Industry pathway
Retail & Consumer Businesses
Bring sales, inventory, customer, and channel data together to understand performance by store, product, and customer, and to plan stock with more confidence.
Use cases
What we solve in retail
Retail
A fashion warehouse and its shop, a supermarket's tills and fresh food hall, a click-and-collect point, a returns centre, and a café with a stamp card.
Pick a use case to see the problem and what we build, or play the tour.
An illustration of typical work in retail. The business, people, and data are invented.
All 6 use cases in the scene
One stock count across channels
The shop's count says a jacket has sold out, while the warehouse next door still has plenty.
One stock count shared by the tills, the warehouse and the website, so any of them can fill a sale.
Store footfall & staffing
Rotas are set weeks ahead, so too few tills are open when a rush comes through the doors.
Footfall from the door counters, forecast by the hour, so staff are on the tills before the rush.
Pricing & promotions
Fresh food stays at full price to its last day, then goes in the bin when it has not sold.
Sales and dates on the shelf feed the shelf labels, so prices drop while there is time to sell.
Online orders & click-and-collect
Orders are picked in the order they came in, so a customer can arrive before theirs is ready.
Picking planned by collection time, so each order is in its locker before its customer is due.
Returns
Return reasons are logged one parcel at a time, so the same fault comes back again and again.
Return reasons brought together by product, so a pattern is spotted and fixed at its source.
Loyalty & repeat customers
Regulars drift away and nobody notices until they have stopped coming in altogether.
Loyalty card visits watched for a drop, so a lapsing regular gets a reason to come back in time.
Common challenges
Where data and process problems usually show up
01
Channel data does not reconcile
Point-of-sale, e-commerce, and marketplace data use different product and customer identifiers. A shared model allows like-for-like comparison.
Relevant services
02
Stock is in the wrong place
Combining sales velocity, stock levels, and replenishment lead times highlights overstock and stock-out risk earlier.
03
Customer insight is limited to totals
Segmentation by behaviour and value helps target promotions and service where they matter.
Typical data sources
- Point of sale
- E-commerce platforms
- Inventory systems
- Loyalty and CRM
- Marketplace exports
This page describes common sector challenges and the services that address them. It does not describe specific client engagements.
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