2D Trend represents the trend analysis of two KPIs at a time to get insights about the business performance for a selected time duration. Primarily, the KPIs often considered for getting 2D Trend are a combination of RFM attributes. Like, the 2D trend analysis is done for a customer, segment, product or cluster on the basis of evaluating RF, RM, and FM values for the selected time period.
Let’s suppose a customer segment is chosen to yield its 2D Trend of purchase behavior on the basis of RM (Recency-Monetary) Analysis. The aim is to find the last 12-month trend, which provides the month by month values in the graph. Enalito runs its analytical check and breaks down the customers of selected segment as per their purchase frequency and purchase monetary values for the last 12 months.
The purchase recency and purchase monetary of each customer of the segment are labeled as low, neutral or high as per the performance of the customer for the selected duration. This way, the customers of the segment whose recency in days has increased will be labeled as Low (as high recency value is not good for the business), whose purchase recency has remained neutral will be labeled neutral and whose purchase recency has decreased will be labeled high. The same way customers with low, neutral and high purchase monetary values will be labeled likewise (however, increased monetary value is good for the business while decreased monetary value is bad).
After labeling the customers as low, neutral and high performing for the respective purchase recency and purchase monetary attributes, the customers are then categorized to find out the bad, very bad, neutral, good and very good customers in comparison to the previous and current standing of the customers.
Enalito with its analytical genius finds out all the customers who are very good to very bad for the past 12-months (or any duration selected). It is figured out by pairing the low, neutral and high status of customers derived from purchase recency with that of the purchase monetary respectively. The customers who have low purchase recency, as well as low purchase monetary, are considered as very bad performing ones. All types of customers derived from the Purchase recency and purchase monetary are classified on the basis of their performance this way:
|Last 12 Month Purchase Recency|
|Last 12 Month Purchase Monetary|
After figuring out the weightage from Recency and Monetary ratings of customers, the true status of customers (or products) is recognized as good, very good, bad, very bad and neutral customers. Based on the differing low, neutral and high scoring of purchase recency and purchase monetary for different customers, all types of customers are figured out. By 2D Trend analysis, retailers find the very bad to very good customers and can uplift them in a way they want.
Just the way customers are figured through 2D Trend for RM segmentation, similarly, it can be done for RF and FM segments too. Additionally, 2D trends not only categorize the customers only but products too.
Enalito presents the 1D and 2D trend for customer segments and product clusters by handling profound technological solutions at the back end and produces results that are productive and profitable for business units.
Now as we’ve understood the meaning and workability of 1D and 2D Trends, now it’s time that we know about the business view provided from the analysis of 6 significant KPIs.