The Industry Average Myth

The Industry Average Myth

There is a lot of “common knowledge” that floats around about what’s good for a particular metric and what’s bad for a particular metric. While these numbers can serve as a guideline they are likely a poor benchmark. Make sure that an industry average actually applies to your industry.

As an example 10% is often used as a good click through rate. But for many industries or campaigns (like trainers, consultants, and professional coaches) it might signify an outstanding rate. It might also be an underperformance in some cases.
The problem with blindly using industry “rates” is that it might set up an unrealistic goal, or worse yet, have you focus on the wrong problem.

We had a potential client that was comparing their click rates to industry average and decided that their rates should be higher. Frustrated he said, “That’s why I’m talking to you guys. My click rate is 5%. I’m just barely making the low average!” The problem with this is that he was looking at “industry average” which was the below:

  • 5% – 15% for B2B newsletters
  • 2% – 12% for B2C promotional email marketing campaigns
  • 10% – 20% for emails sent to highly segmented and personalized B2B and B2C lists
    [Data: Alert Solutions]

While we agreed that he could be doing better, he was not as far outside the norm as he was suggesting. He was taking his overall average which included promotional emails and comparing just to the B2B content newsletter rates. A more accurate reflection would have been taking the B2C and B2B data and averaging that.

To get a better picture we used data from our email marketing platform. The email marketing platform lets us define a particular market segment within B2B, in his case a business consultant. This was data specific to his actual industry and let us compare content based results vs. promotional results. Turns out that he was almost at the median with an average being 4%-8%.
So the question was, “Are you comfortable being middle of the road?” This potential client still wanted improvement to be toward the top of average or even exceed it.

The point is, he didn’t know where he stood because he was using broad generalities. He could have been in the top percentile and still beating himself up trying to fix a problem that didn’t exist. If you’re going to benchmark against averages, make sure it’s the right average.

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