DIY CRM Tip: Uncover Customer-Value Segments
Here’s one way you can turn data into a smart customer experience (with three more to download)
Leveraging customer data to generate insights is not an easy task for any department in any type of business. Especially generating the kind of insights that lead to more effective customer marketing.
Having the right resources and technological know-how, though, is key to helping your team discover new ways to improve the customer experience.
A few weeks ago, we showed you how to use your customers’ first purchase category as a predictor of longevity. Today, we will show you how combining longevity with the time since your customers’ last order can uncover meaningful customer value segments.
It’s even more simple than it might sound 🙂 Read on to discover the simplicity of it or go ahead and download all four ways to leverage your data here.
By clustering customers based on multiple attributes, retailers can provide more relevant and personalized offers to their very different customer segments. Although most retailers cluster customers using attributes such as preferred category or recently purchased product, other more advanced options exist. One such example is combining two or more attributes that indicate your customers’ relationships with your brand.
Using Optimove, a retailer clustered its customers based on longevity (amount of time elapsed since their first purchase) and recency (time since their last order) to create a two-dimensional analysis of each customer’s predicted future value.
The analysis revealed four value tiers, as seen in the following chart:
Note how all value tiers include both veteran and recent customers, which means this analysis cuts between the different longevity of the customer, i.e., across the whole customer base and not only a subset of them. Perhaps a surprising insight that can help turn your data to action.
The retailer used this analysis to communicate differently with customers in each value tier. For example, it often makes sense to incentivize customers with lower predicted future value by sending out more generous offers and discounts, to motivate them to purchase. But this shouldn’t always be the case.
Using Optimove, the retailer set up dynamic segments that populate when customers meet the criteria of each of the value segments. And they set a monthly recurring campaign to be sent at the beginning of each month.
See the flowchart below for a general example:
From Data to Insight to Action
This is but one example of how retailers can leverage data to generate insights that lead to more effective and personalized customer marketing, improving the overall customer experience.
There are plenty of additional ways to leverage customer data to create personalized customer marketing campaigns that suit your specific brand’s needs at hand.