When we discuss marketing strategy, one frequent question is whether to mitigate our weaknesses or play to our strengths. How do we know which is a better strategy for our business? If we choose poorly, we waste an enormous amount of time and resources.

• Playing to our strengths when our weaknesses are overwhelming means negative forces are constantly undermining our efforts to grow.
• MItigating our weaknesses when our strengths are powerful means we leave tons of opportunity on the table, neglected.

How might we determine which is the best choice to take, from an analytical perspective?

What’s The Middle?

To make a sound judgement, we need to know two things:

• What’s the middle of our dataset?
• How much of our performance is above or below the middle?

If we have both answers, we can determine whether to play to our strengths or mitigate our weaknesses.

When we look at our data to judge overall performance, we have two statistical choices to determine what’s happening in the middle of the data set. We have the median and the mean (what most people call an average).

We use medians frequently in marketing because of the number of outliers often in our data. By using the median – the literal middle of an ordered data set – we often get a better measure of what’s happening “in the middle”, known as central tendency in statistics.

Means can be thrown off by outliers. One lucky hit, one marketing item that “goes viral” can seriously skew an average, or one day when our web analytics software forgot to record any data, especially in relatively small data sets.

What does this have to do with the middle of our data? We’re going to compute two middles, one mean and one median.

• If the mean is below the median, that means there are more negative outliers than positive ones – and we should consider a strategy to mitigate our weaknesses.
• If the mean is above the median, that means there are more positive outliers than negative ones – and we should consider a strategy to play to our strengths.

For example, here is a look at my Google Analytics data over the last year:

The columns to pay attention to are highlighted in red above, the gap between average and median. In almost every case, the gap is positive, which means that there are more positive outliers in my data than negative. The average is higher than the median. This means that my strengths are stronger than my weaknesses, so where I have strengths – social media, above – I should play into them. Where the gap is weak or non-existent, I should look to see why, and possibly shore up weaknesses in those channels.

If I wanted to kick it up a notch, I could find the difference between the user gap and the new user gap. This would tell me whether a given channel is better at bringing in new people versus retaining existing audiences:

What we see above is that email and social media have a higher rate of keeping audiences, and organic search and direct have a higher rate of bringing in new audiences. I’d use this information to inform strategy about audience acquisition versus retention.

None of the above requires more than just the average spreadsheet software, but it’s a statistical idea we can take to any marketing data we work with.

Disclosure: This post has been revised and updated several times since its publication. The most recent revision completely replaced all the data and introduced the gap and gap of gaps calculations.

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