Former Senior Vice President at Alteryx
Mike has 35 years experience selling enterprise software. He is the Former Senior Vice President of Customer Success at Alteryx where he was responsible for rolling out the land and expand strategy for the business. Previously, Mike was VP at Quest Software and spent 2 years at both Marketlive and Datasweep in the early 2000’s. He enjoyed 3 years as Senior Vice President at Portal Software which was later acquired by Oracle and started his career in 1988 at Sybase, a SAP company today. Read more
Can you provide a short introduction to your experience and role at Alteryx?
I've got about 35 years’ experience in the enterprise software business and I’ve seen a variety of technologies and applications through the years. As my career evolved and I finally wound up at Alteryx, I thought it was a very interesting opportunity to have this focus as the Senior Vice President of Customer Success on really helping clients understand the technology and then build all the enablement around the land, expand and retention strategies. It was really a customer focus and providing them the tools of training, professional services, technical support and technical pre-sales.
What was the original value proposition of the platform Alteryx was offering?
If we think back 10 years ago, in the marketplace at that time for analytics, you had the big stack vendors that still exist today, but it was dominated by IT; it was dominated by technologies which, while they were very powerful, they required professional developers to implement. Often, what would happen was, you would give your requirements as an end user and then those requirements would come back in the form of a dashboard. By the time you got them back, it could be two, three, four, five months and perhaps the business problem had changed.
So along comes a tool like Alteryx, and some others like Tableau, that gave that the tool directly to the business analyst who understood the problem, who understood the data that they were dealing with but now, they had a tool that could provide them answers without any programming or any IT support. That was the fundamental problem that Alteryx was solving. They gave that analyst who knows the business problem, who knows their data, the ability to self-serve to solve their problem in a timely manner.
This is on-premise hosted solution?
It is on-premise hosted and we can talk about cloud later. Where the data or where the tools reside is less important than who's actually developing these solutions. Is it someone in IT who is very technical and very good at writing Perl or Python, or is it someone who lives in the business every single day and is trying to solve a real problem in a timely manner?
That's where our market has moved, whether it's Tableau or Alteryx or other products, it's getting those tools into the hands of the people who really understand the business problem.
Can we just take a step back and explore how the analytics platform fits into the full enterprise stack with visualization tools, databases and so forth?
This is something that Alteryx really figured out early. The components you just mentioned are all that; they’re just components. Part of the challenge is when people were trying to build these solutions, you had separate tools. You had the problem of, how do I get my data into the database and then how do I analyze it and then, finally, how do I visualize and display it? Oftentimes, they were different tools and they were different people with different priorities. You had this kind of production chain here, but not everyone was aligned and if you're the analyst, you're waiting for your data to get loaded. You're then waiting for it to be somehow cleansed and then some macros run to analyze it.
That was how all these products fit together. They take out all the seams of those different components, put it into one single tool with a common user interface without any programming and it's just putting the power of those tools into the hand of the analyst, who really understands the problem. That's where it all fits together. It eliminates the seams of the data prep and analytic process.