East India

Recommendation & Personalisation across West Bengal

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

Districts
23
PIN codes
1,147
Cities mapped
29

Recommendation & Personalisation in West Bengal

Offline accuracy and revenue are different things. We measure recommendations by experiment against the business metric, because that is the only number that pays anyone.

West Bengal runs on engineering and steel, jute and textiles, leather, tea and financial services, an older industrial base with substantial legacy-system modernisation work ahead of it. Where recommendation & personalisation earns its budget here usually follows directly from that mix.

We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong. We hand over with runbooks, tests and a team that knows how it works, not a dependency.

নমস্কার , Nomoskar. We work in Bengali and English across West Bengal.

West Bengal coverage

State / UT
West Bengal
Region
East India
Districts covered
23
PIN codes covered
1,147
Cities mapped
29
Working languages
Bengali, 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 West Bengal?

Yes, all 23 districts and 1,147 PIN codes. Delivery is remote-first, so coverage is genuinely statewide rather than limited to the cities we happen to have offices in.

Which West Bengal sectors do you work with most?

Across West Bengal the economy leans towards engineering and steel, jute and textiles, leather, tea, financial services. An older industrial base with substantial legacy-system modernisation work ahead of it.

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 West Bengal

Covering all 23 districts. Tell us what you are trying to change.

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