Problems › We Do Not Know Who Our Best Customers Are › Fintech
Best does not mean largest. It means the ones you can acquire repeatably, serve profitably and keep. This page works through it for fintech companies specifically — including an unedited excerpt from a real analysis of a fintech.
Best does not mean largest. It means the ones you can acquire repeatably, serve profitably and keep. For fintech companies, this shows up in a particular place. The numbers that carry the answer are blended take rate and charge-off rate, and the complication specific to this industry is that lending fixed the P&L and converts revenue worth a 7x multiple into revenue worth a 2x multiple. The general version of this problem and the one you are actually in have different first moves.
Most businesses can name their biggest customers and very few can name their best, because best requires combining three things that usually live in different systems: what they contribute, what they cost to acquire, and how long they stay.
The results are consistently surprising. The largest accounts are frequently mid-ranked once cost to serve is included; the best segment is often one nobody targeted deliberately, discovered by accident and never systematised.
This matters because it decides everything downstream. Who to target, what to build next, where to price, what to say. Getting it wrong means optimising the entire business for the wrong customer.
These three together are the signature. One on its own usually points somewhere else.
✓ Best customer means largest by revenue in internal conversation
✓ Cost to acquire is not known by segment
✓ The ideal customer profile was written from intuition rather than from the base
The move that usually makes it worse. Defining the ideal customer from the largest accounts, which selects for the ones with the most negotiating power rather than the best economics.
It is for you if you run or finance a fintech and best customer means largest by revenue in internal conversation. It is the situation where the numbers are available but nobody has put them in an order that produces a decision.
It is not for you if Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.
Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.
Below is an excerpt from a real run of this analysis on a fintech. It is a sample profile rather than a customer, and it is unedited engine output — this is the format you get, on your own numbers.
The subject is Verrano Pay, a sample company profile used for testing rather than a customer — $84M net revenue, 28,000 merchants, $9.4B of payment volume.
Excerpt from a real Percision run · Cost Reduction & Efficiency · sample company profile
The move. Convert 18-24 month platform access into 30-36 month structural lock-in via exclusivity contracts and deeper API integration.
The leak it closes. Prevents 180-day exit clause activation that could remove 61% of new merchant flow overnight.
The assumption it rests on. Platform partners will accept 3-year exclusivity in exchange for deeper API features and revenue-share stability — the engine put the probability at 0.75.
| Investment required | $1.8-2.4M over 18 months |
| Expected return | 18-22× on $2.1M midpoint investment |
| Revenue, year 1 | $2-3M incremental from deeper integration (12-month lag) |
| Revenue, year 2 | $12-15M incremental from exclusivity-protected lending origination |
| Revenue, year 3 | $28-30M incremental from two new platform integrations |
| Exit criteria | Terminate if fewer than two platforms sign exclusivity by Month 18 OR if renegotiation windows do not materialize before December 31, 2026. Redirect resources to direct-acquisition diversification (Node 3) and lending covenant remediation. |
This is one move out of a full analysis. Read a complete report — every page, no email required.
This question routes to Customer Value Architecture, one of 29 engagements the platform runs. For fintech companies it works through blended take rate, charge-off rate, contribution margin and CAC by channel, then produces the sequence rather than a list of options — which move first, what it funds, and the observation that would say the sequence is wrong.
You watch the analysis get built before paying anything. Read a complete report here if you would rather see the depth first.
Combine contribution, acquisition cost and retention at the segment level. Any one of the three alone produces a ranking that is confidently wrong.
That is usually good news — it is a targeting instruction. The relevant question is whether the segment is large enough to support your growth plan, which is answerable.
Reprice first; some become profitable and the rest leave with the decision made for you. Firing directly is faster and costs you the information about which were repriceable.
Materially, yes. Lending fixed the P&L and converts revenue worth a 7x multiple into revenue worth a 2x multiple — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are blended take rate, charge-off rate, contribution margin, and an answer built on industry-general benchmarks will usually point at the wrong one first.
Less than most people expect. Your last twelve months of revenue and cost split the way you already split it, plus whatever you hold on blended take rate and charge-off rate. The analysis is explicit about what it is assuming where your data stops, which is more useful than waiting for numbers you may never have.
Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.
Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.
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