Adding AI to Search
Building and mentoring a team
Senior Product designer (Team Lead)
Charter - Discovery | Pod - Search
with Somanshu: Associate Product Designer
Problem:
Search was a critical but stagnant flow—unchanged for years due to its impact on a key metric: Search CTR.
-
High oversight — every change required business approval
-
Underutilised insights — strong data existed but wasn’t translated into product
-
Low iteration — risk aversion limited experimentation
-
Underperformance — CTR at 73% vs ~80% industry benchmark
Impact
-
Redesigned and launched AI-powered search
-
Improved Search CTR from 79% → 81%
-
Operationalised data and research into product decisions
-
Influenced multiple downstream features (e.g. language rails, content formats)
-
Brought previously unprioritised user problems onto the roadmap
Approach
I used a hackathon as a wedge to bypass approval constraints and prototype a new direction.
The initial proposal was a chat-based interface or natural language search search based on past failures and user expectation (Jacobs law), I challenged this direction. Alternatively I designed a tappable prompt component, subtly educating the user about long form text being available instead of just keywords.
We built the search experiece in a record time of 2 days.
Mapped key user journeys after a brief session on journey mapping to build system understanding
Based on the hackathon success, leadership wanted to launch to production,
Key Constraints & Decisions
-
AI search was gated behind an opt-in entry (banner) to avoid business exposure
-
I pushed for default entry or toggle to improve discovery (top-of-funnel), but this was deprioritised due to dev constraints
This trade-off directly impacted feature adoption—validated later in research.
Feature was launched to 5% of iOS users as an experiment
Phase 2
Strong early signals led leadership to expand the feature scope:
-
Merge AI and standard search into a single experience
-
Introduce new content rails to drive consumption
-
Enable advertising and branding opportunities
-
Reduce result latency
-
Create a distinct visual identity for search
-
Make the experience feel more conversational
The PM scoped delivery screen-by-screen to optimise development bandwidth. I chose to design the end-to-end flow to ensure a coherent experience.
I defined the landing page structure while Somanshu handled its detailing.
In parallel, I partnered with the data analyst to surface long-standing user issues and combined them with research insights.
This allowed me to go beyond the initial scope and solve for validated user problems across the results and typing states. The solution was well received and successfully added to the roadmap.
Mock design initative by associate designers to build an understanding of coordination with data, research and design expectations
User Testing & Validation
Conducted qualitative research with 18 users in partnership with the research team.
Key insights:
-
~50% (9/18) exited the app to search externally
-
Large, unstructured results increased confusion
-
Users defaulted to exact keyword search
-
AI search was misunderstood due to mental model gaps
-
Tappable prompts were appreciated but misinterpreted
Outcome:
Grounded data insights in real user behavior, enabling us to design solutions for actual user needs rather than assumptions.
Recreated the homepage pixel-perfect using the design system to learn Figma and core components
Data & insights
Partnered with data to analyse cross-platform search (Android, CTV, iOS, Web), uncovering high watch time but lower CTR for SVOD users.
-
Insight → execution — Designed high-fidelity flows for contextual search and non-serialized content rails to address poor relevance in results.
-
Roadmap influence — Drove 12 data-backed recommendations into the roadmap, including multi-language standardisation and out-of-catalogue handling to reduce drop-offs.
Recreated the homepage pixel-perfect using the design system to learn Figma and core components
Search Landing Page
Strong
Recreated the homepage pixel-perfect using the design system to learn Figma and core components
Search Typing State
Strong
Recreated the homepage pixel-perfect using the design system to learn Figma and core components
Search Loader
Strong
Recreated the homepage pixel-perfect using the design system to learn Figma and core components
Recreated the homepage pixel-perfect using the design system to learn Figma and core components
Recreated the homepage pixel-perfect using the design system to learn Figma and core components
Recreated the homepage pixel-perfect using the design system to learn Figma and core components
Recreated the homepage pixel-perfect using the design system to learn Figma and core components
Recreated the homepage pixel-perfect using the design system to learn Figma and core components
Recreated the homepage pixel-perfect using the design system to learn Figma and core components