Sramana Mitra: That’s the modus operandi from the point of view of your large customers. Do you have customers who are independent software vendors who are also developing on top of your analytics platform, and are providing the business logic for maybe a particular vertical and then selling?
Sramana: Was Terapeak based in Toronto as well? Kevin North: No, it was based in Victoria, BC. It was on Vancouver Island. Sramana: What was the financing strategy of the company before and after?
Sramana Mitra: You seem to have a regional emphasis. Does that mean that your sales cycle has been an in-person sales cycle? Mike Carter: Yes. Traditionally, our sales process has been person to person. We have invested quite a bit in our digital presence and we are doing things from creating ourselves as an inbound
Entrepreneurs are invited to the 215th FREE online 1M/1M roundtable mentoring session on Thursday, May 15, 2014, at 8 a.m. PDT/11 a.m. EDT/8:30 p.m. India IST. If you are a serious entrepreneur, register to “pitch” and sell your business idea to Sramana Mitra. You’ll gain straightforward feedback, advice on next steps, and she’ll answer any
In case you missed it, you can listen to the recording here:
Paul Zolfaghari: For instance, yesterday I met one of our customers Netflix, which is actually running MicroStrategy against a very substantial instance of data that actually resides in AWS. Netflix is very public about this. It’s a great example for us and one that we’re very proud of. Netflix is a deep analytics company. It’s
Last November, Aileen Lee with Cowboy Ventures 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
Sramana: What was the state of the company when you came in? Kevin North: There were some really good people who had been making great technology. The founders were great and they understood Big Data very well. The only issue was that their organization was not scalable. The goal was to turn it into a