Case studies · An e-commerce company in Thailand

Private sector · Thailand

Sale days that hold, and a clear picture of who buys

An online retailer in Thailand selling to customers across the country.

Client: Name withheld
Location: Thailand
Sector: Private sector

A young team works at laptops round a long table late at night, a wall screen showing order graphs climbing and city lights outside.

Illustration generated for Padmanex. Not a photograph of the client.

Result: Sale-day peaks handled on the live platform
Result: Product recommendations tailored to each shopper
Result: Orders broken down by region, city and age range

The situation

Traffic on big sale days climbed far above normal, and the site had to stay up through the peak.
Shoppers saw much the same products whatever they had browsed or bought before.
The business had plenty of order data but no easy way to see who was buying, where and what.

What we delivered

Platform work so the site absorbs sale-day traffic peaks.
AI recommendation engines that suggest products from each shopper’s own behaviour.
Customer analytics that break orders down by region, city and age range, showing which groups order most.

What this means for an Indian department

A scheme window or an examination result date behaves like a sale day: a published date, a national spike and no room to fail. The analytics carry over as well. Knowing which districts, towns and age groups use a service most is how a department plans its outreach and staffing.

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