What is customer profiling and segmentation?
Customer profiling is the data you keep on each outlet. Customer segmentation is how you group those outlets into classes you treat differently. For a brand that sells through sari-sari stores, groceries, drugstores and wholesalers, the profile says where the store is, what it stocks and what it buys from you. The segments are classes such as A, B and C.
The two work as a pair. Profiling is the data, and segmentation is the grouping built from it:
| Aspect | Customer profiling | Customer segmentation |
|---|---|---|
| What it is | The store-level data kept on each outlet | The classes built from that data |
| Typical content | Location, store size, product range, competitor presence, shelf share | Class A, B and C outlets, or outlet types tied to your sales goals |
| Who handles it | Field reps and promodisers capture it during visits | Sales and trade marketing leads use it to set visit frequency, rep assignment, campaigns and trade schemes |
| Question it answers | What is this store really like? | How should we cover and treat this store? |
Done well, the two tell your team which stores deserve the most visits, which schemes to run where and how to split a territory target. Done on gut feel, they send your best reps and your van to stores that stopped growing.
Why classing stores by gut feel goes wrong
Many teams still class outlets on what a rep or area manager sees: how big the store looks and how often it orders. That misses two things.
A rep walks into the biggest sari-sari on the street and marks it Class A. But the store gives only 10% of its space to your category. It may be a top store for other brands. For you, it is a small one.
Now take a store that sells a lot of your product today. Its shelf is full and the suki owner will not add lines, so there is no room to grow. A smaller store two streets away sells less today, yet it could sell twice as much with a visit every week and a better range. Gut feel pours effort into the first store and ignores the second, and an Excel tracker updated by hand never shows the difference.
Profiling adds the missing half: what a store could buy from you, as well as what it buys now.
The four types of customer segmentation, for outlets
The four classic types are geographic, demographic, behavioral and psychographic. The same four are often called the four types of customer profiling, since a full profile holds data of each kind. They were built for shoppers, but each has a direct version for stores.
| Type | For shoppers | For outlets | What a rep records |
|---|---|---|---|
| Geographic | Country, city, climate | Island group, city, barangay, route and catchment | GPS location; nearby schools, offices, public market or jeepney terminal |
| Demographic (for stores: firmographic) | Age, income, family size | Store type, size, staffing and ownership | Format such as sari-sari, mini grocery, drugstore, convenience store or wholesaler; selling space; staff who handle your category |
| Behavioral | What people buy and how often | What the outlet orders, how often and how fast it grows | Order history, lines bought, response to past schemes, payment record including utang |
| Psychographic (for stores: owner needs and potential) | Lifestyle, values, attitudes | How much the store could sell and what the owner wants | Category sales across all brands, your share of shelf, openness to new lines, need for credit or display |
For stores, behavioral data often follows RFM: recency (when the store last ordered), frequency (how often it orders) and monetary value (how much it spends with you). It comes from your own order records, so reps need no extra data collection on the visit.
The last row is where potential lives. A store's potential is what it could buy from you if you won a fair share of its category. You estimate it from category sales, shelf space and owner attitude.
Most brands get the best segments by mixing the types. Geography and store type tell you which outlets to cover. Behavior and potential tell you how hard to work each one. For how store formats differ, see general trade vs modern trade.
How to profile and segment outlets in six steps
- Decide what the classes will drive. Write down the decisions each class changes: visit frequency, which rep or van covers the store, schemes, range and targets. If a class changes none of these, you do not need it.
- Choose the data to capture. Pick the fields from the table above that predict sales in your category, and add order history from your own records or your distributors. Keep the form short enough to fill in during a normal visit. A short form every rep completes beats a long one nobody finishes.
- Score current sales and potential separately. Current sales come from order data. For potential, rate each factor (catchment, category sales, space and owner attitude) with one point for low, two for medium and three for high, then add them up. With four factors, every store scores between 4 and 12. Keeping the two scores apart stops a busy store with no headroom from looking like a growth store.
