The Art of Web Analytics

In my post Designing Web Analytics Dashboards I mentioned that web analytics KPIs (Key Performance Indicators) can be divided into five main groups: Marketing KPIs, Engagement KPIs, Usability KPIs, Conversion KPIs and Loyalty KPIs.

I didn’t specify, however, which KPIs belonged to each of these groups. As such I thought I should write a series of posts to clarify the issue. Here comes the first one, which focuses on measuring your online marketing activities.

As I see it, there are three types of online marketing activities you can measure: Online Campaigns (PPC links, affiliate marketing, banners, etc.), Email Marketing and Search Engine Optimization (SEO) .

In the following I shall provide a list of KPIs and associated actions for each of these types.

Online Campaigns KPIs

1. How much new traffic do you get from your online campaigns?
2. What is the click-through rate for each campaign?
3. What is the bounce rate for each campaign?
4. What is the conversion rate for each campaign?
5. What is the ROI or cost-per-acquisition for each campaign?

Actions for online campaign KPIs:

If the click-through rate is low, your campaign itself should be improved. If your bounce rate is high, your landing page(s) should be improved. If the conversion rate and ROI are low and your cost-per-acquisition is high, discard the campaign or re-negotiate the prize!

E-mail Marketing KPIs

1. How many emails have you sent?
2. How many emails bounced (could not be delivered)?
3. What is the open rate for each delivered email?
4. What is the click-through rate for each opened email?
5. What is the click-through rate for each link in your emails?
6. What is the conversion rate and/or ROI for each email?
7. What is your unsubscribe rate?

Actions for Email Marketing KPIs:

If the open rate is low, the subject text and visible text in the message should be improved. Learn from the click-through rates of individual links what works and what doesn’t. If your unsubscribe rate is high, the news articles should be improved.

Search Engine Optimization (SEO) KPIs

1. How much traffic do you get from each of the keywords you have chosen to focus on for optimization?
2. What is the average rank of your keywords on the search result pages across all search engines?
3. What is the conversion rate for each keyword?
4. What is the cost-per-acquisition for your SEO activities?
5. What is the ROI for your SEO activities?
6. Which keywords rank low on the search result pages while at the same time contributing with many visits?

Actions for SEO KPIs

If the average ranking of the keywords you have chosen to focus on is low, you should consider ways to further improve your website for SEO purposes.

If the conversion rates for the keywords you have chosen to focus on are low, you should consider to replace them with other, potentially more effective keywords.

All keywords which you have NOT chosen to focus on, and which have low average rankings, are candidates for optimization. Choose those which result in many visits or high conversion rates inspite of their low ranking.

That’s it for now! I hope you found this overview helpful. If not, please leave a comment.

Traditionally, usability is tested qualitatively by conducting interviews with a small number of potential users.

The interviews take place in a “lab” where the participants are given certain tasks to complete on the web site in question. While interacting with the site, a moderator observes their behavior and asks them to share their experiences.

While I’m a big fan of this kind of usability test, the method also has a number of drawbacks. The most important being that it takes a long time to carry out and doesn’t provide the kind of instant and continuous feedback we know from web analytics.

As such, I find it interesting to search for possible ways of using web analytics to measure usability. What we need, ideally, is some kind of easy-to-understand, yet robust, web metric that indicates how easy it is for the visitors to navigate our site.

Such web metric should not necessarily replace qualitative tests in a lab. Rather, it should help us to obtain early warnings and point to the parts of our website which are most in need of usability attention.

Moving beyond standard metrics
Measuring usability by means of web analytics is not as easy as one should perhaps think.

Traditional web metrics, to be sure, will not do the job: The number of page views per visit, the bounce rate, the number of visits per visitor, the average visit duration, etc. None of these metrics can tell us anything about navigational problems.

Although it is true that frustrated or confused visitors might end up producing many page views per visit, for example, highly engaged visitors might do the exact same.

Introducing Back Navigation Rate
So, the question remains: How can we identify usability problems simply by looking at click stream data? Is it possible at all?

Some years ago, my colleagues and I at Netminers set out to answer that question. We came up with the idea that if there is any way to identify frustrated or confused visitors it must be based on how often they go back and forth between the same pages.

A visitor who runs into a problem, we thought, is likely to stop and go back to make sure he or she didn’t miss something. This might even happen repeatedly since visitors are likely to double-check before abandoning the site altogether.

We therefore decided to develop a technique for tracking what we call “back navigations” and “turn pages”. Consider the following click stream.

The blue dots represent pages seen by a single visitor. The arrows indicate the direction of the click stream.

A is the entry page, while B and C are pages that lead to a particular interest point, D. Having looked at D, the visitor decides to go back to C, and further back to B. Finally the visitor makes a new move forward from B to E.

As can be seen from the figure, there are four forward navigations and two back navigations. We say in this case that the Back Navigation Rate is 50% (2 divided by 4). Notice also that D can be seen as a turning point in that the visitor decides to turn around here. We call D a “Turn Page”.

When is a high Back Navigation Rate bad?
Is it good or bad that the Back Navigation Rate is 50%? Well, it depends.

You cannot always say it’s a bad thing, because sometimes visitors just like to explore links by moving back and forth on the site. This is especially the case on the home page where visitors often explore many different links before selecting a specific page for closer inspection.

According to Netminers Index (i.e. a series of benchmarks based on all the data we collect across all of our clients), the Back Navigation Rate is in average 30%. Back navigations are therefore not as rare as you might first think.

Keep it low for your check-out procedure!
However, imagine now that you are looking exclusively at a check-out procedure or a similar conversion process. In this case you certainly do not want users to go back 30% of the times! A check-out procedure, to be sure, is supposed to be linear, not zigzag, and, in our experience, here the Back Navigation Rate definitely shouldn’t exceed 5%.

Turn Page Rate
But you can do more to identify problematic back-and-forth movements. Notice that in the click stream presented above D appear as a turn pages. This, however, happens only once.

Consider now a case where the visitor produces repeated turn pages.

In this case B and C are both turn pages, and both of them appear as such two times. We can capture the difference between the former and the latter click stream by what we in Netminers call Turn Page Rate. This rate is calculated as follows: First, you slice your data so that you only look at turn pages. Then you divide the number of page views by visits. This rate is 1 for D in the former click stream , but 2 for both B and C in the latter.

What do you think?
What is your opinion about Back Navigation Rate and Turn Page Rate? Can you think of any flaws of these metrics? Do you have suggestions for some alternative and perhaps better usability metrics? Please let me know!