Dynamic Attributes of Smart Marketing

 

 

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Attribution is a heavy topic in a world where information access and customer interaction happen anywhere, anytime. Where marketing is becoming a connected web of communications and calls-to-action (CTAs) designed to immerse the customer with a 360-degree experience and a guided journey. In such a world, how can you attribute customer actions to a specific marketing activity that stimulated that action?

It’s no surprise that there are plenty of new products and claims focused on attribution. Unfortunately, it’s easy to invest a ton without getting clear results. In fact, it’s probably not that relevant any more, or at least we need a new way of looking at it.

Let’s say you mail coupons or a catalog to customers. You also email them regularly with offers; you run ongoing search advertising campaigns; and you are active on social networks. Then one day a customer places a $100 order on your e-commerce site. What was the contribution of any one thing? Should you apply rules based on your understanding of how customers think and behave, or look into the latest data science or machine learning platforms?

If you’re considering either reliability or cost, you could simply attribute the full $100 to the last communication sent or the last action taken by the customer just before the purchase. But what if the last email triggered the customer to look at the catalog from weeks ago, which prompted a search for competitors where he saw your ad, but was ultimately swayed by an online review? Some credit ought to go to the email that started this journey, but the customer never clicked through the CTA in that email.

What gets the credit? It’s an attributive mess.

Face it, customers’ engagement with your company will be increasingly blurred across channels, campaigns, messages, content, and networks of all types, so that it’s hardly relevant or meaningful to get too specific about attribution.  Except for one little problem — marketing budgets have to be allocated on some basis of ROI.

Maybe a different approach is needed. Instead of trying to accurately attribute value to each campaign source or channel, which are all a blur, maybe it’s better to focus on how your marketing mix is changing customer value. This idea starts with the premise that there is no more important measure of your marketing success than getting people to purchase more of your products and services. So instead of getting too hung up on the response rate (e.g., click-through) of a particular communication, measure changes in customer purchasing against the total “experience” you are throwing at them.

The simplest thing to do is break the problem down to simple and familiar A/B testing. A/B testing doesn’t scale if you look at everything as a variable, and you can’t control all the variables involved in customer engagement. Instead, consider the dynamism of the entire experience you project to your customers as a constant. Then change just one thing in that entire experience, the one thing you are testing.

For example, add personalized product recommendations to each email to a randomly selected group of customers. Then compare the amount of buying by the customers getting personalized product recommendations with the group getting the “business-as-usual” experience. Then you’ll have an idea how effective the personalization was.

Of course, since there are many things going in terms of the customer experience and in the marketplace; one test by itself should not be relied upon completely. It’s important to conduct several tests over different time periods. If you see relatively consistent positive results, you know you’ve made a difference for the better.

Peter Moloney is CEO of Loyalty Builders, whose Marketing Lift Service offers a automated, cloud-based predictive analytics enabling marketers to get revenue lift from more relevant communications to their customers.

 

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