- Set the class lines from rep capacity. Stores with high sales today are Class A, whatever their headroom, because that volume needs protecting. Stores with high potential that sell little or a middling amount today are growth stores, Class B, and so are steady mid-range stores. They get more effort than their sales suggest. Stores that are low on one score and no better than middling on the other are Class C. Then check the workload: if your reps cannot visit every Class A store as often as planned, narrow Class A from the top third to the top quarter until they can.
To place each store, put the two scores side by side. Rank current sales against similar stores in the same territory: the top third is high and the bottom third is low. Call potential high at 10 to 12 points, medium at 7 to 9 and low at 6 or less. The grid below then gives the class.
| Potential score | Low sales today | Medium sales today | High sales today |
|---|---|---|---|
| High (10 to 12) | Class B: growth store | Class B: growth store | Class A |
| Medium (7 to 9) | Class C | Class B | Class A |
| Low (6 or less) | Class C | Class C | Class A: protect and hold share |
- Give the classification an owner. Reps collect the data, but they should not set the class, since a higher class often brings more support for their own stores. A sales operations or trade marketing analyst runs the scoring, and area managers review any store that moves.
- Test, then reclassify on a fixed rhythm. Try the classes in one territory for a quarter and compare productive visits and sales with a territory that kept the old classes. Once you roll out, rescore every quarter, and sooner after a store renovation, a new competitor next door or a change of owner.
Example: one sari-sari scored and placed
Take a large sari-sari with a small grocery counter on a busy road near a school and a tricycle terminal. Today it buys little from you: a few fast-moving lines, ordered once a month through your distributor. On size and past orders alone, it would sit in Class C.
Its profile says otherwise:
- Catchment: high. Steady footfall from parents, students and commuters.
- Category sales: high. It sells a wide range in your category, mostly other brands.
- Space: medium. The owner could free a shelf if your range sold.
- Owner attitude: high. The owner runs the counter and asked the rep about a new pack.
That adds up to 11 out of 12 points. Low current sales and high potential make it a growth store, so it goes into Class B. It now gets a visit every two weeks instead of once a month, an entry scheme on two core lines and a target set from its potential. Once its sales reach the top third of similar stores in its territory, it moves up to Class A.
How each class changes visits, schemes, range and targets
Here is a common starting point for each class. Adjust it to your category and your rep and van capacity.
| Action | Class A: high sales today | Class B: growth stores | Class C: low sales, limited potential |
|---|---|---|---|
| Visits | Weekly, by a senior rep | Every one or two weeks, with time to sell in new lines | Monthly, or orders by phone, Viber or app |
| Schemes | Display and loyalty schemes that protect your space | Entry and trial schemes on new lines | Simple volume offers through the distributor |
| Range | Full range; new launches go here first | Core lines plus the next best-fit lines | Fast movers only |
| Targets | Hold share and widen the range | Set from potential | Keep steady at a low cost to serve |
Visits. Rep time is the resource you have least of, and traffic already eats into every selling day. Feed the class straight into the beat plan. Class C stores often do fine with a call, a Viber order or an app order between visits, so a rep stops crossing town for a store that barely moves volume.
Schemes. Segmentation puts trade promotion spend into stores that can turn a discount into extra sell-out. A store that would sell the same amount anyway gets a simpler offer. In a suki-and-listahan market, credit terms deserve the same treatment: looser terms for a growth store with a good payment record, tighter ones where utang keeps piling up.
New launches. Send a new product first to stores whose profile fits it: the right price band, the right shoppers and room on the shelf. A launch placed this way gets a fairer test than one pushed to every outlet at once. Your distributor's van team also knows exactly which stops to load for.
Targets. Split the territory target by class. A Class A store near its ceiling cannot grow as fast as a growth store, so each class needs its own growth goal, not one flat number for every stop.
How outlet classes differ by industry
The method stays the same across industries, but the data that predicts sales changes.
- FMCG and food: many small outlets that order often. Footfall, shelf and cooler space, and order frequency drive the class, and visit frequency is the main lever.
