Problems › We Do Not Know Who Our Best Customers Are › Retail
Best does not mean the stores with highest sales. It means the customer segments whose purchases produce four-wall margin after occupancy cost and can be reached at traffic density that covers the lease. For retailers, this shows up in a particular place. The numbers that carry the answer are four-wall margin and sales per square foot, and the complication specific to this industry is that 22 leases expire within 24 months and nobody can say which stores are actually profitable. The general version of this problem and the one you are actually in have different first moves.
Best does not mean the stores with highest sales. It means the customer segments whose purchases produce four-wall margin after occupancy cost and can be reached at traffic density that covers the lease. For retailers, this shows up in a particular place. The numbers that carry the answer are four-wall margin and sales per square foot, and the complication specific to this industry is that 22 leases expire within 24 months and nobody can say which stores are actually profitable. The general version of this problem and the one you are actually in have different first moves.
Most retailers can name their highest revenue stores and very few can name their best customer segments, because best requires combining four-wall margin, sales per square foot and occupancy cost ratio that usually sit in separate systems.
The results are consistently surprising. The highest revenue stores are frequently mid-ranked once occupancy cost is included; the best segment is often one nobody targeted deliberately, discovered by accident and never systematised across the remaining leases.
This matters because it decides everything downstream. Which customer groups to promote to, what to stock next, where to price, what to say in local marketing. Getting it wrong means optimising the entire portfolio for the wrong customer as the 22 leases come up for decision.
These three together are the signature. One on its own usually points somewhere else.
✓ Revenue by store is reported weekly but four-wall margin is not calculated before lease decisions
✓ Occupancy cost ratio is tracked at the portfolio level but not broken out by the customer segments driving each store
✓ The target customer profile was written from the owner’s view of top-line stores rather than from segments that actually clear occupancy cost
The move that usually makes it worse. Defining the ideal customer from the highest revenue stores, which selects for the locations with the most negotiating power over lease terms rather than the segments that deliver four-wall margin.
It is for you if you run or finance a retailer 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 retailer. 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 Marlin & Crowe, a sample company profile used for testing rather than a customer — $95M revenue, 40 stores.
Excerpt from a real Percision run · Customer Value Architecture · sample company profile
The move. Lock in the 8 stores that deliver 14.1% four-wall margin before 22 leases expire.
The leak it closes. Prevents $1.9M annual EBITDA leakage from lease non-renewal
The assumption it rests on. Landlords accept ≤3% rent escalation on all 8 leases — the engine put the probability at 0.75.
| Investment required | $160K total ($40K legal + $120K store refreshes) |
| Expected return | 11.9× on $160K investment via $1.9M EBITDA protection |
| Revenue, year 1 | $13.5M protected store revenue |
| Revenue, year 2 | $13.9M (3% rent absorption) |
| Revenue, year 3 | $14.3M (volume growth from personalization) |
| Exit criteria | If fewer than 6 leases renewed by Month 6, pivot to sub-10k sq ft pop-up format in high-traffic street locations. |
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 retailers it works through four-wall margin, sales per square foot, occupancy cost ratio and traffic density, 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. 22 leases expire within 24 months and nobody can say which stores are actually profitable — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are four-wall margin, sales per square foot, occupancy cost ratio, 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 four-wall margin and sales per square foot. 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.
Describe the situation in your own words and we will tell you which analysis answers it — before you sign up for anything.
Describe my situation →Prefer to skip ahead? Go straight to the free diagnostic.
English · Español · Deutsch · Português · Français · Italiano · Nederlands · 日本語 · 한국어 · 中文 · Polski · Svenska · Türkçe · العربية · Tiếng Việt · ไทย · हिन्दी · עברית