Using Data To Increase Subscriber Retention By 39%.
Objective
Centralise and model customer behaviour.
Obstacle
Finding small improvements that could make a big difference.
Outcome
39% increase in subscriber retention.
Background
The UK’s most loved doggy borrowing platform was on a mission to deepen their understanding of their customers and the factors that influenced their journey. They wanted to uncover the key drivers behind customer acquisition, pinpointing what attracted new users to the platform and how to optimise these efforts further. Beyond acquisition, the platform sought to analyse engagement patterns—understanding what kept users active, connected, and coming back for more.
Challenges
Too Much Data: BorrowMyDoggy had a wealth of transactional data capturing actions like sign-ups, likes, and subscriptions, but they struggled to derive meaningful insights from it. The complexity and volume of the data made it difficult to uncover patterns or understand user behavior on a larger scale. Without connecting these data points, it was challenging to identify trends or make data-driven decisions to improve the platform.
The ‘Why’ Behind The ‘What’: The team needed deeper insights into what attracted new users, kept them engaged, and encouraged long-term retention. They wanted to identify the key drivers behind acquisition and determine what features or activities boosted engagement and loyalty. Improving the user experience and conversion rates was also a priority, requiring a better understanding of pain points and opportunities to streamline the customer journey.
Solution
The Right Tools: Building on their existing technical architecture, we conducted a thorough evaluation of data tools to determine which would best meet BorrowMyDoggy’s needs. This allowed us to design and implement an efficient end-to-end data pipeline tailored to their requirements.
ETL Process: We automated the extraction and modelling of data from their operational database, transforming raw information into actionable insights. To make these insights accessible, we created user-friendly dashboards that provided clear visibility into user behavior and growth trends, empowering the team to make data-driven decisions.
The Proof Is In The Numbers...
7
16
39%
Implementation
Handover: Once the data pipeline was fully operational, we focused on enabling the team to maximise its value. We provided comprehensive training on Metabase, equipping them to explore the data and derive their own insights independently.
User Behaviour: To enhance CRM effectiveness, we segmented the user base, enabling targeted communication and personalised strategies. We conducted a deep-dive analysis on the modelled data to uncover key opportunities for improving conversion. These strategies, informed by a robust understanding of user behavior, were designed to drive growth and optimise the platform’s performance.
Quick Wins: Our deep-dive analysis uncovered seven low-hanging fruit strategies spanning marketing, CRM, and search algorithms, each designed to boost user engagement and drive subscription uptake. These quick-win opportunities set the stage for immediate improvements while laying the groundwork for sustained growth.
