Release Content
In the newly added "Features" page, you can see a ranking display of how many customers have purchased or used products, product tags, and order tags. Filter with conditional segments to analyze the characteristics of customers in each segment 🔍
For example, you can quickly answer questions like, "Which products were most commonly purchased by customers in the Loyal Customer Segment on their first purchase?" or "What types of product categories are favored by customers who come through Instagram?" 🎉
For instance, by using this new feature analysis function, you can easily identify products popular among your store's loyal customers with just one click, and then create loyal customer segments based on their needs, such as:
- "Loyal customers who have purchased Product XX more than three times"
- "Loyal customers who have purchased Product YY more than three times"
Let's try creating these customer segments tailored to specific needs 💡
This feature is being released as a beta version. Please note that the detailed specifications may change in the future.
For a detailed guide on how to use this feature, please visit the following page 📚:
Background of the Release
Understanding what kind of loyal customers exist in a store is very important when considering strategies to improve Lifetime Value.
In ECPower, you can create loyal customer segments based on quantitative perspectives, such as "Total number of purchases: 5 or more" or "Total purchase amount: $500 or more." However, it was not possible to know the specific characteristics and needs of the people in these loyal customer segments.
Even if customers are classified as "loyal customers" based on quantitative criteria, they might actually have completely different needs.
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Until now, ECPower was unable to effectively analyze this aspect, and when we received inquiries from users, our only advice was to "look at the individual data of your loyal customers."
The task of inferring the characteristics of segments from this analysis relies heavily on the personal skills and experience of marketers. ECPower wanted to scientize this area, which led to the development of this feature.
We are very pleased to be able to release this feature functionality as a beta version!