Transportation & Logistics
Case StudyNeopost

Neopost identifies customers at risk of churn with machine learning using PredicSis

Neopost has centralised all customer data and implemented PredicSis (a plug-n-play service available through Amazon Web Services) to generate lists of customers at risk of churn.

Context

"Neopost is the number two global provider of mailing solutions and a major player in digital communications and shipping solutions.... the Neopost marketing team was looking to improve its retention initiatives. Current processes did not leverage the data and rather left the sales team struggling to fight churn, making decisions based purely on personal judgment. Predictive scoring was identified by top management as a way to maximise customer retention by detecting fragile customer relationships and providing the means to take appropriate retention initiatives."

The Project

Neopost''s "front line marketing team used PredicSis.ai to generate targeted lists of at risk customers, which the Neopost sales team was then able to rapidly act upon to implement sales-led retention activities and ultimately reduce churn".

Data

Neopost users were set up and able to run predictive analysis on large numbers of tables from multiple data sources - from customer data, to digital data and invoices.

Results

Results undisclosed

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