In-store analytics for supermarkets: every trip, matched to the receipt
A door counter tells you how many came in. A supermarket needs to know what happened between the entrance and the till. Shoppermotion follows every trolley and basket and, with the Insights plan, matches the trip to its receipt, so you see conversion per bay, the main-aisle effect and what in-store media really sold.
In-store analytics for supermarkets measures what happens between the entrance and the till. Shoppermotion follows every trolley and basket with Bluetooth tags and ceiling antennas, with no cameras and no personal data, and with the Insights plan matches each trip to its own receipt. You see which aisles shoppers reach, which bays convert and what in-store media sold.
What in-store analytics should answer in a supermarket
A receipt tells you what was bought. It can't tell you how the shopper got there. These are the questions a grocery team should be able to answer every week:
Which aisles shoppers actually reach from the main aisle, and which ones they skip.
Which bays turn passers-by into buyers, and which ones only get looked at (shelf conversion).
Whether the main aisle and end caps earn the space they take.
Whether a promotion, a flyer page or a new display changed what shoppers did.
People counters do one job well. They count entries and exits, and divided into the number of tickets they give a store-level conversion rate. If you only need footfall, a counter is the right tool.
What a counter can't see is the store itself: the route from the door to the till, the zones crossed, the bays where shoppers slowed down and the displays they walked past. Answering those questions needs the full path of every trip, not a count at the entrance. Compare Shoppermotion vs people counters and Shoppermotion vs ShopperTrak.
In-store analytics approaches, side by side
Each technology sees a different part of the trip. This is what each approach typically measures in a supermarket.
Criterion
Door / people counters
Cameras / computer vision
Wi-Fi / phone tracking
Trolley & basket tags + receipt (Shoppermotion)
What's measured
Entries and exits, occupancy
People in camera view: counts, paths, dwell
Phones with Wi-Fi or Bluetooth switched on
Full path of every tagged trolley and basket, entrance to till
Link to sales
Store conversion (counts vs tickets)
Usually combined with sales totals
Usually none
Each trip matched to its own receipt (Insights plan)
Shelf / bay level
No
Where cameras cover
Low precision
Visual contact and engagement per bay; conversion per bay with the Insights plan
In-store media proof
No
Exposure at best
No
Impressions, views and visits per placement; sales lift with the Insights plan
Personal data
None
Images processed
Device identifiers
No cameras, no personal data
Typical fit
Footfall, staffing, malls
Fashion and specialty chains
Malls, venues
Supermarkets, hypermarkets, CPG brands, Retail Media Networks
If you only need footfall, a counter is the right tool.
Last reviewed: October 2026. Columns describe typical setups for each approach; individual products vary. Vendor details, with sources from each vendor's public pages, are on our comparison pages: ShopperTrak · RetailNext · Xovis · V-Count · Trax · cameras · Wi-Fi and Bluetooth tracking.
Small Bluetooth (BLE) tags on trolleys and baskets are located by Angle of Arrival antennas on the ceiling with sub-metre precision. Passive and anonymous: no app, no cameras, no personal data.
02
Match the receipt
With the Insights plan, each anonymous trip is matched to its own POS ticket at the till, so every stop in the path has an outcome. See how ticket matching works.
03
Decide
Read it in Shoppermotion AI dashboards and reports, or take the data to your own stack through the REST API and data exports, with Power BI and Tableau integrations.
What you can measure
The same anonymous paths feed every metric, from the whole store down to a single bay.
Shelf funnel
Traffic, visual contact (below 45 cm/s), engagement (below 25 cm/s) and, with the Insights plan, buyers from the matched ticket, for every bay. Shelf conversion.
Missed opportunities
Engaged trips that left the bay without buying, and Category Pulse in Shoppermotion AI to spot the shelves that attract but don't convert.
Heatmaps and dwell
Where shoppers go and how long they stay in each zone, by hour and day. Heatmap · Dwell time.
Shopping missions
Stock-up, fill-in, urgent and fresh missions, inferred from paths and tickets rather than surveys. Shopping mission.
Layout A/B tests
Test store vs control store over the same weeks, with statistical confidence on every result. Perfect Store.
Category benchmarks
Missions, behaviour shifts and category performance compared across similar stores. Shopper Insights.
In-store retail media you can prove
Screens, end caps, pallets and flyers get the metrics digital media already has: verified impressions, views, visits to the promoted category and sales lift per in-store placement.
Best in-store analytics tools: how the main approaches compare
There is no single best tool: each approach answers a different question. These are the vendors most often named for in-store analytics, grouped by approach, in no particular order.
