The Click Through Quandary - A Closer Look at Key Email Metrics

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Email marketers rely on customers to tell us if we are doing a good job in delivering relevant content. We receive and interpret that customer feedback through email metrics. These metrics tell us if people are opening our email when they receive it,

what action they take after reviewing the content, and if our message has successfully prompted them to action. We then analyze the information provided to us by our metrics data and adjust our email program strategy--continuously fine tuning the process and gauging our success.

But are these metrics we rely on to guide us accurate? And just how reliable are the industry benchmarks we measure ourselves against? What do all these metrics truly speak to? To answer these questions we start by looking at the human behavior behind the metric.

The process looks something like this:
1. We produce and send an email.
2. The recipient checks and receives our email.
3. The recipient either opens or deletes the email.
4. If the recipient has chosen to open, their options are either to click a link or delete after viewing the content.
5. Finally, they either convert or leave our site.

Three key metrics relate to these behaviors--open, click through, and conversion rates.

Dissecting the open rate
The industry standard for measuring open rates is opens-to-emails delivered. Open rates speak to the quality of list, cleanliness of list, segmentation, brand loyalty, perceived value, subject line etc. This equation makes sense for the most part, since a cleaner list should equate to higher open percentages.

However, it assumes a constant cleaning cycle for your list. Those marketers who clean their list infrequently will see dramatic increases in open percentages after a list cleanse that is not supported by an increase in the

actual number of emails opened. This gain slowly decreases over time as the list grows, until the next cleanse takes place. Therefore, these percentages do not compare apples to apples when reviewed against one another. Take a look at the fluctuations in an actual case sample below.

Email 1: (Pre cleanse) 19.7% Open Rate. 11,342 Opens.
Email 2: (Post cleanse) 40.0% Open Rate. 11,007 Opens.
What appears to be a 20.3% increase in the open rate is actually a 2.9% decrease in the actual number of opens.

The click through quandary
But wait, it gets worse! Should your email recipient open your email, they will review the content and then choose to either click a link, or delete the email. The industry standard for

measuring this action (or lack thereof) is click thruoughs-to-emails delivered. What? Was I absent from class on click through equation day? How does the number of emails that get delivered speak to the content and message of my email?

The answer to how this equation developed can be found within the history of the Direct Marketing industry.

This equation was developed in the early days of technology- limited email marketing, when direct marketers were measuring direct mail response rates based on the number of orders against the total pieces they mailed. Direct marketers had no way to track how many people actually

opened and read their marketing piece. Technology quickly advanced to where we can now measure how many people open our emails, but the click through rate equation has failed to reflect these advancements.

A click through relates to the relevance of content, perceived value of the content, effectiveness of offers, sense of urgency, timeliness etc. Since someone who does not open your email cannot ‘vote’ on your content, why would we measure our click through rate against the number of emails delivered?

The result is that when you clean your list, your click through percentage increases dramatically, even if the actual number of clicks doesn’t change much at all. If we rely on this information, we make inaccurate determinations about the content of our email. Look at what happened in our actual case sample.

Email 1: 4.7% Click Through Rate. 2,685 Unique Clicks.
Email 2: 10.2% Click Through Rate. 2,795 Unique Clicks.
What appears to be a 5.5% increase in CTR is really only a 4% increase in the actual number of unique clicks.

The true measure of content is how many people click, measured against how many people actually see your content. Take a look at what happens in our actual case sample when we measure clicks-to-opens.

Email 1: 23.7% Click Through Rate. 11,342 Opens. 2,685 Clicks.
Email 2: 25.4% Click Through Rate. 11,007 Opens. 2,795 Clicks.
We see an increase of 1.7% in CTR based on how many people actually opened and reviewed the content of the email and then clicked. This is a much more accurate gauge of your content and message.

Conversions--this one must be easy!
Now that we are all scratching our heads in a state of confusion, we have to move on to calculating and analyzing the next step in recipient behavior--conversions. How do we calculate conversions to provide meaningful data? This is a scenario where you will want to look at two equations--conversions measured against opens and against clicks.

Conversions-to-opens is a good indicator of the actual value of your content and call to action to the people who reviewed your email. Conversions-to-clicks is an important gauge of the success of converting those who were prompted to action by your content and message. Both have value in their feedback to us as marketers. Let’s look at our actual case sample.

Email 1: 11,342 Opens. 85 Conversions. .75% conversion rate.
Email 1: 2685 Clicks. 85 Conversions. 3.2% conversion rate.
The first metric speaks to how well you convert those who viewed your message. The second speaks to how well you convert those who were prompted to action by your message.


How about those industry benchmarks?
The first problem is that only those benchmarks best segmented for your industry are remotely relevant. But what about the accuracy of those benchmarks? If you consider the problem

with the industry standard equations discussed above, add to that the varying list growth and cleansing strategies of the companies they measure, we can conclude that these benchmarks are

misleading at best. Since this is the only conceivable reason to calculate click through percentages using the industry standard equation, it completes the argument for moving to the new conversion rate calculation of click throughs-to-opens.

Take those pesky industry benchmarks, and file them in the cylindrical file. Create and set goals based on your own benchmarks over time, and strive to focus on what really does count--the experience of your email recipients!

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