How to Predict and React to Your Customers’ Changing Needs: Quick 3-Step Guide
As a marketer, it’s not enough to simply understand your customers – you need to predict their changing needs. According to Forrester, “firms will experience 25% to 50% increases in revenue risk as more customers operate as free agents.” The troubling reality is, it’s all too easy for customers to pick up their business and take it elsewhere.
So, how do you stay ahead of your customers and gain insights to build strong relationships that will last a lifetime? Let analytics do the heavy lifting for you.
Identify and reveal impactful customer behaviors, as well as key changes in behavior, which will allow you to target customers effectively. Follow these three steps to anticipate and react to your customers’ changing needs:
Step #1: Reveal what’s important
Predictive models and AI/cognitive capabilities sift through mountains of data, spotting patterns in customer behaviors and what they might lead to in the future. Standard metrics like open rates and ad clicks are useful, but they’ll only get you so far. 85% of customer analytics projects help companies access data, but don’t achieve any ROI.
When companies use data from static monthly reports, they’re leaving the majority of the benefits from analytics on the table. Using predictive indicators to drive decision-making is the key to improving ROI. To gain insight into how your customers are predicted to behave in the future, think about metrics like likelihood to churn or lifetime value of a customer. How engaged are your customers with your brand, and how is this predicted to change over time? These kinds of metrics look forward, not backward. While it’s good to understand how things were in the past, it’s much more effective to target based on what’s predicted to happen in the future.
Step #2: Understand why
Once you know the important insights into how your customers think and behave, you need to know why. Say you have a group of customers who are predicted to churn. The question to ask is, why? What are the behaviors associated with these customers that are causing them to fall into this category? It could be something like cart abandonment. Or it could be a deeper, behavioral issue. For example, maybe they just got married and no longer have the same purchasing habits. After you understand these bits of information, you’re ready to build a campaign. Using a combination of predictive and behavioral attributes, you can create campaigns that hone in on a specific persona. If you can build a persona based around these insights and predictors, you’ll have a much better sense of how to target them effectively.
Step #3: Act
Now that you have a campaign in mind, it’s time to act. Pull together the group of customers who you identified that will fit your campaign and pull the trigger. Hooking up your campaign management system to a smart segmentation tool is the key to creating a seamless, campaign execution system.
If you’re interested in learning more about predictive analytics, check out IBM Watson Marketing Insights.
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August 29, 2017 at 09:03AM