# Solution: Favorite Products and Optimization ## 1. Three Products I Admire ### Google Maps Job to be done: - Help users confidently get from intent to arrival, including search, route choice, navigation, and local discovery. Why I admire it: - Global coverage. - Strong routing. - Local search and reviews. - Multimodal navigation. - Useful in both planned and urgent situations. Competitors: - Apple Maps: strong iOS integration and polished design, but historically less broad in local discovery. - Waze: excellent driver incident reporting, but narrower outside driving. - HERE WeGo: strong offline maps, less consumer mindshare. Trade-off: Google Maps is broad and powerful, but complex trips, parking, EV charging, and route explainability still create pain. ### Notion Job to be done: - Help individuals and teams organize knowledge and lightweight workflows. Why I admire it: - Flexible blocks. - Databases. - Templates. - Strong community. Competitors: - Evernote: simpler capture, less flexible workflow building. - Coda: powerful interactive docs, steeper learning curve. - Confluence: enterprise documentation, less personal flexibility. Trade-off: Notion's flexibility can create information architecture sprawl. ### IKEA Flat-Pack Furniture Job to be done: - Help customers furnish a home affordably with transportable, modular products. Why I admire it: - Product design, packaging, logistics, and price are tightly integrated. - Showrooms help customers visualize complete rooms. - Flat-pack model lowers distribution cost. Competitors: - Wayfair: more online selection, less consistent in-person experience. - Target: convenient and affordable, less complete room-planning depth. - West Elm: higher design polish, higher price. Trade-off: IKEA wins on affordability and system design, but assembly friction and store complexity can be painful. ## 2. Improvement Plan: Google Maps Parking Confidence ### Target Users - Urban drivers. - Event-goers. - Travelers. - EV drivers. - People visiting unfamiliar neighborhoods. ### Pain Point Google Maps often gets users to the destination, but not necessarily to a confident parking outcome. Users still circle blocks, misjudge garage entrances, face unexpected pricing, or discover that street parking is restricted. ### Hypothesis If Google Maps helps users choose parking based on certainty, price, distance, and walking time before arrival, then users will spend less time circling, feel more confident, and return to Maps for future driving trips. ## 3. Feature Proposal Parking Confidence Layer: - Parking difficulty badge for destination. - Off-street garage and lot options. - Price, hours, walking time, and entrance routing. - Availability confidence. - Reservation where partners support it. - On-street likelihood zones only where data quality is strong. MVP: - Launch in dense cities with garage partners. - Focus on off-street options first. - Add walking directions from parking to destination. - Collect feedback on availability and entrance accuracy. ## 4. Roadmap Phase 1: Discovery and data quality. - Identify markets with high parking pain and strong partner coverage. - Validate data reliability. Phase 2: MVP. - Parking badge. - Garage option comparison. - Entrance routing. - Reservation links. - User feedback. Phase 3: Expansion. - Event and airport flows. - EV charging filters. - On-street probability where city data supports it. Phase 4: Personalization. - Rank by user preference: cheapest, closest, most certain, EV, accessible. ## 5. Metrics Primary metric: - Successful parking-assisted trips. Secondary metrics: - Parking option click-through. - Reservation conversion. - Time from arrival area to parked. - Repeat use. - User satisfaction after parking. - Entrance accuracy. Guardrails: - Illegal parking reports. - Wrong availability reports. - Driver distraction. - Congestion near recommended areas. - Partner bias complaints. - Refunds or disputes. ## 6. Experiment and Rollout Rollout: - Pilot in one or two markets. - Compare users shown parking guidance with matched users or randomized eligible sessions. - Measure trip-level outcomes and feedback. Decision rule: Scale if parking-assisted trips reduce time-to-park and improve satisfaction without increasing complaints, wrong availability, or congestion. ## 7. Stakeholder Alignment Partners: - Maps engineering. - Local data. - Parking partners. - UX research. - Trust and safety. - Legal. - Ads/commerce if monetization is considered. Narrative: "Maps is trusted for navigation, but the trip is not done until the user can park. Improving the last 200 meters strengthens Maps' core job to be done."