Tag Archives: analytics

Save the Sanity of Your Analytics Team

Most of us have an analytics platform of choice; be it Omniture, Webtrends, Google Analytics, Coremetrics, or whatever. Most likely your Enterprise analytics solution is one of these. In reality though, we often find different stakeholders bringing their own metrics and analysis to the table – which can be a nightmare for your analytics team or person.

During my time at a major financial institution, our agency used analytics platform A, internally we used analytics platform B, our boss had a personal preference for platform C, and another business unit continued using a legacy platform D. Four different platforms! Four different sources of data! Four different points of view! How do you reconcile all of this data?

You can’t, or perhaps you can, but is it worth all the effort? It is next to impossible to reconcile web metrics from one platform to another. They are inherently different. Do you want your analytics team to explain why platform A came up with 34 conversions while platform B came up with 31? Honestly, this is an exercise in futility. You’d rather have your analytics team working on deeper, more meaningful stuff.

Do yourself a favour, and do your analytics team a favour and draw a line in the sand. You’ll need to convince your key stakeholders that for any given campaign, you’ll be using analytics platform X for your analysis. Your analytics team will thank you.

Now, the governance of certain aspects of your campaign will reside beyond your direct control. For example, your ad server for your banners, Facebook for your Facebook ads, Google for your remarketing, etc. In these situations, you’ll be dependent on external metrics, and some level of reconciliation between platforms is a must. I’m referring to situations that fall directly under your oversight. Say you’ve got a number of marketing initiatives that drive traffic to your corporate domain – this is where you should be using your platform of choice. While platform redundancy is an insurance policy against data loss or corruption, platforms should never be intermingled. Stick to your guns, build your insights based on your data, and don’t allow conflicting data points to cloud your analysis and divert your efforts.

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