When engaging your customers with email marketing, or any other media, it’s not just a matter of getting results; it’s about getting the right results. Having a way to define which responses are most important to achieving your objectives and then optimizing your campaigns based on their relative performance over time should be the cornerstone of any email marketing strategy.
This concept can be broken down into two parts. The first component, data capture, is the essential foundation upon which all optimization will take place. The second component, developing a standardized analysis framework, helps you choose which combination of responses results in a successful campaign.
Every marketer knows that to gauge the performance of a given email marketing campaign, it is important to capture relevant, insightful, and actionable data. This means tracking your campaigns beyond simple delivery statistics, such as the number of emails sent or opened. It also means tracking your campaigns beyond basic click-through statistics.
Too many marketers rely on click-through reports to determine the effectiveness of their campaigns; deep down, though, they know that click-through alone represents very little value to the performance of their marketing programs. Only conversion data — the tracking of each sale, download, registration, etc. — from a given campaign truly illustrates the return on a marketing investment.
Using conversion data as the foundation, marketers can then build a framework to weigh each potential conversion relative to one another. For example, an email marketing program may be trying to drive home-page visits as well as sales. If the first mailing generated 500 sales and 10,000 home-page visits, is it preferable to the second mailing, which generated 600 sales and 6,000 home-page visits? The answer depends on how the marketer values each response.
In such a scenario, we can safely assume that the marketer prefers sales to home-page visits, so the key is to build a framework that allows the marketer to choose which campaign had the preferred result. An effective way to choose the right results is to use an index in which each possible response action, or conversion, is given a relative weight. Once the marketer has formalized the tradeoff of the desired actions into a common unit, or index, he or she can calculate a “score” for each mailing.
For the example above, a sale may be given a weight of 1.00, while a home-page visit may be given a weight of 0.05. In that case, a sale is valued at 20 times that of a home-page visit. Using these weights, a marketer can then objectively evaluate the performance of the two mailings.
Multiplying the sum of each response type by the weight in the index, the first mailing would have a score of 1,000 (500 x 1.00 + 10,000 x 0.05 = 1,000), and the second mailing would have a score of 900 (600 x 1.00 + 6,000 x 0.05 = 900). Therefore, the first mailing outperformed the second mailing! It is preferable, in this case, to have 500 sales and 10,000 home-page visits rather than 600 sales and 6,000 home-page visits — an outcome that may have been more difficult to determine without an index.
At the end of the day, it’s about providing value to each one of your customers. Tracking which elements in your email marketing messages are driving your customers to respond and using an index to help quantify those responses can help you optimize your campaigns so that you’ll get more of what you want. And so will your customers.