Own web analytics for startups – Part IV

Part IV – define questions our web analytics must answer

Now we know which systems we might need to use web analytics with. The only thing left to understand is what exactly we want to analyse and we will talk about it today. Our next step will be to write requirements and start looking for a solution.

Let’s look in Wikipedia: ‘Web analytics is the measurement, collection, analysis and reporting of internet data for purposes of understanding and optimizing web usage.’

Trimming down the definition, I would say web analytics is the collection and analysis of information about viewers of a web site with the purpose of optimization and improvement. Everything is very simple – collection and analysis. The analysis part is more important, because it will determine what we need to collect and how. What are we going to analyse? This is not hard to decide, all you have to do is formulate questions the answers to which we want to find out. And the analytics must give us those answers, whether it’s a web service, installable software or home-grown solution.

Fortunately, we are not trailblazers in this business, so let’s pay a tribute of respect to Dave McClure and Ash Maurya who ‘have tread out a trail’ for all of us in this direction. I recommend reading ‘How I am Measuring Product/Market Fit’ and ’3 Rules to Actionable Metrics’ before continuing reading. Dave designates the 5 main steps in any process of converting visitors to users.

1. Acquisition: users come to site from various channels
2. Activation: users enjoy first visit: ‘happy’ experience
3. Retention: users come back, visit site multiple times
4. Referral: users like product enough to refer others
5. Revenue: users conduct some monetization behavior

If you don’t use the metric to make a decision, it’s not actionable.

At this stage we are only interested in the first three points formulated by Dave. The fourth and fifth points have almost nothing to do with start-ups, to us. They are more useful for services with large amounts of paying customers. At this stage of business development one can already analyse how people generating revenue use the system, what do they miss, how to bring more such customers, how did they find you, and why did they choose your service. When the time comes and our customers will be eager to praise our product, then we can gather such information from Twitter and other social or professional networks and analyse it. As we have already learned a bit not to engage ourselves into not yet materialised problem solving – let’s concentrate on the most important things and rephrase the first three questions in the terms of web analytics.

The key point here, as we see it, is the registration page. It divides analytics into BEFORE and AFTER. Before registration, we are talking about visitors/viewers, after registration we are talking about customers/users. Then users either leave us or stay. Some of them use the system from time to time, the others become ‘frequent flyers’, and the third group really uses the system and this group inspires us to further improve our product.

Let’s look at the first half of the journey, it ends with the user ending up on the registration page, we want answers to the following questions:

1. Where do visitors come from?
We assume that we have all the components we talked about in our previous post; marketing site with a registration page, forum, blog, Ideas, Answers and Customer Support. So let’s split this question into two sub questions:

1.1 Where do visitors come from to our systems?
1.2 After getting to our systems how do visitors get to the registration page?

Each question will be interesting if formulated with negation. This is how it will look like:
1.1 Where do not visitors come from to our systems? Well we thought they would but they didn’t.
1.2 After getting to our systems how do visitors not get to the registration page? Why not?

Because the registration page is so important, we devoted a separate question to it, I think you would agree.
2. How does the registration page work?
Knowing the percentage of people who get to it, but then do not register, and where they go from there, will allow us to rate alterations we make.

And now to those who have trusted us, we want to know the following:
3. What does a user do inside our product?
Having this information will allow us to understand what clients who use the system from time to time need or how we can help heavy users.

If we can get answers to these questions, we can draw a heap of useful conclusions and make decisions based on them. We understand that web analytics gives an approximate picture of what’s going on, but we want it to be able to analyse the information in an intelligent way. Let’s give an example. Our visitor went to the blog page, then went to the web sites’ home page and closed the browser. On the next day same visitor goes to the login page (not registration!), logs in and starts working under his own account. So our analytics shouldn’t count yesterdays’ journey as a visitors’ journey which did not end up with a registration, because in reality this was our user. We simply found it out next day when he logged in. Users are analysed in our analytics system in a completely different way than visitors. In this case his first visit will not be taken in account when we analyse users abandoning a subscription funnel.

Finally, knowing the systems that we might need, and the requirements for the analytics system, we can start searching for a solution. If you like what we do and you have thoughts please leave comments.

Own web analytics for startups – Part IPart IIPart III

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One comment

  1. Andre says:

    You should try us, we just quietly launched in beta and we are releasing powerful features in phases, custom events tracking is part of our feature set, as a matter of fact our system is 100% event driven. Check us out at http://foxmetrics.com – real time web analytics.