There’s been a lot of web ink spilled on the subject of measuring user engagement. It is true there is no magic formula for measuring it, but take my word for it: when a user buys something from your web store, fills up a lead form, subscribes to your RSS feed or comments on your latest blog post, that user engages with your website.

Try to answer the following question: how well is your website doing when it tries to engage visitors that have a clear focus? I am talking about those visitors that land on your website by searching for a specific keyword on search engines, unrelated to your brand.

1. Start by setting goals for each action you deem means engagement

The following video will offer you clear details on how to do exactly that:

Here are a bunch of examples of actions on your website that can define user engagement:

• buying a product
• filling up a form
• subscribing to newsletter or RSS
• sending you feedback
• commenting on an article
• recommending you to a friend
• tweeting your content

2. Define a non-brand keywords visits segment: that is, visitors that land on your website when searching with keywords unrelated to your brand

If you have never created segments before, check out this video tutorial.If you are familiar with segments, dive right just in and define one just like in the following image:

Replace "your-brand-name" with a keyword specific only to your brand

3. Check out for winners and losers

It is time to check out how well your website is doing when it comes to engaging your visitors. Apply the above segment to your Google Analytics data and dive in the following report: Traffic Sources > Keywords. Filter for non-paid traffic and look at the Goal statistics, just like in the image below:

Check out the conversion rate for each keyword

That’s about it. Now that you know, how do you plan to improve performance?

…or the scientific approach to actionable web analytics

Web analytics masters like Eric Peterson, Avinash Kaushik, Anil Batra and many others have been advocating since always for actionable web analytics. They have dedicated blogs and entire books on how not to be a reporting monkey but rather be an web analytics ninja.

The road to web analytics ninjaness ain’t easy. Whenever you think you get a big WOW from your web analytics data don’t just run to the IT department and tell them everything they did is plain wrong. Take a deep breath and try to answer some questions before.

How reliable is the source of your discovery?

This one gave me shame moments for a couple of times so far. On my dashboard I have a big widget for the conversion rate. One day, entering the web analytics solution it showed a huge drop. I got everybody in the company fired up, just to realize that nothing happened to the conversion rate. It was just a bug in our website that affected the way we measured a couple of our metrics.

Now, whenever I get WOW or OMG moments, the first thing I do is to do a WASP debugging of the pages are guilty for my WOW moment. I make sure everything is still measured correctly.

Have the claims been verified by other departments?

In the above scenario, when I got everybody fired up with my conversion rate drop, just before entering the CEO and giving the awful news,  the sales department told me that according to their reports, for the same day sales were up and not down. The marketing department told me that no special marketing campaigns are on so the traffic should be the same… All of them suggested me to calm down, drink some tea and go double check.

Since then, whenever I analyze revenue reports in my analytics application, I make sure to double check it with the other departments. If they confirm, now it’s the moment to get excited.

Is this how websites work?

This question actually helped me quite some times so far. Here is an example: A report is showing that a page has 100% bounce rate however people visiting that page bought a product in the same session. How is that possible? No, this is not how websites work. If a user bounces than he can’t convert: he is not on your website anymore. So there must be something wrong with this report

Actually, it isn’t. What is wrong is the way some people look at it. Bounce rate is calculated only for landing pages. Let’s say that page has been seen by 1000 visitors out of which 5 coming from search engines directly to the page and the others coming to it from other pages in the website. If all the 5 visitors coming from Google bounce, than we have 100% bounce rate. However, any of the other 995 users might of have bought something.

If things just don’t make sense, try to figure them out. If they don’t make sense to you, they won’t to your management as well.

What else could be explained with the data you get?

This is a classic one. When you see that the time spent on your website increases it doesn’t necessary means that users decided to look into more products of your website. It can also mean they don’t find what they are looking for. The same goes for increases or decreases of the pages/visit rate.

Whenever you are ready to take a decision based on the data, question yourself  if the same data can’t explain for other behaviors of your users as well.

Where does the other evidence point to?

The metrics you get for your website visitors are interconnected. When one metric is affected bet on it that other metrics will be affected as well. What does it mean when pages/visit increases but time spent on website doesn’t? What about the other way around? What if the drop in bounce rate has a very small impact on time on website? Does it mean people really stopped bouncing or might there be another explanation?

Whenever you want to act based on the web analytics data you have, make sure that any other metric you take to analyze, fits in your theory.

Are you taking it personal?

This is a tough one. As mastering the web analytics ninja way of life, your intuition becomes stronger as well; sometimes too eager to adopt new things. If during your experience the conversion rate increased only by working on the funnel, it doesn’t mean that’s the only way it can be increased.

