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Engagement scores to predict customer retention

Part 3 on personalized marketing solutions that CDPs deliver

Most marketers have pretty much adopted the concept of lead scores to access where a prospect is in the funnel. They apply the score to marketing qualified leads in hopes of setting sales up for an easier close. And this market acceptance has really fueled innovation. The application of predictive scores in customer engagement and personalized marketing is still young and emerging but has BIG potential.

A lead score is easy when you are working with one system and simple workflows. Insight into opens, click-throughs, and attendees informs the adjustments you need to make. It also helps save costs when you cancel the campaigns that don’t convert. As more business applications are used to drive your customer journey, the help of CDP technology, like VIEWN’s platform, will be critical to innovating into the next phase with Engagement Scores and Retention Prediction Scores.

Digital marketing can more efficiently look at opens and bounces from a single view. Even if the customer journey is tied together from various apps, like email automation, webinars, CRMs, and POSs. Customer journey metrics in terms of usage and combined engagement scoring can provide deeper insights into how your customers interact with your brand, so drill down into what they are doing and how they want to interact.

Engagement scores can be used to understand better what is going on in a marketing funnel that seems to have many entryways, different speeding lanes, and a bunch of swirls before exiting. It weighs and measures the entryways and swirls from an individual’s perspective to gauge whether your customer has a good experience. Engagement scores can be applied to predictive algorithms and a weighted average of different interactions tied to campaign types. This approach is used to predict marketing qualified leads and factors that impact customer retention.

Use Case Example:

Engagement scores to predict customer retention

At VIEWN, we are using our customer data platform to build engagement scores that take in the bigger picture and that can consider the context of the customer journey in evaluating engagement health. Marketers need to be able to use the tools they have already invested in, and we honor that by connecting to any source. Our experience with predictive analytics, in particular, has us looking at combined engagement scores to try to understand what it takes for a customer to stay subscribed one more month.

In this business with over twenty-five thousand customers, the buyer and user are not necessarily the same person, and much consideration is taken before purchase. In the CDP, data is brought together with lead scores from their marketing automation system, attitudinal data on motivations and purchasing factors, customer support tickets, and product usage measures from existing customers. This data represents the measurable engagement along the customer lifecycle and gave us characteristics to start looking at what factors will get a customer to stay.

At the customer profile level, these engagement scores can be tied to customer retention efforts. For example, a support ticket that comes in just after purchase can change the engagement score and trigger the profile for level two service to keep the customer from canceling. The product marketing team put together campaigns and promotions to test what will keep good customers from churning out. Further, at the time of renewal, email nurturing about the product's continued value may make sense. We continue to test for factors that move the needle.

Engagement scores can take the lead score and apply it to both on-line and off-line events within the customer journey before purchase and can be used to begin predicting customer retention after purchase. With the onset of big data and artificial intelligence applied to CDPs, the engagement score is just emerging but can deliver value to marketing effectiveness.

In Part 4 of this series, CDPs add personalization to the Customer Journey, I return with other use cases that help marketers empathize with their customers and deliver better customer experiences.

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