Personalization with proof
Recommendations, ranking and personalised messaging on your event data, shipped with an A/B test so the lift is yours, not a benchmark.
We measure:Conversion and order-value lift
AI that drives sales, not just traffic.
For retail and e-commerce, Eazyware builds AI that moves revenue: recommendation and personalization engines with measured lift, AI support agents on WhatsApp and web that resolve order queries, demand and inventory forecasting models, and multi-vertical super apps.
Which problems do we solve in Retail & E-commerce?
- Every shopper sees the same storefront and the same email
- Support volume on WhatsApp outgrowing the team
- Demand and inventory forecasting done in spreadsheets
Where AI pays off in Retail & E-commerce
Three plays we have built for this industry, each with the number we instrument so the result is measured, not claimed.
WhatsApp support that resolves
Order status, returns within policy and delivery issues handled end to end on the WhatsApp Cloud API, with a clean human hand-off.
We measure:First-contact resolution
Forecasting that moves stock
Demand and inventory models by SKU and location that feed purchasing and replenishment, monitored for drift every season.
We measure:Forecast error vs current process
What we design for in Retail & E-commerce
The constraints that shape the architecture before a line of code is written.
- Catalogue and event quality decide the ceiling; we audit both before promising a number.
- Peak-season traffic is the design load, not the average.
- Marketplace, POS and ERP integrations are usually the long pole; we scope them first.
- Cold-start and long-tail items get explicit fallbacks so the experience never goes blank.
Have more questions?
Questions we hear most from Retail & E-commerce teams.
It varies by catalogue and traffic. Every deployment ships with an A/B test so you see your own number rather than a benchmark.
Yes, via the Meta WhatsApp Cloud API, with order lookup and policy-gated actions.
Get in touch
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