Customer Discovery and business model establishment for B2C product

"SpotSavvy" is a mobile application concept designed to enhance the personal safety of women aged 25-45 in metro areas. The app addresses the critical need for safety by providing users with AI-driven safety scores for locations, safe walking routes, and safe parking spots. This is achieved through the analysis of crime statistics, user-generated data, and other relevant factors to provide real-time safety assessments.  

During the development of SpotSavvy, I played a key role in customer discovery, business model definition, and go-to-market strategy. Applying customer discovery techniques, our team conducted over 250 interviews to deeply understand the target user's pain points and needs, pivoting from an initial focus on parking solutions to a core emphasis on safety. This pivot was driven by compelling user feedback highlighting safety concerns as a paramount priority. I utilized the Business Model Canvas to articulate SpotSavvy's value propositions, customer segments, channels, and revenue streams, which included consumer subscriptions, pay-per-use options, and B2B sponsorships. The go-to-market strategy involved a phased launch, focusing on beta testing, incentivizing user reporting to refine the safety algorithm, and scaling the user base. This project showcases my ability to translate customer insights into a viable business model and develop a targeted go-to-market approach, crucial skills for a Senior/Lead Product Manager."  

Key Skills and Concepts Demonstrated:

Customer Discovery: The project highlights my proficiency in conducting customer interviews (250+), synthesizing data, and iterating on the product concept based on user feedback. It shows I can pivot based on data, moving from parking to safety.  

Business Model Canvas: My ability to use the Business Model Canvas is clearly demonstrated by outlining value propositions, customer segments (25-45-year-old women), channels, revenue streams (subscriptions, pay-per-use, ads, sponsorships), and key partnerships.  

Go-to-Market Strategy: The description emphasizes the phased launch approach, beta testing, and iterative refinement of the algorithm based on user input, showcasing a data-driven approach to product development and launch.  

Market Analysis: The project demonstrates an understanding of market segmentation, target customer prioritization, and competitive analysis.  

Financial Modeling: The inclusion of revenue projections, cost considerations, and ARPU/CAC/LTV analysis indicates an understanding of the financial viability of a product.  

Problem-Solving: The core of the project addresses a significant problem (women's safety in metro areas) with a well-thought-out solution.  

Data-Driven Decision Making: The emphasis on using crime statistics and user-generated data to drive the safety score algorithm highlights your ability to use data to inform product decisions.  

This detailed description should effectively communicate your skills and experience to potential hiring managers.