Not sure how to start integrating AI into your email marketing strategy? Learn how to transform your customer lifecycle with predictive analytics.
Watch our YouTube video from our chat with RedEye’s Database and Multi-channel Manager James about predictive analytics, how they work and why you should use them in your email marketing strategy.
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Our definition of predictive analytics tools is that they are for ‘understanding your customer’s behaviours, so you can predict their next action, enabling you to target the right customers with the appropriate message.’
Often our predictive models have begin by helping a client of ours with an issue they are facing whether that be them wanting more customers in their VIP segment, reducing their customer churn rate, or converting more prospects into paying customers.
James takes us through how a predictive model works, from starting with the marketing challenge faced and then analysing historical data to look for patterns to find customers who follow similar behaviours.
This helps us target the same groups of people and then send them personalised campaigns when they reach certain criteria to help achieve our goal.
Overall they enable marketers to work smarter, give customers a better experience and most importantly, drive more revenue, a no-brainer right?
RedEye’s Marketing Director Rachael and James also discuss the top pain points we hear from marketers often stopping them from using predictive models and how you can get around these.
Mainly focused on misinterpretations around how much data is needed, James explains how most of the time these are easy to solve and how each model needs varying degrees of historical data, meaning some can be utilised pretty quickly.
With our host of predictive models available, in the video Rachael breaks down which is the most popular, the easiest to get started with, the most underrated, most critical to use and the most valuable, so depending on where you need support there will be a model best suited and can drive results.
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