I think does transfer is the shape of the idea: if your business runs on referrals, the thing you are protecting is a relationship between two people, and losing the first one puts the second at risk in a way nothing in your books will show you.

Read the 2018 paper

A tool I disappeared into

Every business in your county, counted, by size and industry

County Business Patterns is an annual count of establishments by county and industry, built from administrative records rather than a survey. The complete county files download as flat text without an account or an API key, and the table tool will do the same job if you would rather not open a 100 megabyte file.

I pulled the 2023 file for Cape Girardeau County. There are 2,334 establishments. Of those, 1,068 have fewer than five employees, 464 have five to nine, and 386 have ten to nineteen. That is 1,918 establishments under twenty people, about 82 percent of everything in the county — my addition and division, not a published figure. By sector: 360 in retail, 315 in health care and social assistance, 247 in other services, 228 in accommodation and food, 199 in construction, 181 in professional and technical services, 85 in manufacturing.

If you sell to other businesses, that is not a market estimate. That is a count of the doors. Three hundred and fifteen health care establishments is a number you can hold in your head, and it changes what a sales plan looks like — four hundred cold emails is not a strategy when the entire addressable set is three hundred and fifteen and most of them have four people in them.

Four limits, all real. The data runs a year or two behind; the 2023 file was published in 2025. Small cells are suppressed where a single employer would be identifiable, which bites hardest in exactly the rural counties you most want to look at. It counts establishments rather than decision-makers, so a chain's three locations are three rows and one buyer. And it excludes most farms, most of the self-employed without payroll, and some government, which in a lot of Missouri counties is a meaningful share of the economy.

Open County Business Patterns

Learn something

Four people decide whether you get the job, and only one of them is the customer

MIT publishes the full slide deck for 15.390 New Enterprises free under a Creative Commons licence, no registration. Lecture twelve is the one on acquisition, covering three steps: define the decision making unit, map the decision making process, and map the sales process.

The decision making unit is the part I would hand to anyone who sells to other businesses. The exercise is to write down, for a single target customer, every person involved when your product gets bought, and label what sort of power each one holds: the person with the problem, the person who owns the budget, the influencer whose recommendation carries weight, and the person who can veto without ever having to justify it. The worked examples put finance and purchasing in the veto seat and an engineering firm in the prescriber seat, with the nominal customer in the middle holding the problem and the budget but not the final word.

The decision process map is the same exercise against a calendar: lead generation one to two months, access to influencers two to four, design phase six to twelve, the actual sale twelve to fifteen. Those are the numbers from an industrial example and they are not your numbers — a residential plumbing job is a phone call. The value is in being forced to write down a realistic range for each step rather than assuming the whole thing is one decision made by one person on one afternoon.

Two honest caveats. It is from 2013 and framed for MBA teams building venture-scale companies, so the vocabulary is heavier than the ideas require. And because the textbook illustrations were removed for copyright, several slides are blank frames with a note where a diagram used to be. You are reading a good outline, not a complete deck.

Open the lecture notes

What we’re seeing

Eighty-two percent against seventy-nine point two. That is what 'referrals are more loyal' looks like measured.

The 2011 paper behind the one in the first slot tracked 5,181 customers the same German bank acquired through its referral programme in 2006 and a random sample of 4,633 it acquired by other means, following all of them for 33 months. Its headline findings are genuinely positive for referrals. After controlling for demographics and month of acquisition, referred customers were about 18 percent less likely to defect at any given moment. Their value to the bank over a six-year horizon was about 40 euros higher on a base of 253, which is 16 percent, rising to about 25 percent once you count the roughly 20 euros less it cost to acquire them. Against a 25 euro reward paid to the referrer, the authors put the return at about 60 percent over six years.

And here is the same finding from the other end. The probability of still being an active customer after 33 months was 82.0 percent for referred customers and 79.2 percent for nonreferred ones. Two point eight percentage points — that subtraction is mine. An 18 percent reduction in a hazard that is already small produces a difference you would struggle to see in a business with eighty customers, and would certainly never notice without writing it down. Both numbers are true and describe the same data. If you only ever see the first one quoted, now you know why.

Two more things the paper found that the summaries drop. The margin advantage of referred customers eroded over time while the loyalty advantage did not, so the two halves of the benefit behave differently. And the value differential showed up among high-margin customers and not among low-margin ones, and the programme was less beneficial when used to acquire older customers. The authors' conclusion is explicitly that referral programmes should be selective rather than universal.

Now the part I owe you. This is the best-identified evidence I could find on how customers arrive, and it is about a bank's formal referral scheme, not about how a new business gets its first customers. Those are different questions. I looked for administrative data or a survey with a published sampling frame on first-customer acquisition for small firms and did not find one. What is abundant is statistics of the form '85 percent of small businesses get customers through word of mouth', which circulate without a method, a sample size, or a definition of what counts as word of mouth, and which are published almost exclusively by companies that sell marketing services. I am not going to repeat one here as though it were a finding.

I want to be careful not to turn an absence of evidence into a tidy conclusion. It is entirely possible that referrals dominate small-business customer acquisition. It is also possible that owners report referrals because a referral is the only acquisition event that arrives with a name attached, while the advert that made the referrer's friend remember you does not. Nobody has measured it in a way I can check, and the people best placed to fund that research are the people selling the alternative.

Which leaves one unglamorous instruction that costs nothing. Ask every new customer who sent them, record the answer in the same place every time, and after a year you will have something nobody else has: real data about your own business, with a denominator. If a name keeps appearing, the 2018 paper says that relationship is load-bearing, and the thing to do is not to automate a referral programme but to keep that person.

Schmitt, Skiera and Van den Bulte, Referral Programs and Customer Value, Journal of Marketing, 2011

One question

Where did your last three customers actually come from?

Not where you think most of them come from. The last three, specifically. Reply with the three answers.

More in this pillar as it's written.

— Shana

Sources link to the original publisher, never to a summary.