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Starting Unicorn Companies: Tableau Software

Posted on Monday, May 12th 2014

Last November, Aileen Lee wrote a post on Techcrunch titled Welcome To The Unicorn Club: Learning From Billion-Dollar Startups. In it, she offered a list of companies that have had billion dollar exits, and analyzed some of the common threads.

In this series, I would like to look at some of the ‘unicorn’ companies that she identified, as well as some others that I know well, and one by one, explore their early stage entrepreneurial journey. The case studies we explore are all from the 1M/1M Entrepreneur Journeys series of interviews.

Also, we will have a live discussion on each case study at a 1M/1M roundtable soon after we publish.

We begin with Tableau Software, currently trading in the public market under the symbol DATA with a ~$3.5 billion market cap.

Christian Chabot, the founder CEO of Tableau is from Milwaukee, Wisconsin. He arrived in Silicon Valley to study at Stanford, and got inspired to become an entrepreneur by Irv Grousbeck. Soon after graduating from business school in 2000, Christian founded BeeLine Software that came up with a better way of doing digital mapping. The company only had 3 people, and was sold in 18 months to Vicinity, offering the founders some early cash.

After a couple of years at Softbank, Christian started Tableau as his second venture in 2003. He and his two cofounders from BeeLine had cash with which to bootstrap Tableau for a while. He already had some deep insights into a problem he had encountered as a data analyst at Cornerstone Research. This problem had to do with visualization of structured data from databases, a technology already being incubated in the Polaris project at Stanford.

“Almost all visualization of data, even today, follows the same archaic model. First you open some data with a query interface and you work with that data. You analyze it, dice it, and pivot it, all in text form until you get what you would call your answer. Only then do you put it into some kind of chart wizard. Once you get your data points into the chart you have an end result, which is data translation. And what happens next? You look at it and say, “That’s not what I wanted” or, “That’s what I wanted.”

Your brain is naturally curious about data whenever it sees it. The problem with the whole paradigm to understanding data is that the visualization comes last. By then it’s too late. If you have a new hunch or angle, then you have to go back and do the whole process again. The idea behind Polaris was to query a database using a picture, to be able to sort, filter, zoom up, and pivot it through a purely graphical interface. When you do it that way you are working at the speed of thought. By dragging and dropping after viewing some of the data on a canvas, you are actively querying it. That lets you generate pictures of it at the same time.”

Christian had insights into the problem as a user. And he had really strong computer scientists as cofounders to figure out the solution that he envisioned. To that, they added a powerful set of cross-domain expertise: “They say that the greatest innovations are born from strange bedfellows. In our case it was PhD’s in database optimization, data structures, and data queries, married in the lab with people who had PhD’s in computer graphics. These are groups that even talk to each other anywhere else. They definitely don’t collaborate. That is one of the reasons that we have the IP we have today.”

Cross-domain innovation tends to produce strong, defensible competitive advantage.

The Tableau team licensed the Polaris technology out of Stanford for a small equity, and very quickly started selling to real customers. The first 100 customers gave them immense validation.

At this stage, there was no investor involved. In fact, for two years, and 200 customers, there was no investor involved. In effect, they bootstrapped.

Then they got a mammoth 4-year OEM deal with Hyperion including an advance.

At this point, Tableau raised $5 million from NEA at a $20 million pre-money valuation. The average pre-money range at the time for Series A was $5 million. VCs love to come to the rescue of victory.

Revenue ramped very well. In 2004 they did $800,000. That rose to $2.1 million in 2005, $3.7 million in 2006, $7.8 million in 2007, $13.9 million in 2008, and $20.1 million in 2009.

Tableau went public in May 2013 raising over $250 million at a $2 billion valuation.

You can read the full interview with Christian Chabot here.

We will discuss the case study on Thursday May 15 at our free online strategy roundtable.

This segment is a part in the series : Starting Unicorn Companies


. Tableau Software
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