It is considered obvious and necessary for businesses to have an online presence of some sort. Accepted business practice also dictates that website performance is measured in some way, usually through Digital Analytics data. For example, you may ask “how many visitors came to my site last month?” Thinking a little deeper you may also ask “I’ve spent x dollars on this new website… what’s my return?” This is where digital analytics should tell you the answer.
But… It’s often not that simple. Think about a popular site such as Amazon. How does Amazon determine the performance of their site(s)?
Hard cash is a reasonable example and who would argue? Smart analysts will not focus on the absolute value of the revenue metric though. Absolute metric values are not actionable and, as such, while they can answer your ROI questions they can’t help you grow your business.
The key here is to look at the data trend – the change over time. Metrics become actionable and therefore useful when you apply context. Seeing how a metric has changed is informative, but seeing how a metric has changed over time when applied to a dimension such as traffic source is more than informative… it’s actionable.
Think how much more powerful the revenue metric is regarding site performance, ROI and site optimisation when you analyze it per traffic source over a month and then compare it to the same month in the previous year – golden!
Now, this is all well and good for transactional sites; but not all sites exchange goods and services for money, so how can these sites extract meaningful and actionable metrics when revenue data is not as readily available? You may not be able to extract precise economic data but what if you could at least extract value trends? Actionable economic trend data for a non-transactional site, that would be powerful!
Capturing Value As Data Points In Analytics
We need to break this down to grasp the idea: the first challenge is to capture value as data points in your digital analytics. How? Whilst a site might not conduct transactions there is definitely going to be a set of desired outcomes. These are the activities users preform on the site that the business model depends on. Here are some examples of what those activities might be:
- Sign up for a newsletter
- Download (an app, wall paper, brochure or case study)
- Click to a partner site (affiliate relationship model)
- Read a blog article
It’s worth noting that these outcomes may well be true of transactional sites too and the techniques described in this missive are still applicable regardless of the transactional nature of the site but we’ll focus on non-transactional sites for this discussion.
Now, the business owner must build a site with these outcomes in mind. He or she should know that these are the actions that users need to take to make the business work. The difficult question is “what are the outcomes worth?” Two thought models are useful here. Either:
- You know the monetary value of each site action.
- Use relative engagement scoring as the best estimation.
If you’re running an affiliate business model, you’ll know that a click on a link to your partner sites will be worth x dollars. For example, if your site offers comparison deals on broadband offerings from your partners, they’ll be able to tell you what a click is worth. The fictional example in the right shows how each click might be valued:
If this site was running Google Analytics, the clicks on these links would be measured using goals with each goal being assigned a value based on the economic worth of the click (see step 8 of this help center article to learn how set up goal values). Hence, no transactions take place but value data is captured.
What if you can’t use this model? Your outcomes might be somewhat nebulous in their nature and the economic value is just too darn hard to work out. Then you could use relative engagement scoring.
Using Relative Engagement Scoring To Measure Economic Value
First, decide which outcomes need to happen, this will help understanding which outcomes are most valuable – not exactly what they’re worth, but as compared to other outcomes. For example, a sign up is worth more than a brochure download. Using this knowledge, you will be able to apply a value of $100 to the most valuable outcome and score the others in descending value down to the least valuable (if possible, using a ratio, such as using $100 for a really important goal, $90 for a very important goal, $50 for an average goal and so on).
The table on the left shows an example of the result of such an exercise. The meaning of the absolute number is less important. You could look at the score as a grade, an economic proxy, a value analogue, a percentage or a weight of bananas! It doesn’t matter. What does matter is that the outcomes have relative values that give you value data from which to extract contextual trend data and therefore actionable insights.
If you use Google Analytics, applying these values to goals will expose three super exciting and powerful metrics:
- Goal value (total value delivered by the site/action)
- Per visit goal value (OMG!)
- Page value (I need to sit down…)
Consider the available metrics before and after applying relative engagement scores.
While the metrics available previously were essentially vanity metrics, now the metrics are actionable and they demonstrate return. You can see return on investment for campaigns. You can see the value your content represents – great for bloggers and content sites.
Using these techniques you will be able to analyse your data as Amazon does – using value as a KPI. Okay, the absolute figures are not great to use in your tax return, but the value trend data is seriously powerful stuff.