Personalizing, even individualizing, customer experiences with predictive analytics is now the de facto marketing strategy in the race to stay competitive. However, predictive analytics tools are becoming more sophisticated every day. Machine learning and AI are making the science of using data to predict customer behavior more accurate and far-reaching than ever before. A trend that is only going to continue, at an accelerated pace. Marketers who do not keep up with the advances in predictive analytics are going to have a difficult time playing catch up.
Decoding Customer Buying Behavior
Predictive analytics, aided by machine learning and AI, helps marketers anticipate the buying habits of consumers by decoding past and present buying habits, thus giving greater insight into the customer, their needs and wants, and the ability to project future behavior. For example, if the goal is to increase wallet share, decoding a customer’s current behavior and buying habits can put you in the position to serve up messages based on that behavior and through machine learning perfect those messages over time, to the point where the customer believes you are individualizing the messages – “time to buy more toilet paper?”
Creating A Test and Learn Engine
Predictive analytics coupled with machine learning creates a test and learn engine that requires a fundamental re-architecting of a company’s marketing analytics processes. The definition of predictive analytics is as follows, “The practice of extracting information from existing data sets to determine patterns and predict outcomes and trends.” The goal then is to create a learning ecosystem that connects insights to outcomes as part of a continuous, self-improving cycle. It requires a commitment to iteration, not an absolute success or failure mind-set.
Anytime you use the past to predict what is going to happen tomorrow or the next day, you need to adjust your success metrics. Learning is success. Continuous learning brings greater understanding and great understanding leads to more and more success, over time.
Successfully Using Predictive Analytics Requires Focused Thinking and Modeling
The insights gained from the use of predictive analytics are only as good as the thinking and modeling that the analysis is based on. Like all data analysis this adage still holds – garbage in, garbage out.
Successful use of predictive analytics demands several actions from marketing.
- Be clear about your business objectives
- Determine your personalization strategy or approach
- Make a clear decision as to what it is you need to know about the customer
- Define your model by integrating data discovery and decision making.
- Data discovery is about sourcing and combining traditional and behavioral data to uncover meaningful insights about customers (such as their preferences, interests, and needs.)
- Automated decision makingis driven by the advanced analytics models that produce propensity scores for each customer or prospect. These scores define the probability of an individual responding to a specific offer or engaging with specific content.
- Content distribution is the final step.A good system will use customer and prospect scores to trigger personalized ads and landing pages, and to distribute specific content, offers, or experiences across channels.
To find out how to implement personalization at scale using predictive analytics download our latest eBook, How to Implement Personalization Across All Customer Touchpoints.
About VeraCentra: Marketers everywhere want to use data to implement more modern customer engagement strategies. But there can be many obstacles standing in the way of success. That’s where we come in. VeraCentra provides easy-access Customer Data Hubs. We represent best of breed Cross Channel Engagement Platforms (so marketers get the right fit) and offer the Marketing and Data Services that guarantee speed to value and quick win ROI from technology investments. We deliver these solutions with an unmatched wholehearted approach bringing personalized support, care, and service to every client. That’s why many of our client relationships span more than a decade.