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Wednesday, March 6, 2013

A Journey Into Web Analytics (Part II): The challenges

[After an introduction post on the business value of Web Analytics, the second part of this series covers some of the major challenges & obstacles that await you on the long journey to successful online analytics.]

“Web Analytic is hard”

Web Analytics holds attractive promises for businesses. After reading part I, it certainly sounds like online analytics is the magic silver-bullet that most businesses are dreaming for. Then why so many companies are failing in seizing such opportunities? A simple and common answer is that “Web Analytics is “hard, damn hard”!

Ok, let’s be honest with ourselves: most people would certainly say about their job that it is hard. But for sure leveraging Web Analytics value isn’t certainly easy – not as easy as many people think or as most vendors used to claim it. Creating an online analytics culture is quite challenging as there are many difficulties and obstacles to tackle on the way.  And these are not always lying where you think they are (ooh, the vicious ones!). Many companies fail because they underestimate the challenges behind successful Web Analytics.


I have a Web Analytics tool so…

Usually, the first challenge that comes to mind is the technology and the tools. I think too many people believe that Web analytics is just about deploying a great tool, getting online content tagged properly and that’s it. So how can that be so difficult? After all, nowadays most businesses have a Web analytics solution implemented on their websites. For example, last year I had a look at European automotive sites and only 4% had no recognized analytics solution. So does that prove that the other 96% are doing what is defined as “Web Analytics”?


No. Having a Web analytics tool just proves that you are doing online measurements and possibly reporting but not that you are doing analysis (i.e. turning data into insights) or that you are taking actions. The purpose of Web analytics is about understanding and optimizing online usage!

Moreover, having one tool (or two) whether it is Google Analytics, WebTrends, Adobe analytics or Analyser III is not enough as these are just measuring quantitative information know as the "What" (=what happened on your site) and the "When" (= when it happened). But what about the qualitative information - the “Why” (= why people came to your site) and the “How” (= how do they feel about it)?  Usually measuring qualitative information will require different and specific tools.

Finally, in many cases, the online channel is just a part of a (much) larger business picture. Online data can not sit alone on their side – they fit in a lager context (see further). Therefore to be really effective, online data has to be integrated with other data. That means integrating your Web analytics tool with other systems (such as CRM, other databases…). Oooh, system integration! That is where things usually get dirty. Now, we are talking about challenges! :-)

 

Too much data

Ok, let’s assume you have overcome the technical challenge. Now you are likely to face another typical challenge of Web analytics: having way too much data – more than any data geek can handle. The great thing with the Web is that it is probably the most measurable media we have so far but it is also a problem. Indeed, it is very easy to get overwhelmed by the huge quantity of data that can be collected.

The measurement possibilities are so enormous that it is tempting to succumb to let’s-measure-every-single-click frenzy and to turn any Web analytics tool into a data-report-puking machine.

The problem is that the insightful information is usually a very small portion of this mountain of data. But this is the one you need, the specific data that will bring real insights and that will make you take the right actions. So finding this tiny piece of information is often like finding a hairpin in a haystack.

For that you need the right people and that is the next challenge…


Lack of “staffing”

Another typical problem with Web Analytics is that many limit its scope to a tool and technology. Too often, the focus is on allocating budget for implementing tagging, configuring the tool and the thousands of reports that come with it. But when it comes to allocating people: nothing, nada, nicht, que dalle!

Ok, now is the right time to slip in some intelligent expression like “Owning the best hammer doesn’t make you a good carpenter”. Just replace the words “hammer” by “web analytics tools” and “carpenter” by “analyst”. Amen. Web analytics tools are just er… tools. They don’t analyse nor interpret the data, they don’t make recommendations, yet (but who knows, I am sure people like Joseph Carrabis have probably their own idea on that topic).

This is the job of (Web) analysts to put the data in context, to grab its complexity and turn it into business intelligence. And, this is not a job you can assign to first person you will find. It is not something that can be done one hour a day. Don't get me wrong here, I am not picking on Avinash’s great book, “Web Analytics an hour a day” (highly recommended reading by the way) – I just want to say that analytics is not a side task, it is a real new job that requires specific skills and experience (more about this in Part IV).



And even if you decide to assign dedicated persons, you will need to find these. And you will not find them at the corner of the street. Experienced analysts are highly demanded and come for a price. What about hiring junior or freshly graduated Web analysts? The problem is that online analytics is not much taught in universities or high schools – apart for few exceptions (but it is slowly changing). Online analytics is more something that you learn by yourself, on the job. It may get easier in the future thanks to great projects such as Web Analytics Without Borders and Analytics Exchange that offer the opportunities to beginners, students to develop their skills and acquire experience on real projects.

