Akin Arikan, product strategist for Unica, discusses web analytics and whether or not they are easy enough for everyone to use and understand.  

Believe it or not, that question has been a heated debate in our little industry. 

Looking from the outside, you might think that we just breed over web site usage reports all day long to dream up ways for increasing usability, conversion rates, or sales.

But you need to know the following fact about us:

While people looking from the outside might feel that the topic of web analytics is so boring that it could cure insomnia, for us on the inside, there is deep passion for the subject.

The fire of passion is burning: 

• In web analysts who are trying to get their advice heard in their companies
• Among vendors competing with each other like gladiators in Rome, e.g. Unica, Omniture, Coremetrics, and Webtrends
• Between vendors and consultants who have epic debates over whether the bottleneck for success is in the tools or how they are being used
• In all of us, trying to advance web analytics from mere tactical reporting to a strategic source of customer insights for the business

So, it isn’t surprising then maybe that all this passion has led to a bitter debate among the best minds in our field

Are analytics “easy” and can even be done on the side sometimes? Or are they “hard” and difficult and need closer attention to get right?

Some of our brightest are on a crusade to make analytics intuitive and spread their adoption to the masses. Others of our brightest are on a crusade to reveal all the pitfalls that exist and that have prevented too many companies from generating ROI from web analytics.

It is a good thing the world has me to now reveal the answer to this epic debate!

The answer is, of course, that web analytics are both easy AND hard.

There are aspects of analytics that are easy or at least straight forward. For example:

• If you measure that visitors coming to you from search keyword XYZ have a high bounce rate, i.e .they are arriving at the landing page and them immediately leaving, chances are that either the landing page doesn’t fit their expectations or the keyword isn’t a good one for your offering.
• If you create two test versions of the landing page with essentially the same content but different layout, design, etc. and you find that one leads to higher engagement and conversion rates, chances are you should keep the better performing page.
• If you measure that visitors coming to you from search keyword ABC have a great conversion rates but there are only few people reaching you via this keyword, you probably want to check whether you should try to rank higher for that keyword ABC.
• If you measure that visitors buying from you are all shopaholic until they reach your page where you reveal exorbitant shipment costs or a long form that they must complete, chances are that improving these items will decrease leaks from your funnel

If you did nothing but the above, you’d likely create very respectable ROI from analytics.

But there are other valuable aspects of analytics that are far from easy. In fact, the harder you look at any individual metric the less it seems to say. The more you know about analytics, the less sure you become what any individual report really means.

Huh?

Well remind yourself of the following: 

• If search keyword ABC has great conversion rates, is that because of only the keyword itself or have visitors been exposed to other ads or emails of yours that led them to search for ABC in the first place? Most obviously, anyone searching for your brand or product names must have heard them elsewhere.
• If you create two versions of a landing page with different offers and one performs better for conversion rates, you may still find that you hurt your company by producing lower sales or profits. That happens if you accidentally lead people towards products that are cheaper or less profitable
• If people leak at a particular page in your funnel is it because of something you said? Or is it the point where they have learned enough from you to stop and check first what the competition has to offer? Think about how you shopped for auto insurance online, for instance. Of course, you drop out after receiving the quote and before buying the policy.

So given easy and hard options, which would you pick to work on first?

Tackling the more difficult questions is critical for working towards the ultimate optimization summit whereas the easier questions may leave you working towards a local optimum.

But the easy questions have potentially higher % ROI because you put less effort into them. So you might be inclined to start with the easier tasks and work yourself to the more difficult questions over time.

But would it be a waste of time to optimize the layout of a landing page, for example, if optimizing the offer on the page could yield much higher overall returns?

Argggh… Analytics are both easy and hard.