Optimise CLV through EM

Background

A scale-up company discovered that the cost of acquisition was too high to achieve the exponential growth rate projected in its plans for the coming years. One of the goals of the organisation is to become profitable within one European market.
What the company found was that despite its elaborate (rule-based) 1:1 communication journeys, they were unable to retain customer at rates high enough to justify the cost of acquisition.
The only way to accelerate growth was to revise its retention strategy and make it more customer centric.

Objective

1. Increase loyalty on the customer base
2. Increase the value of customers acquired

Approach

Our platform has the objective to increase CLV (customer lifetime value). Internal data sources like transaction -, product – and behavioural data are ingested and combined with our proprietary set of external data (eg. time -, weather -, demographic -, purchase based – and online trend data). This creates a 360-perspective on commercial performance, as well as user-level engagement.
Customers are clustered in (real)time using various complementary models and features.  We apply sequential-, survival-, similarity and propensity models to determine how and when most value can be generated from existing customers.

By applying Humai’s intelligence to all available data, individual customers were identified and passed to the organisation’s email platform on the most relevant date, time and product.
The time from start to the first campaign live was kept short thanks to standardized integrations with Marketing technologies, our proprietary external data set and the already present models within the platform.

The end result showed an increase in retention rate of the customers identified by us that received an email compared to a benchmark group of customers.