June 27, 2022
Join MOJO-CX©'s Senior Solutions Consultant, Paul Banks, for a chat with John Devlin
In today’s digital age companies need to harness their consumer data effectively to create and protect customer value. One increasingly common approach to do so is the use of next best action modelling to drive personalised marketing. Companies that use this type of modelling will predict what the best thing for an individual customer might be, spanning the gamut of potential possibilities—product, action, non-action—all whilst accounting for the customer’s browsing or purchase behaviour.
If it sounds complicated, that’s because it is often notoriously complex, which makes NBA a difficult thing to get right even for large companies with many resources at their disposal.
MOJO-CX© specialises in increasing customer lifetime value using data-driven marketing, so NBA algorithms and marketing campaigns are a common delivery for our consultants. They often demonstrate that the companies that can nail the right approach—which usually blends clever data modelling and machine learning with bespoke marketing—consistently reap more value from their customers.
A FTSE 250 insurer had recently expanded their product portfolio and invested in a NBA algorithm to embed the new products into the market. Ultimately, the insurer wanted to reduce churn and increase market share to maximise customer lifetime value. Insurance is an industry with relatively low margins since there is often little direct control over price, so once a customer is acquired, even on a low price, it was cost effective for the insurer to cross-sell products where appropriate.
Unfortunately for our client, they went to a big four consultancy firm to build out the solution and after 16 months, had no clear indication of the benefit in terms of ROI versus statistically efficient control groups.
Our work was clear cut. Our client was 16 months overdue on delivering value to the bottom line so we had to identify both the issue, solution and build a quality alternative, quickly.
We split our work into the following streams and spent the next 8 weeks building and deploying:
A whopping £750k in incremental revenue for the insurer; and, since we deployed very quickly our client was able to reap these benefits in year. Outer year benefits are still being realised!
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