How would you improve restaurant search?
Google PM Interview - Product Improvement Interview Question: How would you improve restaurant search?
Ask Clarifying Questions
Before jumping into solutions, ask the right questions to narrow the scope and avoid building for the wrong objective.
Here are the key clarifying questions I would ask:
1. Is the restaurant search being improved for an existing app like Zomato, Swiggy, Google Maps, or are we building a new standalone product?
Assumption: We're improving search within an existing restaurant discovery + delivery platform, similar to Swiggy or Zomato.
2. Is there any specific target audience for the restaurant search feature that we want to focus on?
Assumption: Its upto you to decide.
3. Is there any specific goal we want to achieve with this improvement?
(E.g. Improve search-to-order conversion, Reduce search time, Increase user satisfaction, or Enhance restaurant discoverability)
Assumption: Its upto you to decide.
4. Is there any specific target region (i.e. specific country or global) we want to focus on?
Assumption: For the scope of this question you can focus on India.
5. What platforms are we targeting — mobile app, web, or both?
Assumption: The solution will be mobile-first, since most food delivery and discovery happens on mobile apps.
8. Are there specific pain points users have reported in the current search experience?
(e.g. irrelevant results, poor filters, or slow response time)
Assumption: You can come up with your own assumptions
9. Are we considering any monetization tied to search (e.g., promoted listings)?
Assumption: Monetization through promoted listings is allowed, but must not degrade the trust in organic relevance.
Goals
The primary goal of improving restaurant search is to help users discover and order from restaurants that best match their intent—quickly, confidently, and delightfully. This involves designing a search experience that is not only fast and intuitive but also personalized, trustworthy, and aligned with the user’s context (e.g., time of day, cuisine preference, delivery constraints).
We want users to feel efficient, empowered, and satisfied every time they use the search function—whether they are reordering a favorite meal, exploring trending spots, or trying something entirely new.
Metrics:
Search-to-Order Conversion Rate (key conversion metric)
Search Abandonment Rate (lower is better)
CTR on Top 3 Search Results (relevance indicator)
A key objective is to reduce the cognitive load of filtering through hundreds of listings by surfacing context-aware, highly relevant restaurant suggestions. Whether a user searches for “veg lunch under ₹300” or “late-night Chinese,” the experience should feel tailored, frictionless, and trust-enhancing—making search a natural entry point to every order journey.
User Segments
1. Power Diners : Frequent users who order food 3–5 times a week and prioritize speed, familiarity, and convenience.
Needs:
Instant reorder options from past history
Smart autocomplete for recent and favorite restaurants
Personalized ranking of results based on usage patterns
2. Curious Explorers : Occasional users who love discovering new cuisines, restaurants, and trending food experiences.
Needs:
Rich visual results (photos, ratings, tags)
Filters for trending, new, or top-rated places
Personalized suggestions like “You might like” or “Popular in your area”
3. First-Time Users : New or infrequent users still learning how to navigate the app or choose what to order.
Needs:
Guided search flows and simplified filters
Pre-curated lists like “Best in your area” or “Beginner picks”
Prominent reviews and hygiene ratings for decision support
4. Value Hunters : Budget-conscious users who optimize for cost, deals, and quantity.
Needs:
Price filters (e.g., “Under ₹200”), delivery fee visibility
Highlighted deals, discounts, and combos
Sort by “best value” or “lowest cost per meal”
Priority Segment: Power Diners
Why?
They represent the most frequent and high-intent users of the platform, often placing multiple orders per week. Improving their search experience leads directly to higher order conversion rates, repeat usage, and higher lifetime value.
They already know what they want but expect speed, relevance, and personalization. By reducing friction in their search journey (e.g., enabling 1-tap reorders, smart autocomplete), we create a seamless experience that strengthens user stickiness.
Pain Points:
Their previous orders and preferences aren’t reflected in search results, leading to irrelevant listings and extra effort. They often have to repeat the same search queries (e.g., favorite dish or restaurant) instead of seeing tailored shortcuts, save defaults or smart suggestions.
Sponsored or promoted listings often crowd out relevant choices, breaking trust and causing frustration.
They waste time clicking into restaurants that are closed, offline, or have delayed delivery — because real-time availability isn’t clearly shown upfront.
They crave variety but often default to the same 2–3 places out of habit, leading to “menu fatigue” and reduced excitement around mealtimes.
There’s no intelligent nudge when a usual restaurant is offering a deal or has a shorter ETA than normal — missing a personalized opportunity.
Search doesn’t offer social validation cues (e.g., “10 of your friends ordered from here this week”) that could drive faster, more confident decision-making.
They don’t receive smart reminders to reorder just before typical mealtimes, based on personal patterns (e.g., “Your Thursday pasta order?”), which could reduce search effort altogether.