Earn Retention
The system that turns retention from a relationship-driven activity into a measurable business lever, integrating data science, churn prediction, marketing automation, and customer data platforms.
In growing organisations, retention stops being a relational matter and becomes an economic lever to be governed over time. The problem is not the absence of data — it is the absence of a system that transforms data into decisions, actions and measurable results. We build that system, from assessment to loyalty, integrating data science, marketing automation and predictive intelligence into a single operational architecture.
What we build together
Customer profiles enriched with internal and external signals and a scoring model calibrated on your historical data. The sales and marketing team has an actionable priority list, not a database to interpret.
A system that estimates the probability of abandonment for each customer before it happens, with an updated list of who is at risk and in which time window. Intervention becomes anticipatory, not reactive.
A set of KPIs — retention rate, churn, LTV (lifetime value), CAC (customer acquisition cost), repeat rate — structured in an analytical framework that the board and operational teams read with the same definition and the same logic. BI stops being reporting and becomes a governance instrument.
We build a state-based framework that maps the customer lifecycle through defined states — active, at risk, lost, recovered, reactivated. The system monitors monthly movements between states and produces the transition KPIs that make retention readable and governable over time: at-risk rate, churn rate, recovery rate, reactivation rate. This is not a generic descriptive model — it is an operational control tool that says exactly where each customer is and where they are heading.
A communication system that reacts to behaviour, not to an editorial calendar. Every trigger is connected to a real signal: a customer at risk, an opportunity for repurchase, a value threshold crossed.
We build or integrate the Customer Data Platform that unifies customer demographic, behavioural and transactional data into a single actionable profile. It is the infrastructure that makes personalisation, advanced segmentation and automation possible — without it, communications remain generic and predictive models do not have a sufficiently structured data foundation to work on.
Interventions on interfaces at critical moments in the customer lifecycle, where the system calls for them. It is a component of the programme, not its centre.
How we do it
1. Assessment and CRM Audit
We map the current state: retention process, CRM quality, available data, technology stack, existing activations. The output is a shared map of where customers are being lost and why.
2. Data Foundation and Enrichment
We build or rewrite the collection and integration architecture, and enrich existing profiles with external signals. This phase does not produce visible value immediately — but it determines the solidity of everything built on top of it.
3. Modelling and Intelligence
We build the scoring, churn prediction and segmentation models, and the analytical tooling for reading retention over time. This is the moment when data stops describing and begins to explain.
4. Activation
Automations become operational. Behavioural triggers replace manual flows. Every relevant signal generates a coherent action — without manual intervention for each individual case.
5. Loyalty and Handoff
The loyalty system is designed as the final layer. The programme closes with a formal transfer: documentation, update criteria, governance. The internal team knows how to evolve it without depending on us.
Answers to your questions
Everything you need to know about how we work and how we can help.
With the assessment. It is not a prerequisite — it is the first step of the programme. We have worked with organisations with years of unstructured data — that is the most common situation, not the exception.
It depends on the quality and history of the data, not just the quantity. The assessment includes an evaluation of modelling feasibility based on the available data.
The system integrates with existing tools. It does not require changing the stack — it requires connecting it so that data flows correctly and automations react to the right signals.
An end-to-end programme — from assessment to loyalty system activation — has a variable duration of between four and six months, depending on the complexity of the customer base and the starting stack.
For organisations with a sufficiently large customer base and history on which it makes sense to build churn and scoring models. Typically with an existing CRM — even an imperfect one — and a retention, CRM or marketing owner with an explicit mandate to reduce churn and increase LTV. It works for those who want to move from a reactive campaign logic to a continuous operating system.
When the customer base is too small to train reliable predictive models, or when a minimum CRM or basic transactional tracking is not in place. It is also not the right choice for those expecting retention results in under 4 months, or for those looking for a single tool (CDP, marketing automation tool) rather than an integrated system.
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Thirty minutes to understand whether your retention process is truly under control.