Always question your personal beliefs and share them with seniors. Don’t take their word for it (they have their own personal beliefs) but rather use their arguments to see if your belief can still stand up.

Conclusions

Be scientific about it. Web analytics should not be treated as a walk in the park but again, it’s not rocket science for MIT graduates as well. Be skeptical.

What other questions/methods are you using to validate your web analytics actions?

This article idea came out while going through the Skeptical Magazine, which I recommend to any geek out there.

Understanding who your newsletter subscribers are, is a must. The simple fact that they subscribed it means that they are interested, they care, they want to know more about you. If your newsletter quality will raise to their expectations, it will be much easier to convert them from subscribers to clients.

So, who subscribes to your newsletter?

In order to make a profile of the visitors who subscribe to your newsletter, first add a Goal to your Google Analytics implementation. A goal would be the URL of the page that says “Thank you for subscribing”. In case you use double opt-in, which I highly recommend, it is the URL address of the page that confirms the subscription.

Here is how your goal setup should look like:

Creating a Google Analytics Goal for newsletter subscribing

Gather data for one or 2 weeks (or until you have at least 100 new subscribers) and than you can run deep into profiling the newsletter subscribers. It will help you better understand the behavior of your visitors and come up with strategies to increase your subscribers list (without spamming that is).

Define a new segment for newsletter subscribers

In case you are not familiar with user segments in Google Analytics, take a look at this video tutorial. Here is how your new segment should look like (that is if your Goal for newsletter subscribers is defined as Goal 1):

Defining a segment for newsletter subscribers

Now, all you need to do is get back to your Analytics data, apply the newly created segment and see what you find out about the people who subscribe to your newsletter. Try to answer the following questions:

• Are they mostly new or returning visitors (Dashboard > Visitors > New vs Returning)
• How many pages and how much time do they spend on the website before subscribing (Dashboard > Visitors > Visitor Trending)
• What are the pages that are most persuasive in convincing users to subscribe ($index metric in Dashboard > Content > Top content)
• What are the most common traffic sources for the visitors that decide to subscribe (Dashboard > Traffic Sources)

How much potential are you wasting?

After understanding your newsletter subscribers, the next step would be to see how many visitors of your website have the same behavior with your newsletter subscribers. In other words, how many people are most likely to become subscribers.

Back to the drawing board (that is the segment creating page). Generate a new segment that would define the behavior of your subscribed users. Let’s say the conclusion you get from the above study is that your newsletter subscribers are new users that come mostly from search engines and visit at least 4 pages a session. Create a segment for it and apply it to your website data.

Now you have the number of visitors that subscribe to your newsletter and the number of visitors that are most likely to subscribe. Check out the conversion rate from one to the other? Let’s improve on that.

The next best thing would be to act on it

In case you use MailChimp for delivering your newsletter, we have a free solution for you. Today we have just launched a public limited edition of our real time behavioral targeting platform, PadiAct. After defining your segment of visitors who are most likely to subscribe to your newsletter, using PadiAct, you can ask these visitors to subscribe to your newsletter. It can and it will skyrocket your subscribing rate. Here is how it has worked for one of our clients.

In case you don’t use MailChimp but you are still very interested in making this work for you as well, drop us a message and we’ll see what can be done.

In the real world behavioral targeting is easy. When a woman enters your shop you welcome her, invite her to the area for women products. Based on the interaction with her you modify your tactics to persuade her to buy or try your products.

Just like in the real world, on the web, users interact with you but using different methods: links and forms, instead of language. There is no excuse for you not to use real time behavioral targeting when dealing with your potential customers… and it’s really not that difficult.

No matter if you are just about to start a new website and want to track it using the power of Google Analytics or you are one of the early adopters of the powerful web analytics platform, an implementation checklist might be handy. This series of articles comes from my own need in having a clear checklist when starting any new client with web analytics consultancy.

First thing is first. As the owner of the website, make sure you own the analytics data for it. I’ve seen many cases where consultants create the Google Analytics profile on their username and share it with the owner of the website with read only rights. When the website owner wanted to switch the consultant guess what happened?

Yep, losing your analytics data is not cool at all. So, the owner of the website should be the one who creates the Google Analytics profile and shares it with as many consultants he wishes to. You can start by using your already existing Google account or create a new one.

So, here are the checklist chapters:

• Implement the right tracking code and make sure you track your whole website
• Accuracy in tracking traffic sources
• Setting up goals, funnels and ecommerce tracking
• Bonus tracking tips and hacks (filters, segments and others)

Here is the short version of the checklist:

Let me know your feedback on it or if you would like me to cover any other aspects as well.