Predictive analytics is the key advantage that Customer Data Platforms (CDPs) have over other data platforms.
In addition to the 360-degree data available about customers, predictive analytics goes deeper to gain customer insights about what is likely to happen based on past trends.
Why Use Predictive Analytics?
Predictive customer analytics deals with real data to providing the closest possible answer to your questions about future behavior.
Most companies have access to volumes of data, but have no idea about how to organize it, what to do with it, or how to leverage it across functional departments. This lack of direction can contribute to disjointed customer experiences and a lack of customer retention.
Which Kinds of Companies Can Benefit From Predictive Analytics?
Predictive analytics leverages historical data to predict what an individual customer is most likely to do and recommend the best way to intact with that customer.
In order for this model to be accurate, you need a significant amount of reliable data.
So, if you don't have enough data, or the data contains anomalies, then you are likely to also discover inaccuracies in your model and predictions.
However, if you have 6 months of historical customer data, or roughly 1 thousand purchases per month, you will be able to reliably use predictive analytics to improve your business. Accessibility to predictive analytics is no longer reserved for large enterprises alone.
Of course, the more data you have, the better the insights you can uncover.
Predictive customer analytics is flexible enough to allow for any specification parameters, since every company has on its own unique combination of Key Performance Indicators and internal operating processes. You're really only limited by your imagination.
Machine Learning Predictive Capabilities
Many CDPs like Evinent Analytics have artificial intelligence and machine learning built into them to provide deeper customer insights that can unleash and create new possibilities for your business.
As the amount of incoming data grows, so does the complexity of the model. CDPs can influence customer behavior across all channels and create intelligent reports based on customer activity.
Machine Learning helps generate, evaluate, and reveal relationships between data sets to deliver intelligent recommendations and allow deeper understanding of customer patterns.
Predict Future Client Actions
With the power of predictive models capable of identifying patterns based on collected data, businesses can influence customer decisions in the future instead of reacting to past behaviors.
Predict Customer Lifetime Value
In terms of long-term strategy, predictive analytics can help you identify your most loyal customers through the Customer Lifetime Value calculation tool.
By using historical customer data as a predictive tool, companies can generate continuous, profitable growth opportunities grounded in real-time analysis.