- Pharma: drugstores, chain pharmacies and doctors are profiled separately. For a drugstore, the prescriptions written nearby and whether it stocks your molecule decide the class. Nurturemed Pharma raised PMR productivity by 20% on BeatRoute. Read the Nurturemed case study.
- Paints and building materials: fewer, larger dealers and hardware stores. Credit terms, counter staff influence and project business decide the class, and visits are longer and less frequent. A leading paints brand in the Philippines improved sales productivity by 30%. See the leading paints brand case study.
- Lubricants and auto parts: workshops and parts retailers sit in one network. A mechanic's advice can matter as much as the shelf, so profile the workshops too.
Customer profile vs persona vs ideal customer profile
These three terms get mixed up, but they do different jobs.
- Customer profile: the facts about one real customer, such as this drugstore on this street. It changes as the store changes.
- Customer persona: a made-up character that stands for a group, such as “the owner-run sari-sari that buys on credit”. Personas help you write schemes and sales pitches.
- Ideal customer profile (ICP): a description of the kind of customer most worth winning. For a brand, it is the outlet type and size you most want to add to your coverage.
Profiles feed your segments, each segment can be summed up as a persona, and the ICP tells reps which new stores to go after.
Common mistakes in outlet segmentation
- Classing on size alone. A big store with little space for your category is not a big customer.
- Classing once and never again. Stores change owners, renovate and lose footfall. A class set years ago steers today's visits with old facts.
- Too many classes. If two classes get the same visits, schemes and range, merge them.
- Letting reps set the class. Reps know their stores best, but they also gain from a higher class. Use their data and let the analyst set the class.
- Duplicate stores. One sari-sari entered twice as “Aling Nena Store” and “A. Nena Sto.” splits its order history, so neither record looks like a big customer. This happens often when several distributors encode the same store.
- Profiles nobody finishes. Build the profile into the visit form and track how complete each rep's profiles are.
Where BeatRoute fits
BeatRoute is a sales force automation and distribution platform for consumer brands. It runs across modern trade, chain pharmacies, van sales and sari-sari coverage on one platform. For profiling and segmentation, it handles the capture and the follow-through:
- Reps build store profiles in the BeatRoute SFA app during visits, with store type and subtype, photos and custom fields. A profile built by a rep in Cebu feeds the same national database as one built in Davao.
- The app works on any Android, including low-end phones, and works offline. A rep in a provincial dead zone or on a route after a typhoon still saves the profile. It syncs when the phone gets a signal.
- New stores are geotagged when they are onboarded, and likely duplicates are flagged, so one shop has one record.
- Orders from the distributor management system add secondary sales to each store's history.
- The Scheduling AI Agent plans each rep's visits around store priority, so Class A and growth stores are covered first.
If you cover a few hundred stores with a handful of reps, a spreadsheet and a clear scoring rule will do the job. A platform earns its place when thousands of outlets across Luzon, Visayas and Mindanao, many reps and several distributors make the data hard to keep clean and current.
To see store profiles and classes driving visit plans, request a demo.
Frequently asked questions
Is customer segmentation the same as market segmentation?
Not quite. Market segmentation splits a whole market, including people or stores that do not buy from you yet. Customer segmentation groups the customers you already serve. Outlet classing often does both: it ranks the stores you sell to and flags uncovered sari-sari stores and groceries worth adding.
How many outlet classes should a brand use?
Three or four suits most brands. Each class needs its own visit plan, schemes and range. With more classes than that, reps struggle to remember the rules and the classes end up treated the same.
Can you profile outlets that do not buy from you yet?
Yes. A market census or retail audit records every outlet on a route, with its type, size and the brands it stocks. Those profiles show where your coverage gaps are and which new stores deserve a visit.
Where does order data come from when stores buy through distributors?
From the distributors. Secondary sales, the orders a distributor ships to each outlet, give you the order history your reps cannot see. It only works if each distributor invoice carries the same outlet ID as your rep app.
Does outlet profiling raise data privacy questions?
Mostly it is business data, such as store size and order history. Owner names and phone numbers are personal data, so collect only what reps need and follow the Philippine Data Privacy Act and National Privacy Commission rules.
