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How Much Is An Email Address Worth To Your Business?

by David Baker

On the surface of it, measuring the value of email marketing is simple: 1,000 emails go out, 995 were delivered, 300 unique people viewed the message in HTML, 100 clicked on one of more links, and 30 purchased something. Anyone can make sense of this logic. Thus, based on a causal relationship to direct response, anyone can demonstrate the value of the email channel to a business.

However, few people in our space have found a formula that represents the true or implied value of an email address to a business. This is why many will ask, "how should I build an email database?" I've written a few articles on this concept of the value of an email address and talked with a great many others who struggle with this type of valuation.

We developed a survey at EEC on this exact subject (access it here). I even spoke on this at the Email Insider Summit. At this point, there are only a few instances where the email channel can be isolated and a valuation can be put on the channel. On is an ROI calculation and another is creating a proxy to understand the incremental value to a customer.

If I asked you to scrap everything you are doing with email and start fresh, how would you budget for your channel? How would you justify it when you have NO email addresse? How would you dissect your media budgets to understand their influence on sales and the relationship value email will bring to that? I know many of you would struggle with this especially if there isn't a causal transactional event.

Fortunately, I can help you make some useful calculations. Here are some areas to consider:

1. Wherever there is a finite comparison of cost savings (efficiencies gained through the use of the channel). An easy area to isolate is where you are replacing print or fulfillment costs with the distribution costs of email. This is a direct cost savings, yet also has a value that isn't as finite as costs - the value of efficiencies gained in being real-time in the fulfillment function- good customer experience.

2. Wherever there is a finite transactional event tied to email. This is the easiest to calculate as you have a direct response link to conversion.. You know which emails went out to whom and whether they bought something. The challenge is, attribution modeling. What credit do media, search and the site get in this conversion? Should it all go to the email channel? For instance: a consumer receives an email and goes to the site but doesn't buy; but then they go back the next day and buy. How do you attribute the revenue? Let's say you track the customer's activity through site side cookies, so you know they were exposed to two ads in that time span and four support pages on the site, plus they opened and clicked through from the email and potentially accessed search and came to another part of the site in that time. Who gets credit for the sale, and what attribution should be given to media's influence and the site's influence on the sale?

3. Taking this a step further is creating a proxy that is an extension of lifetime value. So you are predicting the future profit value of a consumer based on today's dollars. Each consumer would seem to have a similar value based on their affinity to purchase, how often and at what discounts, right? But do they? What if they are engaged with you through many channels, such as web, media, search, email, on-premise, and catalog?

The challenge is to understand how the consumer is influenced by each and to create a proxy that helps you understand which channels offer the most influence and efficiency in creating and sustaining loyal customers. This can get quite difficult to calculate since an average customer email file loses 2.4% of its database each month. This is more difficult as you have to consider response rate, time on file, and of course this can't be done across every segment, rather a finite segment. This calculation takes into account RFM considerations and looks at the relationship between response through the channel and RFM to see if increased response and time on file has positive or negative effects lifetime value.

In order to calculate these somewhat accurately, you must try to solve the following:

  • Which customer groups are most important to run this calculation against (high value and low value segments, invest segments)?
  • Do these segments differ in their use of channels (do your highest value customers use channels the same way, or are there email biases within some segments)?
  • How do you factor increased response vs. infrequent response? Is there more value in a higher responder through email vs. someone who responds every other month/week?
  • How do you factor domain conditions in the response? While each ISP filters and blocks images differently, does this impact the value of an email consumer and your ability to get your message through, received and counted as a measured interaction?

Many try to answer these questions; few have the resources to do it. I sit on many councils and committees and I will say no one has a cookie-cutter method of putting this together. What I will tell you is this. If you aren't trying to find some kind proxy for your email channel in terms of valuation and you aren't trying to help with attribution modeling (all media's influence and value in the sales process), you'll be relegated to campaign work, never have the resources for testing and learning, and you will struggle to work closely with all interactive elements of your offering (site, media, email, search). Someone has to start the dialog!

Source: WhiteNoise

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