Siloed organizations& the reluctance to change

But then even if you have good tool and a good analyst, it will not be a guarantee for success (at least it is a good start). You will need to face “organizational” challenges. It is very typical (and even almost unavoidable) that big companies are organized in a vertical way, with what are commonly called silos. Each department focusing on its own area: Internet marketing takes care of the website, media department handles advertising, sales department is responsible for lead & sales management… All these departments contribute to the whole business process and it should be the same for Web Analytics. Its scope shouldn’t be limited to the website (or online channels) and to the few departments that are managing it. Online data are part of a more global context: business processes.

What is it the point to measure online lead conversions and increase these if it is not linked with sales? I mean, a Internet marketer, may be doing a great job at using the website to double the number leads but if these don’t turn into sales because of their  poor quality, it makes no sense. Online data can prove to be useful for many departments inside the company: product design, sales/production planning, brand strategy, marketing intelligence... The problem is that there is often a lack of awareness and sharing. It is very likely that most departments are not aware about the existence of online knowledge and about possibilities.

Therefore to really leverage the value of online analytics, one will have to “break” the silos. I don’t mean re-organizing the whole company - that would be impossible :-) - but making people communicate and work more together, change people habits, change processes, change the culture. And if there is something difficult in big organization, it is change. Finding the right organisation is a challenge on its own – as who should own Web analytics? Where should it sit in the organization? Vertical vs. horizontal? Centralized vs. distributed?

Patience & perseverance, you will need!

 

Beware the Hippos

The people you work for can be a serious challenge as well. Internet marketing managers had a quiet life – as long they could persuade people around that their job was brilliant. The boss could impose any idea because he/she was the boss and there was nothing to contradict it. Web Analytics means a possible end to this “state of grace”. Web Analytics is often a painful reality check -  “bye bye” judgement based on gut feelings or influence and welcome to facts & figures! And the Web analyst is likely to be the bad news messenger. So the persons that are supposed to support you may do it to a certain extent only – as long as it serves their interest. Many people prefer to live in ignorance (I call it the “ignorance is bliss” syndrome), they won’t say it out loud of course but in practice…

Your findings may go against the HiPPO’s - highest paid person opinions. How will you handle that? How will you make people accept something that may show they are not doing such a great job? You can’t just come in and throw your facts & conclusions at your boss face while saying victoriously “Ah! Ah, see how wrong you are!”. When it reaches a certain level, political aspects get in the way and you will have to deal with these with extreme caution.

 

And there are more…

Challenges don’t stop there. The media itself make it challenging. The Web is a (super) fast evolving media. First, there is what some call the “decentralization” of the Web, induced by social media. Content is not centralized anymore in a limited number of sources (typically your sites) but it is disseminated across multiple types of sources and platforms. Companies now have RSS feeds, blogs, YouTube channels, Facebook brand page, Twitter account… Brand content can be shared by consumers or embedded in other sites. Each source and platform need to measured, usually in different ways, leading to multiple data sources that you will have to put together in order to grasp the your full ecosystem.


Secondly, there is also the multiplication of technical platforms as well. Until not so long ago, it was easy as the majority of people used their computer to surf on the Web but now they can access Internet via their mobile phone, their tablets (like the iPad for example), their TV, their game console or even from their car systems. The same person will use different platforms at different moments for different usage, bringing more challenges in terms of measurements and data reconciliation. For example, measuring mobile sites does not work exactly the same way as measuring websites.

The consequence is that online analytics is constantly evolving (and fast), setting new challenges. No time to rest…

 

Don’t despair!

The challenges covered here are just examples. I could keep on enumerating more but this post is already quite long (you can find more for example in last year Econsultancy’s Online Measurement and Strategy Report or in this great post from Avinash) but I guess you get the idea. Web analytics is certainly not that easy, it is not just a matter of having one tool implemented that provides you with tons of sexy reports. Technology is just one of the difficulties with other aspects like organization, company culture, people, expertise and others. Like in many other areas, whenever significant changes are required, you are up for a long and difficult battle. Even the constantly changing nature of the media itself adds its own set of difficulties.

But don’t get desperate – successful web analytics exists (well, I truly hope so – I keep repeating that to myself :-)). All challenges can be overcome. How so? Find out in Part III – “Critical factors for successful Web Analytics

(TO BE CONTINUED)


Do you want to start using web analytics. Or an analysis and optimization of your current web analytics set-up? You can always contact us

This is a repost and was originally posted on www.kaizen-analytics.com 

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