Introduction
Buyer chats per listing is one of the most important health metrics on OLX India. It tells sellers whether listing on OLX works, and it predicts whether they will list again and pay for Featured ads or Boost to Top. The scenario: in the Mobiles category, buyer chats per new listing fell 18% over four weeks. Total app traffic looks roughly flat. I'll work through this methodically: clarify the metric, rule out external factors, map the product journey, decompose the metric, gather data, form hypotheses, find the root cause, validate it, and decide what to do.
Clarify → rule out external factors → understand the journey → break down the metric → gather and prioritise data → hypothesise → find the root cause → validate → decide → resolve. Say the framework aloud first so the interviewer can follow your path.
Step 1
Clarifying Questions (3 minutes)
- Hypothetical answer: Unique buyers who start a chat on a listing within 7 days of posting, averaged across new Mobiles listings.
- Impact: A change in either buyers (numerator) or listings (denominator) can move it.
- Hypothetical answer: Gradual over two weeks, then flat at the lower level.
- Impact: Suggests a release rolled out in stages, or a slow external shift, rather than an outage.
- Hypothetical answer: All regions, slightly worse in tier-2 cities.
- Impact: Less likely a single-city event.
- Hypothetical answer: New Mobiles listings rose about 12% in the same period.
- Impact: Very important. Chats per listing can fall simply because supply grew faster than demand.
- Hypothetical answer: The September app update shipped revamped listing and ad-detail pages, AI-powered Verified Users, and Mark as Sold improvements.
- Impact: Three candidate internal causes to examine.
Practice similar questions
Subscribe to access the full answer
.png){kind=logo}
