A shopper lifts a white t-shirt off a rail; the screen beside it switches to the same t-shirtApparel: the screen beside the product before it is picked up
A shopper lifts a white leather sneaker off a shelf; the screen beside it switches to the same sneakerFootwear: the screen beside the product before it is picked up
A shopper lifts an amber perfume bottle off a tray; the screen beside it switches to the same bottleFragrance: the screen beside the product before it is picked up
A shopper picks up a pink serum bottle at a beauty table; the screen beside it switches to the same serumCosmetics: the screen beside the product before it is picked up
A shopper lifts a green-dial watch from its box; the screen beside it switches to the same watchWatches: the screen beside the product before it is picked up
A shopper lifts an emerald-green handbag off a counter; the screen beside it switches to the same bagBags: the screen beside the product before it is picked up
A shopper lifts beige headphones off their stand; the screen beside them switches to the same headphonesElectronics: the screen beside the product before it is picked up
A shopper takes a bottle of orange juice from a chiller; the screen beside it switches to the same juiceGrocery: the screen beside the product before it is picked up

Physical retail intelligence

The store, aware.

See how shoppers interact with every product. Understand what happens before the sale. Act in real time.

  • MeasureProduct interactions
  • UnderstandShopper behaviour
  • ActInsights · Content · Automation
Today · one storeExample data
  • 342Pickups
  • 28 sAvg. hold
  • 43%Compared
  • 63%Put back
The missing half of your data

Your POS tells you what sold.
What happened before that?

The sale is only the final event. GoTrack reveals the journey before checkout, product by product.

Your POS 109units sold

One number, at the till.

GoTrack
892product interactions
  • 342picked up
  • 147compared
  • 28 saverage hold
  • 217put back
Example data
A signature GoTrack view

The physical
product funnel

Ecommerce has measured product behaviour for decades. GoTrack brings that visibility into the physical store.

  1. A white t-shirt hangs untouched on a rail in a dark boutique
    01On the shelf48products in viewEvery product in view, including the ones nobody touches.
  2. A shopper lifts the white t-shirt off the rail
    02Picked up342pickupsWhich product and colour, from which shelf zone.
  3. The shopper holds the white t-shirt in front of her
    03Held28 son averageHow long it stays in a shopper's hands.
  4. The shopper holds a white and a black t-shirt side by side
    04Compared14743% of pickupsWhich products are weighed against each other.
  5. The shopper hangs the white t-shirt back on the rail
    05Put back21763% of pickups125 not returned · 37%Tried, then returned to the shelf: the put-back rate.
  6. The shopper keeps the white t-shirt and looks up at the screen
    06Purchased*109from your sales data · 32%Joined with your POS or BI data: how many of the products that did not return were sold.

* Purchase is available when combined with sales data.

Example data
How GoTrack works

A camera sees the product.
GoTrack turns it into data.

Cameras placed near the products recognise which product and colour is in a shopper's hand, and record what happens to it. Your existing store becomes a product-interaction layer.

  • No RFID tags
  • No shelf sensors
  • No face recognition
  • Processed in the store
  • No video leaves the store, only data
A ceiling camera above a clothing rail while a shopper lifts a white t-shirt
White essential tee
SKU
TS-WHT-001
Colour
White
Zone
Rail A
Interaction
Picked up
  1. Camera
  2. Product detected
  3. Product & colour matched
  4. Interaction recorded
  5. GoTrack data
Product analytics

Every product
has a story.

See what gets picked up, held, compared and put back, by product, colour, store and hour. Product-level behaviour, not people counting.

See the analytics
White t-shirt

White essential tee

TS-WHT-001
482pickups+18%
31 savg. hold+6 s
22%put-back rate
Black oversized t-shirt

Black oversized tee

TS-BLK-002
731pickups+24%
43 savg. hold+12 s
11%put-back rate
Sage-green linen t-shirt

Green linen tee

TS-GRN-003
216pickups+6%
17 savg. hold-4 s
39%put-back rate
Heather-gray relaxed t-shirt

Gray relaxed tee

TS-GRY-004
394pickups+11%
26 savg. hold+3 s
18%put-back rate
Which age and gender pick up each product Building nowAggregate reports per product, never individual profiles.
Example data
Insight

High interest.
Low conversion.

The green linen shirt is picked up 623 times and considered for 41 seconds on average; your sales data shows only 18 purchases. GoTrack adds the missing behavioural layer to the sales data you already own.

Explore insights
Green linen shirt
Green linen shirt
Combined with your POS or BI data
GoTrack
  • 623pickups
  • 41 sconsideration
Your sales data
  • 18purchases
High interestLow conversion

What to check next

  • Check the price
  • Check size availability
  • Compare its placement in the store
  • Review the campaign
  • Compare it across stores
  • See which products it is compared with
Example data
Multi-store

See what's working.
Everywhere.

Compare the same product across stores, zones and shelves. GoTrack scales from one interaction to your whole network.

