4 contexts help you interpret your data.
Historical Contexts
What does history tell you to expect? By reviewing data through a historical lens, you can understand trends and typical behavior among your customers.
For instance, at DigitalMarketer, we’ve noted that sales dip in the summer. Consistently. Every summer.
So rather than worrying about lower numbers, we’ve come up with strategies for boosting sales in late spring. We also reduce ad spend in the summer because we know the ROI won’t be as good.
External Contexts
What changes outside our control have influenced our metrics? Maybe a new competitor has entered the market. Or maybe technology has changed, necessitating major changes in the way you do things.
Think Google algorithm updates.
External factors may be outside your control, but you need to keep them in mind when evaluating performance.
Internal Contexts
Have you made changes to your strategy that impact your performance? Have you made changes to your site or launched a campaign?
This is more of a self-review. Think through the changes you’ve made internally that might have affected your numbers.
Contextual Contexts
This has to do with how you’re pulling the data. Are you comparing raw numbers or percentages? Are your numbers skewed by outliers? Do you have data that doesn’t make sense because of an internal or external factor?
Together, these contextual factors help you account for the immeasurable things, the things you can’t foresee or explain in your data. And they help you evaluable the validity of your data.
