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Data recency is one of the important indicators of the RFM model. Let me simplify it further, today most of the database marketing industry’s experts rely on a classic direct marketing response model called RFM. The RFM model is composed of three indicators namely recency, frequency and monetary. Each indicator depicts the online behavior pattern of the existing as well as the potential customer. But let’s focus on the significance of the recency in data usage.
Thankfully, the new technologies like analytic tools are assisting us to track our customer’s online behavior, like their interval between recent visits, number of times they visited and many more. However, these tools help us assign recency score based on their recent visit or the time interval of a recent purchase made. For instance, check with google analytics tool.
Here the tool assigns ‘0 days’ for the new users who visit for the first time and even if they visit again on the same day. By including only the segment of multi-session visitors, the executives can filter out new users. Whereas in the case of Adobe analytics tool, new users or the first time visitors are filtered out. Here is a google analytics report that depicts the customer visits for a month.
In the case of re-targeted marketing campaigns, data recency of potential customers plays a crucial role. Here, knowing the recency of potential customers helps marketers to identify the position of customers in their purchase journey. Perhaps it helps in achieving the best marketing strategies with more number of clicks, shares, and sales.
Business marketers can follow the below-mentioned steps to design a remarketed marketing campaign based on customer recency:
Often B2B marketers make an effort to analyze their existing customer to cross-sell their products or services for larger audiences. Here customer recency offers vital information that helps them to analyze their customer interests. By identifying their journey length, marketers can design effective marketing strategies for beneficial business results. However, in future upcoming technologies will help marketers to predict the future of sales.
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