Picnic - 173tech

Customer Behaviour

Data-driven insights impressed investors to the tune of $2.75m

Objective

Establish a flexible, scalable reporting framework to support an in-development social media app.

Obstacle

Integrate and analyse diverse data sources to uncover actionable insights and support fundraising efforts.

Outcome

Data-driven insights helped validate product strategy and secure $2.75 million in seed funding.

Background

Launching a new social media app in today’s saturated market is a challenge few overcome. According to Google Play statistics, 68.07% of apps never reach 1,000 downloads, and most fail within their first year. Determined to defy these odds, the Picnic team took a proactive, data-first approach.

During their beta testing phase, they used analytics not only to refine their product but also to demonstrate tangible traction to investors. Their goal: to understand how users engaged with the app, identify areas for optimisation, and validate product-market fit before launch.

Challenges

Product Evolution: Picnic’s app was still in development, with features expected to evolve significantly. A rigid reporting structure risked becoming obsolete within months. The team therefore needed a flexible, dynamic data solution capable of adapting as the product matured, one that could reveal user patterns directly from raw transactional data.

Third-Party Data: Picnic wanted to combine first-party user data, third-party market research, and customer feedback into a single, coherent view. This integration was key to identifying which features were driving engagement and retention, and which were not resonating with users.

Solution

One Source Of Truth: We built a unified data stack that centralised metrics from multiple data sources, including transactional and third-party research, into a single, consistent framework. This enabled the team to make like-for-like comparisons and rapidly extract insights that informed both product and business decisions.

Rapid Implementation: In just eight weeks, we successfully set up and deployed a complete data stack for Picnic. This involved ingesting core data sources, organising them into a cohesive system, and modelling the data to ensure it was both actionable and insightful.

Impact

Product Refinement: Even while the app was still in its beta phase, the data provided invaluable insights that led to some major shifts. The team quickly realised that while certain features were popular among users, they did not necessarily translate into features users were willing to pay for. Armed with this knowledge, they made significant adjustments, not just to the app’s user experience (UX) but also to the structure of their paid membership tiers.

Demonstrating Stickiness: Following the testing and changes, Picnic were able to demonstrate rapid improvements in user retention. This data not only helped validate their approach but was instrumental in securing $2.75m seed funding. The investment provided the resources needed to further develop the app and ramp up marketing efforts.