Data Visualization practice

After writing recently quite a bit about the importance of Data Visualization (and even the beauty of data) a lot of marketers have started to ask me: How can we build such a practice without investing a huge amount of dollars?

I rarely have a straightforward answer but my experience taught three things. First, one has to bring together three different functional expertise areas in building out such a practice:

• Data Strategist. This is someone who doesn’t need to be a statistician but someone with strong marketing strategy capabilities and high data affinity. This person is the bridge between the analytical hard core geek and the rest of the world
• Techie. Someone needs to own the build out and implementation of the necessary underlying data infrastructure and applications. This techie needs constant communication with the data strategist to ensure that he is not developing anything off strategy. It’s all about rapid development with instant feedback loops. No development should take more than a couple of days before immediate review by the rest of the team.
• Data Designer. Here we need someone with strong creative background who is able to transform data insights into innovative visuals with meaning. This person is the most difficult to find and challenging to train. There are not too many role models out there, it’s a totally new discipline that we have to define over the next years.

Only the joining of all three experts will enable the right end product. There is no real lead within this triumvirate; it is rather as Tim O’Reilly describes the phenomena of “Harnessing of the Collective Intelligence” within this team and hopefully beyond.

Secondly, I have learned that one productive constraint is the low amount of available dollars for hard and software. This visualization practice should not have a significant capital expenditure budget but should get used to work within very tough financial constraints. I rather recommend investing money in the right talent than in fancy tools and hardware solutions. Financial limitation should be the breeding ground for innovation.

Third, the first projects of such a data visualization practice should be client driven. Ask yourself which client of yours (internal or external) has an urgent challenge or question that you would like to answer with data driven insights. Then you challenge the whole team of coming up with a solution. It’s important to realize that the final visual result is not the result of one brief individual genius stroke but the end product of a painfully labor intensive process with dozens of versions and iterations within this team. Think endless prototyping, think team tension to create a powerful end product.

These three learning can enable any marketing team to slowly build out the right visualization practice without investing millions of dollars. It has not been done too often but it will be required to be a best in class marketer. Enjoy building it.