Market Research · 0→1 Design

Uber — FindMyRide Spot

78% of surveyed Chennai riders said they've switched to Ola or Rapido at least once purely over pickup-point confusion. I sized the opportunity, ran a live survey and rider interviews, and shipped a tested "smart pickup" prototype.

Role
Solo PM — research, sizing, prototyping
Method
TAM/SAM/SOM, user survey, interviews
Scope
Ride-hailing pickup experience, Chennai
Deliverable
Research PDF, live survey & prototype
Walkthrough

Project walkthrough, in five points

The original video walkthrough is no longer available — here's the project end to end in five points instead.

01
The trigger — 78% of surveyed Chennai riders have switched to Ola or Rapido at least once purely over pickup-point confusion, with 72% needing to call the driver just to be found and a 38% cancellation rate tied directly to the pickup point.
02
Sizing the opportunity — before designing anything, sized the problem top-down from a ~139M national ride-hailing base to a realistic 800K–1.2M rides/month a smart-pickup feature could capture in Chennai alone.
03
Grounding it in research — ran a live rider survey plus structured interviews, then built 5 rider personas spanning frequency of use, safety concern and tech comfort, so the redesign followed real behavior, not assumptions.
04
The fix — "Smart Pickup" — replaced the single ambiguous map pin with curated, numbered pickup zones (photo, walk time, distance) plus a live beacon and driver chat, including a dress-colour picker for instant visual ID.
05
Proving it works — built and tested the full flow as a working, clickable prototype with real Chennai locations and zone photos — not just wireframes — so the experience could be evaluated end to end.
The problem

Pickup confusion is a switching trigger, not a minor annoyance

"Where exactly are you?" is one of the most common rider-driver exchanges in dense Indian cities — vague pins, identical-looking gates, and unclear curb space turn a 2-minute pickup into a 10-minute phone call. I ran a structured survey and rider interviews in Chennai to size how much business this actually costs.

78%
Have switched to Ola/Rapido at least once over pickup confusion
72%
Had to call the driver just to be found
38%
Cancellation rate tied directly to the pickup point
58%
Cite busy or visually unclear streets as the root cause
Market sizing

Big enough to matter, narrow enough to ship fast

Sized the opportunity top-down from India's ride-hailing base to a realistic, captureable monthly volume in one metro.

~139M
TAM — India's ride-hailing user base
15–20M
SAM — serviceable riders across the Chennai metro
800K–1.2M
SOM — realistic rides/month a smart-pickup feature could capture
Research

Validated with a live survey and rider interviews, not just intuition

Built 5 rider personas from the survey and interview data — spanning frequency of use, safety concern, and tech comfort — to ground prioritization in real behavior rather than assumptions about "what riders probably want."

View live survey ↗
Solution

"Smart Pickup" — named zones instead of vague pins

Instead of a single ambiguous map pin at high-traffic spots, the redesign gives riders curated, numbered pickup zones with the context they need to walk straight to the right spot — and gives drivers a fast, visual way to confirm they've found the right person.

FEATURE 01

Smart Pickup Locations

Curated zones at high-traffic spots — malls, airports, railway stations — each showing how many numbered pickup zones are available before the rider commits.

FEATURE 02

Zone Selector with context

Every zone shows a photo, walk time, and distance, so the rider picks the exact spot — not a street name — before the driver is even confirmed.

FEATURE 03

Live Beacon + driver chat

Full messaging with the driver, including a "dress colour" picker the rider can send for instant visual ID, plus quick replies for the last 200 metres.

FEATURE 04

End-to-end guided flow

One continuous path from intent to pickup, replacing the back-and-forth phone calls the survey flagged as the #1 friction point.

Step 1–2
Home → Select Location — rider picks a destination or a Smart Pickup location (e.g. Phoenix Marketcity, Chennai Airport, T. Nagar).
Step 3–4
Choose Zone → Booking Confirmed — rider selects the exact numbered zone by photo and walk time, then confirms.
Step 5–6
Pickup Spot → Walking Directions — turn-by-turn guidance to the exact zone, removing pin ambiguity.
Step 7
Live Beacon — real-time chat with the driver, quick replies, and the dress-colour picker for fast visual confirmation.
Prototype

A working app, not a wireframe

Built and tested the full Smart Pickup flow as a live, clickable prototype — real Chennai locations, real zone photos, and a working chat screen.

Live prototype — Smart Pickup Open full screen ↗
Open interactive prototype ↗ View live survey ↗