AI Enabled Customer Segmentation Will Transform Marketing
Executive Summary of a Forthcoming Study from Forrester Consulting1
Marketers are missing opportunities when they use static segmentation, which is not predictive of customer behavior and fails to take customer context into account. In order to deliver the right message to the right customer at the right time, organizations must adopt dynamic predictive segmentation. By doing so, marketing executives will be able to serve relevant content to their customers in real time and capitalize on their understanding of the key drivers of customer behavior. Those that do not provide contextual interactions in the moment face an existential threat.
A soon to be released simMachines-commissioned study conducted by Forrester Consulting demonstrates clear, unequivocal and unanimous recognition among decision-makers responsible for program execution or campaign planning that the current state of customer segmentation fails to deliver on many fronts. In fact, 98% of surveyed marketers agree that they face challenges with static segmentation, including: lack of precision, failure to provide actionable detail, and unresponsiveness to changing customer behaviors.2
Current State Segmentation Is No Longer Adequate
- Segments fail to provide enough actionable detail
- Segments aren’t updated based on changing customer behaviors
- Segments lack precision / are too undifferentiated
- Unable to tailor messages to specific groups
- Unable to serve customers in real time
- Doesn’t take customer context into account
Yet Customer Segmentation Matters More than Ever
However, customer segmentation matters more than ever. Today’s digitally-empowered customers have high expectations for customer experience. Every time they come across an improved experience, they expect and demand it for all interactions to follow. All the more so, marketers need to up their game with improved intimacy and relevance across interactions. To deliver on this, marketers should rely on segmentation to understand and deliver on customer needs.i
Dynamic Predictive Segmentation Moves at the Speed of the Customer
AI enabled dynamic predictive segmentation solves the current state segmentation challenges marketers must overcome. Dynamic predictive segmentation is a new and different approach that accurately segments customers based on propensities to take a specific action, grouped by the most important shared predictive characteristics identified for each segment. Segments and their associated characteristics change dynamically in real-time based on new data from customer interactions. Advances in machine learning have made this a reality that represents a significant new level of relevancy in every customer interaction.
100% of firms agree that not adopting dynamic predictive segmentation is risky.
Dynamic predictive segmentation solves challenges and changes the game for marketers in improving relevancy in the moment at great speed, granularity, and efficiency. Accomplishing this requires explainable AI methods that can reveal the key factors that define predictive customer segments.
Stay tuned for the full study!
1 Capture The Customer Moment With Dynamic Predictive Segmentation, a November 2017 commissioned study conducted by Forrester Consulting on behalf of simMachines.
2 Capture The Customer Moment With Dynamic Predictive Segmentation, a November 2017 commissioned study conducted by Forrester Consulting on behalf of simMachines.
i Learn more about Segmentation in Q&A: The Secrets Of Successful Segmentation Revealed, a March 2017 Forrester Research Report
