Look at the images above — the first defies understanding. It’s just a bunch of mush. The second uses visualization to clearly demonstrate what’s in the bowl, allowing the user to derive meaning. It’s the same with your data.
But, using analytics to drive ROI requires more than simple visualization. You have to think about what relationships are meaningful and which have little or no value.
Today, I’m using Google Analytics to show how you can derive value from your data.
Using analytics to drive ROI
Here’s a great example of how you can use Google Analytics to derive valuable insights and make decisions to optimize your ROI.
We created a table comparing the ROI of various age groups buying from our website. Google determines the age groups, so that’s a little awkward if you want more granular data, but we can clearly see what’s going on.
In terms of conversion rate, we see that younger consumers, between 25 and 34 convert at a higher frequency than other demographic groups. But, we don’t stop there.
We can also see, by looking at the Sessions column, we’re also doing a great job in driving younger visitors to our site. We might consider doing something to increase visits from the 35-44 year olds, since they convert at nearly the same rate as our 25-34 years olds.
At first blush, one strategy we might consider is driving more traffic from younger visitors.
But, let’s take a deeper look at all that this data tells us.
Notice, I’ve included AOV (or average order value) in this table and it tells an entirely different story. Now, we see the importance of older visitors. Specifically, we see that 45-54 year olds have a significantly higher order value than younger visitors.
Unfortunately, we do a pretty poor job of converting these visitors — with a conversion rate of only 1.84%. Equally damaging is that only a little over 3000 sessions come from this very valuable group of visitors.
This suggests an entirely different strategy — drive more visits from consumers 45-54 years old and improve conversion rates for this group.
More analytics to drive ROI
In the analysis above, I chose to focus on conversion because it’s really important for ROI. But, it’s not the only factor impacting ROI. In fact, we need to optimize every aspects of the conversion funnel to achieve maximum ROI.
See the funnel to the right. You need to put more visitors into the hopper, keep them flowing efficiently down the funnel, and guide them out the bottom — that’s maximum ROI.
So, let’s take a look at the other end of the funnel — acquisition. And, I have a visualization to reflect where visitors come from.
Notice, in the pie chart, most traffic comes from Google (which is search traffic) and YouTube drives the next big chunk of traffic. Again, this suggests a strategy to focus on these two sources of visitors.
Now, look what we find — something totally different.
Now, instead of a strategy that focuses on Google and YouTube, we see that the Google sandbox, mail, and Facebook drive ROI.
You clearly see why those of us working in analytics, call things like visits and sessions vanity metrics. They might make you feel good, but they don’t necessarily put money in the company bank account. In contrast, by looking at orders or conversions, we clearly see what strategic changes will increase ROI the most.
I could go on like this forever, but I think you get the idea.
Here are my key take-aways from today:
- Metrics reflecting ROI should dominate in forming strategy, not vanity metrics. Measure conversion, average order size (value), order quantity, transactions/ user, and other metrics that reflect sales.
- Track how segments contribute to ROI based on demographic values (age and gender are available in Google Analytics, but other tools may offer additional demographics such as income, education, etc), geographic values (GA offers city/country, but you might have other options on other platforms), mobile versus desktop (laptop), browser (as some browsers might not do a good job of rendering your pages effectively), and psychographics (GA now offers some of these, which they call interests). This list isn’t comprehensive and your industry may require additional segmentation variables.
- Don’t ignore other stages in the conversion process. I recommend doing a funnel for each segment to see how they move through your pages on the way to conversion. Pay special attention to shopping cart abandonment. Here’s an example of a funnel:
- Create visualizations that allow insights to emerge from the data.
- Analytics isn’t a set it and forget it kind of thing. Repeat this analysis periodically to make sure it’s still valid.
- Don’t stop with looking at the analysis. Change your strategies based on the insights provided.
- And finally, measure again after making strategic changes to see how the changes impact ROI. You may need to tweak it a bit to optimize your returns.
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