I admit it. I’m a fanatic for metrics. Statistics — love them. Quantitative data — can’t live without it. Benchmarks — be still my heart. Especially when you’re talking about optimizing your email marketing efforts, quantitative measures are the only game in town.
So how can you determine if your open/click-through/growth/other rate is good, bad, or ugly? Read on and I’ll relate recent industry figures for common metrics; creative ways to determine the success or failure of your campaigns; and great sources for email marketing statistics.
Recent Industry Metrics
I love when people publish metrics. I actually save them in a spreadsheet format with details about the campaign (industry, list, offer, etc.) to help me with future benchmarks. So I thought it was only right to start off by giving you a few common benchmarks based on the data I’ve gathered. I’ve also included DoubleClick figures for some — see the table’s legend for more detail.
|Open Rates||Click-Through Rates||Acquisition: Website Visitors Opting in for E-mail|
|Modes (%)||39.0, 41.0, 45.0||8.0-8.9||5.0|
|Note: Very few sources differentiate between “total” and “unique” in regards to open rates and click-throughs, so it’s likely these figures include both types of numbers. It’s important to recognize the limitations of the data and factor it in when you’re using it as a benchmark.
These are not hard and fast rules for what you should expect — they’re just examples of what other folks out there are seeing. These are very general, since ClickZ has a broad audience, but you should look for data that’s relevant for your industry and program. Beware: Reported metrics are often for successful campaigns, so you can’t assume you’ll get these just by sending an email. They are goals to shoot for.
Getting Creative With the Numbers
The metrics above are commonly tracked and reported in an apples-to-apples kind of way (though the total vs. unique issue can be a confusing factor). But sometimes you’re looking for numbers that are less prevalent and may be tracked in different ways by different sources. There’s still a way to use them. Here’s one example.
One of my clients has a free email newsletter that he uses to upsell readers to his paid newsletter products. I went in search of data to use to evaluate his latest campaign, and here’s what I found:
- Rule of thumb (online publishing industry): Ten percent of your free email newsletter subscribers will convert to a paid product.
- Case study (online retail): Five percent of those who clicked on a link and visited the Web site bought a product.
- Industry average (online retail and catalog): 0.26 percent of email sent resulted in sales.
On the face of it, these figures are very different. They all come from different sources, are from different industries, and are reported in different ways. But a funny thing happened when I used each of them to evaluate the campaign in a logical way — the “expected response” for each was surprisingly similar. The high end of the range was only 25 percent greater than the low end.
What do I mean when I say I used the figures in a logical way? For the second and third metrics I used them in the way you’d expect — as a straight percentage of the total clicks/number sent, true to the situation from which we got the metric. Not so with the first. This is an old list, it’s been mailed to a lot and solicited to buy these products a lot, so I knew we had probably already skimmed the 10 percent of old names that would buy from the list. However, there were still new names on the list — so I applied the 10 percent rule just to the relatively new names on the list, the ones that hadn’t been exhausted yet.
This gave us a range of sales we feel is realistic for the upcoming mailing. This type of analysis combines art and science. You’re gathering all the hard facts you can (science), then interpreting them based on what you know (art) to come up with what many (including me) fondly call a guesstimate.
Gathering E-Mail Statistics
People tend to keep their email marketing metrics close to the vest. That makes it somewhat difficult to get quantitative figures for benchmarking. To address this, I decided to put all the metrics I ran across into a spreadsheet for future use, as I mentioned above. I include all the particulars I can: industry, company, date, offer, and so on.
Here are some of the best sources I’ve found for gathering this type of data:
- Personal experience. I’m lucky to work with clients in both the business-to-business (B2B) and business-to-consumer (B2C) realms, so just by noting the results and details of my work with them I’ve gathered quite a list. Don’t overlook your past campaigns; even if they bombed you can learn from them. And if you can gather statistics from colleagues, by all means do so!
- Case studies. These can be wonderful sources of metrics, and some of the best are available in Heidi Anderson’s E-Mail Marketing Case Studies columns for ClickZ. Other publications also publish case studies about email marketing and acquisition.
- Research reports. DoubleClick publishes quarterly “Email Trend Reports,” which are incredibly useful. The company makes the executive summary available for free on its Web site. A number of other organizations compile metrics, then sell the reports. Just be sure the data you’re buying is current. We’ve seen metrics shift significantly over the years, so the older the figures are, the less relevant they probably are.
I hope you found this helpful. Now that I’ve confessed to being a numbers-geek, I’m going to totally throw you a curve and talk about the other side of my personality next column — the part that loves working with creative folks (copywriters and designers) to implement the strategies I lay out for clients. It’ll go beyond the basics, exploring more advanced tips you can start using right away. Look for it next month.
Thanks for reading and as always, I’d love to know what you think about this column.
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