Drilling Down And Refining Behavioral Segments

The customer segments defined in the “RFM grid-based segmentation to ensure the healthy retail business“ are pre-defined in the Enalito. Any retailer with Enalito can find all of these customer segments ready to give insights into their business. However, Enalito cares much more for your business than you think. Enalito aims at finding out and resolving every ‘What If’ that comes in a retailer’s mind. So, what if retailers want to dig deeper and find some other customer segment that can provide more clarity in their business insights? Enalito has already worked it up and gives the complete freedom to drill down and refine behavioral segments as furnished as retailers want to get a satisfactory answer to their each and every What if.

Let’s understand this by an example:

There’s a retailer who sells exquisite and popular wines on his online store. He uses Enalito to analyze the customer segments (as well as product clusters) to get detailed insights into his business and sends campaigns to his customers that turn up often and buy more from his store. The retailer figures out that the ‘Defected’ segment in the RF (Recency-Frequency) Grid needs to be more refined, as it shows the customers who haven’t bought recently and haven’t bought often either. As the retailer is a seller of wine, many of his customers don’t purchase much or often but whenever they purchase, they contribute well in the monetary terms. So for his business, the customers who haven’t bought recently and frequently can’t be said ‘Defected’ if they are providing a good monetary contribution.

In such a case and in any other need of drilling down the pre-defined customer segments, Enalito provides the retailer with the provision of refining segments on their own. For the above example, the retailer can introduce an additional attribute M (Monetary Value) to the pre-existing RF-based Defected customer segment. By doing so, the retailer can set up a condition to filter out only those customers as defected who also haven’t provided any monetary contribution in addition to the already low recency and frequency. The retailer can set up the condition as segmenting those customers as defected who have the M score as M<=3 (where M is lesser than or equal to 3). After setting this condition, the retailer will yield a segment of customers who haven’t bought recently and frequently, and also haven’t contributed significant monetary value.

Similarly, the retailer can also figure out customers who might have not bought recently or frequently but have contributed good money. To do this, the retailer can add up the monetary (M) attribute to the RF-based segment and set up the condition of M>=3 (where M is greater than or equal to 3). This way, the retailer can yield a customer segment that isn’t Defected when the monetary value is good.

The retailer can even drill the ‘VIP’ customer segment to get the customers who have the best recency, frequency, and monetary value to find those customers who are VIP in terms of monetary contribution (M>=3). Similarly, the retailer can go the other way around to find those customers who have the best recency and frequency but not the best monetary value (M<=3).

From the above example, it is clear how to add an additional attribute to a pre-defined segment and make it more refined. Using Enalito, the retailers get the freedom to add as many attributes they need to make their customer segments as refined as they want them to be.

Likewise, any retailer can drill and refine any customer segments as per their needs and make the best of the already best Enalito. 

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