South India

Recommendation & Personalisation across Kerala

Recommendations that lift the metric you care about, measured by experiment, not by offline accuracy. Covering every district and PIN code in Kerala.

Districts
14
PIN codes
1,417
Cities mapped
18

Recommendation & Personalisation in Kerala

Cold start is where most recommendation systems disappoint, new users and new products are exactly the cases where a good recommendation matters most.

Kerala runs on healthcare, tourism and hospitality, IT services, spices and plantation agriculture and marine products, a health system with unusually high documentation standards, and a tourism sector that runs on multilingual customer contact. Where recommendation & personalisation earns its budget here usually follows directly from that mix.

Every engagement opens with a measurement: the cycle time, the cost per transaction, or the error rate we are being asked to move. You own the code, the models where they are open-weight, and the documentation to run it without us.

നമസ്കാരം , Namaskāram. We work in Malayalam and English across Kerala.

Kerala coverage

State / UT
Kerala
Region
South India
Districts covered
14
PIN codes covered
1,417
Cities mapped
18
Working languages
Malayalam, English

What is included

  • Event tracking design, since most projects start with inadequate data
  • Baseline popularity model to beat
  • Hybrid collaborative and content-based ranking
  • Cold-start handling for new users and new items
  • A/B testing framework with proper statistics
  • Business-metric reporting, not just offline accuracy

Questions

Do you cover all of Kerala?

Yes, all 14 districts and 1,417 PIN codes. Delivery is remote-first, so coverage is genuinely statewide rather than limited to the cities we happen to have offices in.

Which Kerala sectors do you work with most?

Across Kerala the economy leans towards healthcare, tourism and hospitality, IT services, spices and plantation agriculture, marine products. A health system with unusually high documentation standards, and a tourism sector that runs on multilingual customer contact.

How much data do we need?

Less than people assume to start. A content-based approach works from day one; collaborative filtering improves as interaction volume grows.

How do you handle new products?

Content-based features carry new items until interaction data accumulates, with deliberate exploration so new items get a fair chance to be seen.

How do we know it is working?

Controlled A/B tests measured on revenue or engagement, with proper statistical treatment rather than eyeballing a dashboard.

Recommendation & Personalisation in Kerala

Covering all 14 districts. Tell us what you are trying to change.

Or email bd@dtrasglobal.com · call +91 74118 77878