Retail is one of the most operationally exposed business models - revenue depends on the right product being available, in the right place, at the right time, with the right customer experience around it.
01
You sell in-store and online. Your stock system doesn't update in real time across both. Customers order products that are out of stock. Overselling and unfulfilled orders become a weekly problem.
What breaks
Online and physical stock not synchronised
A sale online doesn't immediately reflect in the store's inventory. Reconciliation is done manually at end of day.
Reordering based on instinct, not data
Purchasing decisions are made by walking the stockroom, not reviewing sales velocity. High-margin items go out of stock; slow movers pile up.
Warehouse and fulfilment managed manually
Pick lists are printed. Packing notes are handwritten. Dispatch confirmation is delayed. Errors are common.
What we build
02
Every purchase your customers make tells you something. But the data lives in your POS and your e-commerce platform separately, and nobody has built the layer that turns it into retention and revenue.
What breaks
No unified customer profile
A customer who shops in-store and online is treated as two different people. There's no single view of who your best customers are.
Post-purchase communication is generic
Every customer gets the same email blast. There's no personalisation based on what they've bought or when they last visited.
Lapsed customers leave without intervention
A customer who used to buy every month stops. Nobody notices until six months later.
What we build
03
You have traffic. You have products. But the gap between visitor and buyer is wider than it should be - and without a systematic view of where people are dropping off, the conversion problem is invisible.
What breaks
No visibility on conversion funnel
You know how much you sold, but not how many people almost bought. No data on where shoppers are abandoning.
Abandoned cart recovery is absent or manual
A significant portion of customers add to cart and leave. There's no automated follow-up to recover that intent.
Product discovery is hard
Customers who would buy can't find what they're looking for. Search, filtering, and recommendations are underbuilt.
What we build
04
Which products are most profitable after returns and discounts? Which suppliers have the highest defect rates? Which promotions actually drove margin? This information exists in your data - but nobody's looking at it.
What breaks
Profitability calculated manually
Gross margin is visible. Net margin per SKU, after returns, discounts, and fulfilment costs, is not.
Supplier performance not tracked
Lead times, defect rates, and fill rates for each supplier are known anecdotally but not measured.
Promotion ROI not measured
You run campaigns. You don't know if they drove incremental revenue or just pulled forward purchases you would have made anyway.
What we build
Other Industries
See how these problems show up in a different sector.