An entire customer pipeline optimised with data
Objective
Build predictive analytics to understand and anticipate customer behaviour.
Obstacle
With no existing infrastructure or data foundations, the challenge was to start from scratch, designing and implementing a scalable analytics ecosystem
Outcome
A fully optimised customer journey, powered by a centralised data platform, predictive insights, and automated reporting.
Background
Ablefy empowers over 50,000 entrepreneurs to create, market, and sell digital products to more than 3 million end customers worldwide. Following a successful Series A, the team recognised the opportunity to turn their rich but fragmented data into a competitive advantage.
They partnered with 173tech to establish a modern data ecosystem, one that could connect the dots between product engagement, sales performance, and customer lifetime value. The goal: to embed analytics into every decision, aligning marketing, sales, product, and customer success around one shared source of truth.
Challenges
Fragmentation: Data was scattered across Salesforce, Google Sheets, and backend systems, making analysis and reporting a manual, time-consuming process. Quarterly reporting alone required eight days of effort, delaying insights and slowing decision-making. The absence of automated systems further limited the ability to predict customer churn, evaluate marketing ROI, and measure customer lifetime value (LTV), restricting business growth.
Inconsistency: Inconsistent revenue definitions across teams led to discrepancies in reporting and strategic planning. Without a unified approach, aligning financial metrics and making data-driven decisions became challenging, further complicating overall business operations.
Solution
Data Launcher: We kickstarted Ablefy’s analytics journey with a robust foundation. We helped them select and set -up the right tools for ongoing data-driven growth and integrate their core database for reporting. In conjunction Ablefy were able to start hiring their own internal team.
Revenue Reconciliation: A unified revenue model was implemented to reconcile discrepancies across Salesforce, backend systems, and financial reports. By aligning multiple definitions of revenue into a single source of truth, we eliminated inconsistencies and manual processes. Automated pipelines now refresh revenue data daily, ensuring reliable and consistent reporting for strategic decisions.
Acquisition
Customer Journey Mapping: We mapped out the end-to-end customer journey, integrating data from multiple sources, including marketing platforms, user behaviour logs, and transaction records. This enabled a comprehensive view of customer touchpoints, helping to identify drop-offs and optimise onboarding, engagement, and retention strategies.
Marketing Analytics: Data from platforms like Google Ads, Meta, and GA4 was centralised to track granular marketing attribution and campaign performance. A marketing performance dashboard was developed to analyse cost-per-click (CPC), cost-per-acquisition (CPA), and ROI at a channel and campaign level. These insights helped reallocate ad spend efficiently, achieving better returns on marketing investments. Our work led to a 90% increase in seller registrations while reducing marketing spend by 36%.
Predictions
LTV Prediction: Predictive LTV models were designed to provide both short-term and long-term insights. A layered approach balanced immediate signals from new customers with more accurate predictions as data accumulated. These models allowed marketing and sales teams to focus on high-value customers and campaigns with the best long-term ROI, optimising acquisition strategies.
Churn Prediction & Prevention: Seven key behavioural indicators were identified and modelled to predict customer churn. Automated workflows were built to flag at-risk customers directly in Salesforce, enabling proactive retention efforts. These models provided actionable insights to the customer success team, reducing churn rates and improving overall customer satisfaction.
Data Product: Leveraging the existing data pipeline, Ablefy launched a suite of multi-tenant Seller Insights dashboards as part of its Pro offering, branded as “7 Analytics 3.0 Modules.” The release garnered positive feedback from Ablefy’s B2B clients, achieving high activation rates and sustained engagement.
Creating Value For Ablefy...
Our data stack was 85% cheaper than the previous solution,
We saved 35% on ad spend but increased seller registration by 90%,
And we saved the team 8 days a month on reporting.
Get In Touch
Our friendly team are always on hand to answer questions, troubleshoot problems and point you in the right direction.
