Web Analytics from a Czech Point of View

December 7th, 2009 by Lars Johansson

An interview with Jiri Brazda, web analytics expert and founder of Optimics.

What’s the web analytics market like in the Czech Republic?

We tend to say that when it comes to the Internet, we are generally three to five years behind the US market, and I think web analytics would be no exception. I think web analytics adoption here suffers from the fact that marketing has problems with appreciating the value of data when making business decisions.

I always remember one day a couple of years ago when my boss, who then worked as a marketing manager, told me how desperate he was because his work life had been all about spreadsheets and numbers, and he hadn’t seen a picture in ages. Now I think this story is telling as to how traditional marketing perceives itself.

Many marketing managers are comfortable with the brand and communication part but struggle with the performance part. And I know it’s up to us to educate the market. I think we have to emphasize the optimization over reporting role of web analytics, because I can see that only increased performance can really sell web analytics. And it’s true of both the tool and the services.

This year has been a major breakthrough for the Czech web analytics market. First of all, I started local Web Analytics Wednesday with much help from Eric Peterson, and it’s proved a tremendous success—not so much in terms of the numbers, compared to what you get over in Scandinavia for example, but in terms of forming and building a community that was already there but no one before had attempted to put it together.

The vendor market has been pretty much all about Google Analytics so far, and this year the first three companies were accredited GAAC. There are now also three members of YWACN in the Czech Republic. When it comes to the paid solutions, there are a few locally driven Omniture implementations, but the other vendors, such as Webtrends or Coremetrics, are unheard of. It’s clear that the market size plays its part here. It should also come as no surprise by now that I know of exactly two companies that have a dedicated full-time web analyst.

What are the main differences between working with web analytics in the banking and insurance sectors, and as a consultant?

Wherever I went as an employee, I was trying to champion an analytical approach to online marketing, and how much I succeeded was always due to the role the Internet played in marketing and sales of my past employers. Of course, a bank that targets affluent customers and prioritizes serving the customers through personal relationships perceives the Internet differently than an online insurance company.

One common thing I’ve learnt, though, is that it’s always better to deliver results in order to promote analytics rather than present a fancy report and let the management drown in its meaning while dissecting metric definitions, which used to be a popular pastime at our meetings.

Being a consultant, I get to work with companies that are generally a step further in their analytics maturity (at least from a demand perspective), and I get to enjoy a wider variety of context situations, which helps me accelerate building my proficiency and expertise. It’s certainly one of the best moves I’ve ever done in my life.

How are you combining web analytics, usability, and such in your consultancy these days?

Even though we position ourselves as the first pure web analytics and optimization consultancy in the Czech Republic, we tend to sell primarily optimization and results. There’s virtually no demand for web analytics, so we’re pressed to sell increased performance. And I see this is as a good thing.

The ongoing debate in the industry is that the data has almost no value unless you derive insight and take action on it. In my view, the debate stems from the fact that a lot of companies often tend to go on hyperbole, and so they spend money on web analytics without first thinking that they will need people to use the tools, bring insights and deliver results based on the insights in order to pay for the investment in web analytics.

On the other hand, the situation here in the Czech Republic, and I believe it’s true of the whole Central and Eastern Europe region, is that we have spent no money on the tools, so we are in a unique position to be able to skip that initial phase. John Lovett of Forrester (comment: now Web Analytics Demystified) describes what he calls investment, staffing and action chasms. It seems like we should first deal with the investment chasm and proceed from there, but I think we can learn from the mistakes of the markets that are ahead of us and sort out the investment chasm while dealing with the action chasm right away.

I’m saying this because for our optimization services, we take web analytics as one of many sources of data. You absolutely have to complement quantitative data from web analytics tools with qualitative data from customer surveys and user testing in order to suggest changes to a website that can stand a chance of improving its performance. And that’s where our skills and experience within information architecture design come in.

It might be due to the overall market maturity when it comes to persuasive websites that sell, but time and again we prove that, based on the data and knowledge we collect, we can suggest changes that directly and very quickly improve website conversion performance. And we use only A/B and multivariate testing to improve the conversion further over a longer period of time.

What is the most exciting development in the web analytics industry since you got involved in it?

Let me narrow it down to the Czech perspective, and I won‘t hesitate a second and say it’s my company—Optimics. But seriously, you mean the whole industry, right? I think it’s the emergence of a number of factors; some of which are already tangible, and some of which are just poking around and struggling to be heard:

1. Adoption of free tools (such as Google Analytics)

2. Introduction of some sort of artificial intelligence either bringing new data or making analysis of data easier (such as NextStage Analytics and Google Analytics Intelligence)

3. Bridging the gap between analysis and action through automation (this I think is just an idea at the moment, but I find it very powerful)

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