Stockouts are found after the lost sale
Symptom
Fast movers run out in some stores while the same SKU sits unsold in others; the weekly report explains the problem after the fact.
Retail Intelligence Lab
Retail AI pilots for stockouts, dead stock and margin
Most retailers already have sales, stock, supplier and channel data in their POS, ERP and marketplace exports. We find the two or three AI uses worth piloting, then build one into your workflow.
4 minutes · results on screen · no email needed
The challenges we see
Four patterns come up in almost every one of the retailers we work with. If one sounds familiar, that is usually where to start.
Reorder rules miss local demand
Symptom
Rules set at chain level keep replenishing slow lines while store-level demand, lead times and promotions change.
Channel data drifts apart
Symptom
Listings, prices and available stock are updated separately for stores, the website and each marketplace.
Markdowns arrive after margin has gone
Symptom
Price changes and ageing stock are reviewed late, so teams discount broadly instead of acting on the lines and stores that need it.
Practical AI uses
Four uses we would consider first. Each one runs on data most teams already have.
Use case 01
Assortment and shelf suggestions
- What it does
- Recommends which lines each store should carry or feature from local sales patterns, availability and seasonality. The buyer approves the plan.
- Data it needs
- 12–24 months of POS sales by store and SKU, current assortment and store attributes.
- Time to first value
- 8–12 weeks
Use case 02
SKU-level demand forecast
- What it does
- Forecasts weekly demand by SKU and store, then proposes reorder quantities and transfers for review.
- Data it needs
- Sales, on-hand stock, receipts, supplier lead times and promotion calendar.
- Time to first value
- 8–12 weeks
Use case 03
Multi-channel listing sync
- What it does
- Flags mismatched titles, attributes, prices and stock across your website and marketplaces, then queues updates for approval.
- Data it needs
- Product catalogue, channel feeds, order and stock exports, and marketplace performance data.
- Time to first value
- 6–10 weeks
Use case 04
Markdown and price guidance
- What it does
- Suggests when to mark down and by how much, within margin floors and stock-age rules you set.
- Data it needs
- Sales, cost, current price and stock age by SKU, plus competitor prices if you track them.
- Time to first value
- 10–14 weeks
How we implement
Four steps, with a decision point after each. You can stop after any of them and keep what was built.
-
Diagnose
Review sales, stock, supplier, promotion and channel data with buyers, inventory managers and store operators.
You get: a ranked use-case brief with baseline, expected value, payback range and data gaps
-
Pilot
Run one use case in one category and selected stores or channels, with a baseline and comparison method agreed before we start.
You get: a working recommendation workflow and a go / no-go report
-
Integrate
Connect approved data feeds to your POS, ERP or warehouse, add permissions and monitoring, and train the people who will use the output.
You get: a production system your team can run
-
Scale
Extend the workflow to more categories, stores or channels in stages, with thresholds, exception handling and a named owner.
You get: a rollout playbook your team owns
Expected outcomes
These are estimates, not client results. We confirm or revise each one against your own baseline during the diagnosis.
- Estimate for a first project, measured against the agreed baseline. Assumes the forecast is used in replenishment and supplier lead times are reasonably reliable.
- Estimate for the targeted category. Assumes reorder rules change, buyers act on exceptions and stock cost and age fields are complete.
- Estimate from the manual tasks replaced in the pilot. Assumes recommendations arrive in an existing workflow and the team does not add a second review process.
- Range equals pilot and integration cost divided by estimated monthly gross-margin and working-capital benefit. Excludes major ERP replacement and depends on rollout to the pilot scope.
Questions retail operators ask
Something else on your mind? Ask us directly.
Do we need a data platform before we start?
No. A first pilot can usually start with exports from the POS, ERP and relevant channel feeds. Diagnosis checks whether the fields are complete enough and lists the fixes before the pilot.
Will this work with several store systems?
Often, if we can map the systems to a common set of product, store, stock and sales fields. We usually start with stores that share one system, then add others after the workflow is proven.
Who owns the models and the data?
You do. Models, code and data stay in your environment or your cloud account. We don't reuse your data to train anything for other clients.
How much of our team's time does a pilot take?
Plan for about four hours a week from a category, inventory or ecommerce manager, plus a short IT or data session to set up access. The exact load depends on the number of systems and data checks.
What if the pilot misses its target?
We agree the target and baseline before we start. If the pilot falls short, you get a written explanation of why, and you are not committed to the next phase.
Reviewed by Faruk Karagöl, CTO ·
Find out which use case fits your store
18 questions, about 4 minutes. You see your score and top three gaps before we ask for anything.