Sensors at entrances, and in some products in zones, that count visitors and occupancy. Combined with transactions, they give store conversion. Compare ShopperTrak, V-Count, Xovis and people counters.
Computer vision
RetailNext (Aurora sensor); on existing CCTV: Flame Analytics, Glimpse
Ceiling sensors or existing security cameras analysed with AI to count people and measure paths and dwell where cameras see. Compare RetailNext and cameras.
Wi-Fi, phone signal and hybrid
Ariadne
Sensors that pick up phone signals to estimate flow across zones, combined in Ariadne's case with depth sensors at entrances. Compare Wi-Fi and Bluetooth tracking.
Shelf execution (image recognition)
Trax
Image recognition of shelves for availability and planogram compliance. Compare Trax.
Retail media measurement on POS data
Circana, QSIC, Footprints AI
Measure in-store campaigns against point-of-sale data. See how Shoppermotion approaches offline attribution.
Trolley and basket paths matched to receipts
Shoppermotion
BLE tags on trolleys and baskets located by ceiling antennas, with each path matched to its receipt on the Insights plan. Built for supermarkets, hypermarkets, CPG brands and Retail Media Networks.
How to choose
If you need footfall and store conversion, a people counter answers it.
If you need conversion per bay and proof of in-store media in grocery, you need full paths matched to receipts.
Shoppermotion tracks shopping tools, not people. Every trip is anonymous by design, and the hardware fits into a working store. More on security and privacy.
No cameras, no app, no personal data
GDPR compliant by design
Deployed in hours, no works in store
Start with a pilot store, then roll out
Trusted by retailers and brands in more than 30 countries
Pricing and ROI
Every project is quoted from five factors: store format and size, number of stores, trolleys, baskets or both, ticket matching and service level.
The Data tier gives your BI team anonymous paths and metrics through the REST API and data exports. Insights adds Shoppermotion AI dashboards, matching with POS receipts and integrations with Power BI or Tableau. See how pricing works or estimate your ROI.
FAQ
Questions, answered.
What is in-store analytics?
In-store analytics is the measurement of how shoppers move, stop and buy inside a physical store. It shows which zones and aisles they reach, where they slow down in front of a bay and whether the visit ended in a purchase. Our glossary has the full in-store analytics definition.
What are the best in-store analytics tools for supermarkets?
It depends on the question. People counters measure footfall and store conversion. Computer vision covers the zones its cameras see. Trolley and basket tags matched to receipts, the Shoppermotion approach, measure conversion per bay and in-store media across the whole store. Most supermarkets need the last one for category and media decisions.
How is in-store analytics different from people counting?
People counting measures how many visitors cross the entrance. In-store analytics measures what happens between the entrance and the till: the path, the zones visited, dwell time, contact with each bay and, with ticket matching, what was bought. A counter gives you footfall; full paths explain it.
Can in-store analytics link shopper behaviour to sales?
Yes, when each trip is matched to its receipt. With the Shoppermotion Insights plan, every anonymous trolley or basket path is matched to its own POS ticket, so each stop has an outcome: shelf conversion, missed opportunities and sales lift per placement. Counter-based tools compare total traffic with total sales instead.
Does in-store analytics need cameras?
No. Shoppermotion uses Bluetooth tags on trolleys and baskets, located by Angle of Arrival antennas on the ceiling with sub-metre precision. Shoppers install no app, there are no cameras and no personal data: the system tracks shopping tools, not people, and it is GDPR compliant by design.
How do supermarkets measure in-store retail media?
By measuring each placement the way digital media is measured: verified impressions, views, visits to the promoted category and sales lift per screen, end cap or display. Exposure is taken from the real path and linked to the matched receipt. See offline attribution and Retail Media.
How long does deployment take?
Deployed in hours, no works in store. A project usually starts with a pilot store: antennas go on the ceiling, tags go on trolleys and baskets, and the hardware does not interfere with existing electrical or network installations. After the pilot, the rollout extends to more stores and formats.
How much does in-store analytics cost?
Shoppermotion has no public price list. Each project is quoted from five factors: store format and size, number of stores, trolleys, baskets or both, ticket matching and service level. The ROI calculator estimates the value for your stores, and the pricing page explains how a quote is built.
Can I see foot traffic, conversion and basket data in one dashboard?
Yes. Shoppermotion AI dashboards show traffic, paths and conversion per store, category and bay in one place, with ticket data on the Insights plan. The same data is available through the REST API and data exports, and integrates with Power BI and Tableau if your team prefers its own BI tools.
See every trip to the till in your own store.
Book a 30-minute demo with a retail analyst and see real trips, tickets and conversion in Shoppermotion AI.
