All too often, pharma marketers are woo'd by vanity metrics that don't offer the full story on marketing campaign performance. Is a "like" worth more than a share? A retweet more important than a mention? In a recent article on MediaPost, April Mullen writes about the value of a click and its relationship to other performance metrics. DMD published a similar article on email marketing metrics, Emerging Trends in Healthcare Marketing, in April 2015.
The awesome part of being in the digital age is that every interaction leaves a trail of data exhaust. This can be a double-edged sword, though. For example, there’s currently an ongoing debate happening in the field of journalism that applies to our efforts in marketing. The question is whether clicks prove the value and acceptance of content.
The issue is that clicks don’t necessarily mean the content is hitting the mark. Are the clickers actually reading the content? Are they doing what the journalist intended when spending countless hours working on the piece?
I can’t help but wonder if we as marketers are sometimes falling into the same trap of not reading the metrics in the right light and assuming a click means engagement — particularly positive engagement.
So, how are we to think about clicks? We start by looking at the most common click metrics that email marketers typically use to evaluate campaigns:
1. What percentage of recipients clicked?
Unique Click Rate – (Clicks rolled up by email address/ delivered) This ratio tells us the percentage of total recipients who clicked any tracked link in the campaign. If a user clicks three times, he/she would be counted as a single unique click.
2. What percent of recipients clicked — maybe multiple times?
Total Clicks – (Total clicks regardless of individual / delivered) This ratio tells us the percentage of tracked links that were clicked by recipients. This count includes multiple clicks from individual recipients. If a user clicks three times, he/she would be counted as three total clicks.
3. Of the recipients that were counted as opens due to the images loading, how many also clicked?
Click-to-Open Rate – (Unique Clicks / Unique Opens) This is a great metric to use when evaluating creative imagery and its impact on driving clicks.
Notice that I didn’t mention anything at all about engagement. I simply used the word “click.”
No, I’m not saying we just write off the idea that engagement drives clicks. I simply caution that sometimes we’re not looking at the full story.
Here are some additional ways to discover if your campaign clicks should truly be classified as driving engagement:
A) Were these clicks driven by high unsubscribes?
Did you know that most ESPs count unsubscribe clicks in your campaign clicks? In the case of a campaign that has high unsubscribe clicks, you could see a high unique click rate. This clearly does not mean this is a campaign that should be repeated. It means the clicks came from the mass amount of traffic to your unsubscribe link.
Want to know if unsubscribes are driving a high click rate? Try out the engaged click-through rate I wrote about earlier.
B) Did these clicks lead to conversions?
At the end of the day, marketers are trying to close some sort of conversion event with emails, whether it is getting someone to read an article, sign up for an event, or buy something. It’s important to look at the adjusted response rate, or click-to-conversion rate.
(Conversions / Unique Clicks) If your clicks drove a lot of site traffic, but failed to deliver on conversions, perhaps the email promised more than what you were actually selling.
C) Where was the location of a higher-clicked link?
I haven’t seen it often, but sometimes a small and hidden link toward the bottom of an email drives a tremendous amount of clicks. When this happens, it’s usually a piece with well-written content that many users skim all the way to the bottom before deciding to click. This tells us that the content hierarchy was incorrectly placed and that there was content that users wanted so much that clicks rolled in regardless of the lowly placement.
As you can see, a click alone doesn’t always tell the full story. What have you learned in the past by looking more closely at the data? Tell me in the comments!