Consistency is Key in Marketing Analytics.png

When it comes to analytics, measurements, and metrics, we marketers have vigorous debates about what tools or software we should be using. Vendors, too, participate loudly in such debates, working to convince us that their solution will be better than what we have now. However, a consequence of changing out our measurement tools is that we ruin our ability to do apples to apples comparisons in our marketing metrics, making historical comparisons difficult.

Why? After all, isn’t a visitor to our website or a social media interaction the same? No. In fact, every analytics tool, in its quest to differentiate itself from its competitors, does things slightly (or significantly) different. For example, Twitter’s own analytics define engagement as the sum of all actions taken on a tweet, while many third party tools look specifically at likes and retweets as interactions. Thus, two tools end up defining and measuring engagement very differently.

Imagine doing a year-over-year comparison when we switched tools mid-year. We’d have great engagement for the first part, using Twitter’s data and definition of engagement, then see our engagement plummet when we switched software. We would penalize ourselves for poor performance when the reality is that our standard of measurement changed.

Consistency is Key in Marketing Analytics

If you use a free or very low cost product to do marketing analytics today, stick with it even as you add new tools and technologies to your marketing technology stack. For example, suppose we moved to a different web analytics platform from the free edition of Google Analytics™. There’s neither harm nor cost to keeping Google Analytics running, and keeping the historical data is valuable.

The second thing we must do is ensure we truly understand what our tools measure. How does Google’s definition of a visitor differ from Adobe’s? How does Facebook’s definition of engagement differ from Salesforce Social Studio? Only by understanding the specifics of each metric will we be able to normalize our marketing analytics and ensure we’re measuring apples-to-apples.

Be consistent in your marketing analytics – your paycheck, your job, and your company may well depend on it!


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