Creating & Leveraging the Closed Loop Part 2: Identify Your Most Valuable Customers

Written by Leapfrog Online
Published on Oct. 07, 2012

In Part 1 of our Closed Loop series, we discussed the need to create a closed loop model that optimizes conversions by having the data and customer experience from the initial ad unit/impression through the final action/sale. A strategy with more sales and highly engaged customers sounds great, right? Well, it is.  But, like all good things, it takes focus and time to truly make it work.  So let’s start.

As you probably guessed, it all starts—and ends—with an understanding of your customers. Who are your customers, what motivates them to action, and how do they want to engage with you? But most importantly, understanding who your most valuable customers are can truly focus and transform your approach.    It seems like a “no brainer” but for some companies, this is one of the hardest things for them to not only measure, but then to apply to their marketing efforts. 

To achieve this measure, it requires an analysis of your customers, or your client’s customers depending on your model, to understand who is really driving the business. Analyzing purchase data—what they are buying, how often and over what time frame. Analyzing behavioral data—where they are looking for your products, when are they looking and how often do they “kick the tires” before make a buying decision.  Demographic data—who are they (gender, income, age), where do they live, what are their interests. Some of this data can be gathered from your direct interactions through your consumer experience; some will likely need to be added from 3rd party data sources. No matter where you get it, it is this combination of data that will be used to guide who you want to target, where you should find them, what the customer experience should be and how much you want to invest in them to become a customer. 

Below is an oversimplified decision tree just to help dimension the approach.  The tree uses 4 data points, some existing and some self-reported by the consumer.  The outcome is a consumer score based on their predicted value--for simplicity sake in this example High/Medium/Low.

Though this post, we have now identified who we want to have as our customer.  In our next post, we will discuss how to find them efficiently, so your program can scale while staying within your financial parameters. 

Something we missed? Get in touch and let us know what you’d like us to cover in future posts!

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