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The in-store product funnel: conversion metrics beyond footfall
E-commerce sees every product view, add-to-cart and abandoned basket. A store usually sees two numbers: visitors and sales. The steps in between can be measured product by product.
Definition
The in-store product funnel follows a product from the shelf to the till: in view, picked up, held, compared, then put back or not returned; purchase comes from your sales data. Store conversion rate (transactions divided by visitors) tells you how the store did. The product funnel tells you where a single product loses shoppers: never reached for, picked up and put back, or compared and beaten by another one. Cameras see that a product did not come back to its shelf; only your POS or BI data can say it was bought.
The metrics, and how to calculate them
| Metric | How to calculate it | What it tells you |
|---|---|---|
| Pickups | Times a product is lifted from the shelf, per day or week | Reach: does the product draw a hand at all? |
| Hold time | Average seconds a product stays in hand after a pickup | Consideration: how seriously it is weighed |
| Comparison rate | Pickups compared with another product ÷ pickups | Which products compete for the same decision |
| Put-back rate | Put-backs ÷ pickups | Interest that did not become a decision at the shelf |
| Not-returned rate | 1 − put-back rate | Pickups that did not come back to this shelf: not yet a sale |
| Pickup-to-purchase | Units sold (joined from your POS or BI) ÷ pickups | How much handling turns into sales |
| Never-touched | Products in view with no pickups in the period | Products invisible or unappealing where they stand |
A worked example
One day, one store, one rack (illustrative figures, the same as on our home page): 342 pickups, an average hold of 28 s, 147 pickups compared with another product (43%), 217 put back (a 63% put-back rate) and 125 not returned to the shelf (37%). Not returned is not sold: some go to the fitting room, another rack or are left elsewhere. Joined with the POS, which shows 109 units sold, pickup-to-purchase is 32%.
Read that way, the question is no longer "why did sales fall?" but "why do 63 of every 100 shoppers who pick this up put it back?" And that question has places to look: the price label, the sizes on the shelf, the product seen up close, the product it is compared with.
Using it well
- Compare like with like. A coat and a pair of socks are handled differently. Compare a product with itself over time, and with similar products in the same zone.
- Go down to colour. One model's put-back rate can hide a single colour that goes back far more often.
- Wait for enough pickups. Three put-backs out of four pickups is not a pattern.
- Change one thing at a time. Move a product or change its screen content, not both in the same week (in-store A/B testing).
- Join it with sales, carefully. A put-back is not a lost sale: the shopper may take another size or buy later.
Go deeper
Each step has its own guide: put-back rate, hold time, products compared together and never-touched products. To size what put-backs could be worth in your stores, try the put-back calculator. GoTrack measures every step with cameras close to the products, per product, colour, zone and store, without face recognition. Which team reads which number: GoTrack for teams.
Questions
What is a good put-back rate?
There is no universal benchmark: it depends on the category, the price and the store. The useful comparisons are a product against itself over time, and against similar products in the same store and zone. GoTrack reports the rate per product, colour, zone and store so those comparisons are possible.
Can GoTrack tell marketing which products are examined, and for how long?
Yes. It reports pickups per product and variant, average hold time, put-back rate, products compared together and never-touched products. It measures how long a product is held, not how long someone stands in front of it.
Can GoTrack show whether sales went up?
Not on its own. GoTrack measures what happens at the shelf — pickups, hold time and put-backs — and does not read POS data. To relate interest to sales, join GoTrack's CSV exports or webhook events with your own sales data.
Which reports does GoTrack produce?
Pickups, hold time, put-backs, never-touched products and products compared together, per product, colour, zone, hour and store; store visits; and, with screens, which content goes with longer holds. Every report can be filtered by store and exported as CSV or PDF.
See the funnel for products like yours.
We will show you each step on your own kind of products.
or write to info@gotonom.com