  1. Network
  2. Store
  3. Zone
  4. Shelf
  5. Product
  6. Colour
White essential tee · TS-WHT-001
StoreInteractionsAvg. holdPut-back rate
Flagship storeİstanbul68742 s18%
Mall storeAnkara41129 s31%
City storeİzmir89247 s12%
  • City
  • Store
  • Zone
  • Shelf
  • Product
  • Colour
Example data
Real-time activation

Insight doesn't
have to wait.

GoTrack can stop at analytics.

Or it can act the moment a product is picked up. The screen beside it is one option, not a requirement.

What GoTrack can do next

  • Show the product's content on the nearest screen
  • Show two products side by side
  • Play a campaign
  • Send the event to your systems (API, webhook)
See smart screens
A shopper holds a white sneaker while the screen beside the shelf shows the same sneaker
  1. Picked up
  2. Product & colour matched
  3. Event created
  4. Screen shows it
Measured

How fast the screen reacts

0.35 sMedian with one product on the screen
0.51 sMedian when two products share the screen
0.71 sThe slowest of 24 measured fires

Measured on 30 September 2026 in GoTrack's test setup: 25 fires across 8 products; 24 reported their render back (one two-product fire did not). Timed on the store device's clock from the moment GoTrack decided which product was in hand until the screen reported the product content painted, including that report's trip back. The time from lifting a product to that decision is not included here; we will publish it once it is measured. How we measured it

Close the loop

Don't just run experiences.
Measure their effect.

GoTrack can change what a screen shows, then measure whether shoppers picked up and held the product more than in a period without it.

How to run an in-store A/B test
Before content182interactions / hour
After content246interactions / hour
+35% product engagement
Example data
Use cases

One camera system. Many ways to use it.

Screens are optional: the analytics works with cameras alone.

All use cases

Shelf analytics, no screens

Pickups, holds and put-backs from cameras alone.

Learn more

Lift and learn

Pick up a product; its story appears on the screen beside it.

Learn more

Showrooms & trade fairs

Hold a product up to the camera and the screen presents it.

Learn more

Screen content testing

Which content goes with longer holds, per asset and store.

Learn more

Visitor counting

On request: how many came in, anonymously.

Learn more

Store and chain benchmarking

The same reports, compared across every branch.

Learn more
GoBot, the GoTrack robot, in a store
Privacy by design

Understand behaviour.
Not identity.

GoTrack watches the products. Never the people.

  • No face recognitionNo face templates and no biometric matching.
  • No identity profilingNo shopper is recognised from one visit to the next.
  • Processed in the storeImages are analysed on a device in the store, in memory.
  • No video to the cloudOnly product data leaves the store: which product, when, for how long.
  • Works offlineRecognition and screens keep running when the internet drops.
  • No images keptBy default no camera image is written to disk.
Read the privacy approach
Why GoTrack

Designed for real stores, not for a lab.

See how it fits

Its own cameras

Cameras and hardware specified for each project, placed close to the products: we supply them, or you buy them to the spec.

Product- and colour-level

Not “someone touched the rack” — the exact product and colour variant.

Add products yourself

A guided step in the panel — no data-science project, no waiting on a vendor.

Offline-first

Recognition and screens keep running when the internet drops; nothing is lost.

Managed remotely

Every store device reports its health and receives updates without a site visit.

Local team, three languages

Built and supported in İstanbul. Panel and site in Turkish, English and Spanish.

What is GoTrack?

GoTrack is retail vision-analytics software made by GOTONOM in İstanbul. It measures product interaction on the shop floor: which product and colour was picked up, from which shelf zone, how long it was held and whether it went back on the shelf.

Its focus is products: what shoppers do with them. It uses no face recognition, images are processed on a device inside the store, and screens are optional. The full picture: What is GoTrack?

Common questions

What is GoTrack?

GoTrack is retail vision-analytics software made by GOTONOM in İstanbul. Using cameras placed close to the products, it measures product interaction on the shop floor — which product and colour is picked up, how long it is held and whether it is put back — and shows that product's content on the nearest screen.

How quickly does the screen change when a product is picked up?

In our measurement on 30 September 2026, the screen showed the product within 0.71 s of GoTrack deciding which product was in hand, in all 24 measured fires: a median of 0.35 s with one product on screen and 0.51 s with two. The time from the lift itself to that decision is not yet measured separately.

How is GoTrack different from people counters and heatmaps?

People counters count who comes in, heatmaps show where people walk, and shelf recognition checks what is on the shelf. GoTrack measures what shoppers do with the products themselves: which product and colour is picked up, how long it is held, and which are put back or compared. Visitor counting can be added on request.

Does GoTrack use face recognition?

No. There is no face recognition, no face template, no biometric matching, and no shopper is recognised across visits.

Do we need screens to use GoTrack?

No. GoTrack's product analytics works with cameras alone. Screens are optional: add them when you want the shelf to react to the product in hand.

Does GoTrack count people?

On request, yes. GoTrack's standard reports are about products: what shoppers pick up, hold and put back. For stores that also need visitor numbers, GoTrack can count visitors with the same cameras, anonymously and without face recognition; it is set up per project.

All questions
Physical retail intelligence

GoTrack is the intelligence layer between the shelf and the sale.

Measure interactions. Understand product performance. Activate better retail experiences.

or write to info@gotonom.com