Analyzing e-mail isn’t as simple as learning open and click-through rates. There’s a lot of information beyond those basic metrics that tell us a great deal about how we can more effectively use e-mail.
Most analytics programs (and some e-mail vendors) allow e-mail to be tagged. Typically, this occurs in some form of a hierarchy, but sometimes it occurs via simpler metadata tagging. While every organization espouses its own best practices on tagging e-mail, I usually find tagging structures don’t answer the specific business questions I (and my clients) are asking. To be fair, each industry has its own business needs.
Our clients tend to be multichannel retailers (B2B and B2C). In this column, I’ll discuss how we tend to categorize e-mail for this industry. Of course, the actual tagging and hierarchies we use are tailored to specific clients and are confidential. But below is the high-level starting point for most of our clients.
We divide e-mail into major categories. The two we typically come across with all of our clients are campaign and triggered e-mail.
These are traditional marketing messages, such as a Christmas sale, a back-to-school sale, or Valentine’s Day specials. Weekly specials could also fall into this category. Campaign e-mail has the following characteristics:
- It’s created by the marketing department.
- It’s time or event based. The time might be Christmas. The event might be a new store opening or an end-of-the-season sale. Either way, campaigns are not generic, they’re celebrating something specific.
- It may or may not be personalized
- A simple campaign might consist of only one message. A more complicated campaign includes several e-mail messages (“drops”) that arrive on different days.
- Each e-mail drop might actually consist of different test versions of that message.
The business questions we want our analytics package to answer include:
- How are our campaigns performing in general?
- How is the specific campaign (e.g., “Valentine’s Sale”) doing?
- If this campaign had multiple drops, are there patterns we can see in how each drop performed?
- Within each drop, which test messages worked best?
- If we used various types of promotions (e.g., “Free Shipping” vs. “10% off”), which are most effective overall?
Triggered e-mail is automatically generated by the system. It includes both merchandising and back-end messages. Triggered e-mail has the following characteristics:
- It’s automatically generated based on a user’s action.
- It can be (and should be) highly personalized, based on what the user was doing on the Web site.
- It usually contains some sort of promotion or recommended product listing.
- It’s not time or event specific (as campaign e-mail is).
Examples of triggered e-mail include:
- Registration thank you
- Order receipt (and cross-sell items)
- Notice of items still in the shopping cart
- Product suggestions within the category the recipient was browsing
- More information about viewed products
There are endless possibilities for these types of messages. As I’ve mentioned previously, these messages can be extremely profitable if well implemented.
Business questions we want to ask about triggered e-mail include:
- How effective is triggered e-mail in general?
- Which type of triggered e-mail performs best (e.g., abandoned cart e-mail, cross-sells after checkout, etc.)?
- What offer types are most effective in these e-mail messages (product links, category links, coupons, etc.)?
Setting Up the Hierarchies
Each analytics package organizes reporting in different ways. It should be clear from the structure of the above business questions, though, how you should effectively tag your e-mail messages.
Once systems are set up with these tags, you can watch the numbers and get a much higher level view of how e-mail marketing is performing. It’s important to see how campaign e-mail performs against triggered e-mail. Some packages let you input how expensive an e-mail was to send. In packages that afford you that capability, don’t just look at performance; examine net profit too. Campaign e-mail, for example, is typically more expensive to create because it involves the marketing and graphics departments. Triggered e-mail, on the other hand, is designed once, then filled in automatically by the system. Of course, that system costs money to build, and that cost must be amortized.
Although this column may seem like an e-mail primer to some, many advanced and successful companies still report on each e-mail individually or don’t differentiate between campaign and triggered e-mail. Because they look too closely at each message and haven’t organized their tagging with high-level business questions in mind, they don’t have a clear picture of the e-mail marketing landscape. These categories (and business questions) are only the beginning of what a real tagging structure should look like. But it should be a good starting point for you to reassess how you think about e-mail marketing reporting.
Thoughts, comments? Let me know.
Until next time…
Marketers need to know what’s in their data and trim out the filler to provide continuous, data-driven ROI for their brands.
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