As we think about what data we gather, I am always so happy to hear about publishers who move away from dashboards of raw analytics to move to blended metrics.
Blended metrics are usually described as scores (not all scores are blended metrics, but all blended metrics are scores).
The very idea of blended metrics is to tumble the various metrics that together make a more useful KPI and allow your data department to manipulate the component metrics by taking into account certain characteristics of a screen where you are collecting these metrics.
If I take the example of my magazine article versus my hard news article, a blended metric may use scroll-depth, factorize this raw metric differently depending on the type of article (expect that a baseline of less scroll-depth is normal for hard news articles), and further consider time spent to more fairly take into account the presence of visual items that may hold the attention of our users even if they do not induce scroll.
Here’s a great example, from the Financial Times:
The FT created what has become a famous score, which they call RFV (recency, frequency, volume). Now, this is a blended metric for a user. But they also have another one called “Quality Reads,” which blends various metrics to determine whether an article is creating the kind of engaged behaviour that sustains habituation.
Quality Reads couldn’t exist from anything other than a blend. The raw engagement metrics Quality Reads is built out of are then processed (against baselines) so the single score you end up with speaks far more intelligibly about the actual KPI you wanted to track.
You never really wanted to track scroll depth. You wanted to track whether your user was spending good time with your article.
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