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How to measure content performance is certainly an ongoing discussion. Yes, we want it to help us drive leads, and we want it to help us drive conversions, but what’s a good time frame for our content performance analysis?
I’ve tried a number of different ways to try to measure performance. By day, by week, and even by month. Every way has its positives and negatives. The way that I have seen work the best is the 30-day rolling model. That’s also what Amazon does for creator content. For example, here is how Amazon displays the performance of my product review videos. They show me my performance for the last 30 days. That’s it. I don’t even get an option to look at it differently.
The 30 – days rolling model
When it comes to looking at content performance and what’s working and what’s not working, I recommend looking at the timeframe of 30 days rolling. So that means we’re looking at what has worked in the last 30 days. Then tomorrow, we look at the new last 30 days from that point backward.
Oversimplified, that model looks like this below. The blue rectangle signifies the time period that we’re looking at and then it moves over as time advances.
Why this content performance analysis model works better to measure content performance
For some content creators, this model makes a lot of sense, but sometimes there’s pushback when you implement this. People that are used to measuring everything on a monthly or quarterly basis ask questions. Why wouldn’t we look at the month, or why wouldn’t we look at the quarter? I’m not saying we absolutely 100% never ever can look at anything by month or quarter. But on an ongoing basis the 30 days directly preceding today make the most sense.
Keep in mind that analyzing content performance is different from analyzing financial performance.
I‘ll put it this way. The dollar earned on Day 1 of the month has the same value as the dollar earned on the last day of the month.
Content published on the first day of the month is potentially way more valuable than content published on the last day of the month, however. Because it has had a longer chance to perform – whether it’s through email, social or search engine optimization.
We also shouldn’t just look at content that was published in the last 30 days. We should look at the performance of all content in the last 30 days – no matter when it was published. As we discussed before, some content takes a while to perform.
Months also vary in how many days they have. So why would content published in February with 28 days be able to keep up with content published in July with 31 days?
Read next: How to Use Data to Make Decisions: A Guide for Success in Content Strategy
Content performance analysis is an ongoing campaign
This model also signals to content creators that it’s an ongoing engagement. Yes, you can perform incredibly well on Day 1 but on Day 31, that original Day 1 cycles off the metrics. So there is a very well-defined need to keep up performance and find a way to drive content performance on an ongoing basis.
I’m not a fan of being on the content hamster wheel, and I’m not so sure we need to overdo content production. Sometimes updating existing content is much more efficient and effective. For example, I updated an article the other day from seven years ago, and after my update, it had way more traffic in the first day after the update than it had in the last few years.
The point that this kind of way of measuring content performance signals is that we need to find a way to get content to perform. Always. Sometimes that’s through updating existing content and sometimes by producing new content. Other times it might include creating content of a different type.
You know how some salespeople are always trying to reach a goal on the last day of the quarter? This model doesn’t necessarily get rid of that completely, as some creators may realize that they need to see some improvements in the next day or two because a couple of good days are rolling off. But the encouragement should be to simply continuously work on getting content to perform.
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