To thrive, B2C enterprises need to predict the future using a blend of proprietary and private data.
Predictive AI Helps B2C Enterprises Take Actionable Next Steps
Connecting the dots and analyzing those data points can give marketers and other stakeholders insights into metrics such as churn, customer lifetime spend and customer lifetime value—and give them predictions that help them identify the correct next steps.
There are two types of predictive AI solutions available today. The first type consists of vertical solutions, which focus on niche problems, such as marketing automation. Data must be loaded into a required schema so the system can ingest it and help solve a given problem in a preset manner. Because the data is hard-coded in the solution, this is often a rigid process that can be difficult to tailor to unique needs.
Here’s the typical life cycle of horizontal AI solutions: Data scientists define a problem, examine the build features, create an initial model based on those build features and then start getting predictions. Over the lifecycle of such a model, data scientists routinely test new features, experimenting to make gradual, incremental improvements over time.
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