AI for retail and e-commerce in Africa
African retail runs on thin margins and WhatsApp conversations. The winners forecast demand instead of guessing, and answer every customer at the moment of intent rather than the next business day.
What we hear
- Stock-outs and overstock from spreadsheet forecasting
- Customer questions at all hours across WhatsApp, social and web
- Generic promotions that ignore what each customer actually buys
- Order status queries drowning the support inbox
Where AI moves the numbers
Demand forecasting
Store- and SKU-level forecasts that respect seasonality, promotions and local events.
WhatsApp commerce agent
Catalogue questions, order tracking and re-orders handled conversationally, 24/7.
Related use case →Personalized offers
Recommendations and promotions matched to each customer’s actual behaviour.
Back-office automation
Supplier reconciliation, price-file processing and reporting without the month-end fire drill.
Related use case →Common questions
We have messy data. Is that a problem?
It is normal. Every engagement starts with a data assessment; useful models are regularly built from imperfect POS and inventory data, and we tell you honestly when they cannot be.
Does this work for smaller retailers?
Yes. Agents are priced by scope, and a WhatsApp commerce agent is often viable well before enterprise-scale ML is.
Let's talk retail & e-commerce
Book a 30-minute call and we'll map the highest-value AI play for your organisation.