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Slowly but surely Google Analytics is becoming a fully fledged powerhouse tool of digital business intelligence.
You can upload your own custom data, campaign cost data, send custom dimensions and metrics, include Big Query integration, sync with the DoubleClick suite, AdWords… something we all have seen coming since people started tracking their coffee machines with Google Analytics.
Until now there was one little feature that was missing (which was frustrating as it was available in other Google products such as DoubleClick) and it’s finally here: the ability to create personalized metrics from existing ones.
In other tools you might see it called ‘compound metrics’ or other variations of the phrase.
In a sense, Google is catching up to established players such as Omniture. And it is yet another move by Google that further improves the experience for the more advanced users of the platform who would normally rely on the API and spreadsheets to calculate their own metrics.
1) Moving away from ROAS: getting ROI in Google Analytics
The standard business model for digital marketing agency is to charge the client a certain percentage of their net media spend. For instance, with a 10% fee, spending $1000 on AdWords would result in $100 fee for the agency.
This immediately presents a problem in Google Analytics as we are not able to easily calculate the actual ROI for our ecommerce clients and we have to resort to Excel spreadsheets that add our fees.
Now, with calculated metrics, we can easily create a metric that is the real spend (net media investment + % agency fee) and a separate metric that calculates ROI based on the revenue divided by this actual spend.
No more API calls and formulas in spreadsheets that we need to share. The client can always login into GA and see the real performance.
In order to do so you already need to have ecommerce implemented and correctly linked Google Analytics and AdWords.
2) Getting the real cost per lead
You might be a lead generation website and your goal is to know how much you are paying to have each lead that comes to you after agency fees. Similar to the exercise above our goal is again to calculate the real cost per acquisition of a user.
In this case we would need to have already conversion (goal) tracking setup in your Google Analytics and you need to be tracking each sign up.
Similar to the above, you would need to create a calculated metric that that is Media Spend + % of Media Spend and then a second one that divides Total spend divided by number of conversions.
If you have estimated an internal fixed cost to process each lead you can now easily add that to Google Analytics.
3) Revenue in any currency
If you are a global organization (or your client is one) you might find yourself required to report your local revenue in the currency of the head office. This process can also be facilitated and made much more efficient if you create a calculated metric that simply uses the average of the exchange rate.
This is of course only to be used as an estimation and to allow for quick understanding of the performance and not for final purposes.
Headquarters usually want to understand how a specific local market is trending in their own revenue and seeing the results in the local currency is not usually helpful.
4) Page views by user
If you are a publisher and you care about the loyalty and engagement of your subscribers you would be interested in understanding these on a per person basis. You would not be as much concerned with the number of page views per session (visit) but rather the consumption per user.
A great calculated metric to use in a cohort analysis is the number of page views per user. So you can see how well your content and marketing is evolving.
For instance, how much content are users consuming week over week when we compare users who first came to the website three months ago vs. users who came a month ago. Also, how many pages are those same users consuming a week or two weeks later? Are your metrics improving?
Word of caution
And now for a word of caution in regards to calculated metrics. If you use any analytics tool on a day-to-day basis you have surely read and re-read all of Avinash Kaushik’s articles on analytics, after all he is the star in the field and I highly encourage you to look into his work.
In that case, you might remember an article back from 2009 that recommend four metrics that are helpful if we want to avoid having insights (note the sarcasm). And surprise surprise, calculated metrics are on the list! But how can they be? The examples above make sense and sound very useful…
Indeed. But what Avinash warns against is creating complicated metrics that may actually harm our ability to derive insights from the data. Read the article before you jump into creating any that are too advanced.
With thanks to Hristo Vassilev, Paid Media & Analytics Specialist at iProspect Canada, who contributed to this article.
To hear more from Avinash Kaushik, he will be speaking at our Search Engine Watch Connect event in Miami on February 4-5, 2016. Register your interest today!
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