Building a Cool Technology Company from Chicago: Narrative Science CEO Stuart Frankel (Part 6)

Sramana Mitra: Do they pay a subscription?

Stuart Frankel: Yes. I’ll tell you how much the business has evolved. Given our customers today and given what we do, it’s a much more relevant model for us rather than selling volumes of content. When we were creating news content, that’s how news content is bought. That’s how we sold it.

Sramana Mitra: You said you got some early customers. Are we talking of 2011?

Stuart Frankel: 2010.

Sramana Mitra: In 2010, you got some customers and you were selling to them in this per piece mode.

Stuart Frankel: Yes, we were. We were starting to understand where those pockets of opportunities were. We obviously did a lot of evangelical work at the beginning of this company and started the conversations by breaking the news to people that this kind of technology existed because nobody had done this before. We had lots and lots of conversations with different organizations. There was a lot of disbelief. There was a lot of doubt that Quill could do what we said it would do.

Once we started getting a few customers as well as product and market validation, people started to take the business much more seriously. In fact, during this time, we started to get a lot of press in large well-read publications. The theme was, “Here are these robots and they’re doing what people can do.” I think most reporters would start out wanting to conclude that the technology didn’t work. Almost two of the reporters concluded that this works and that they’d better up their game. That press coverage actually created enough awareness around the company, not only with other media companies but with all kinds of organizations across every industry.

We started to get a lot of inbound inquiries from financial services, marketing services, retailers, manufacturers, governmental entities. They were all describing the same problem. The problem was and is, “We have spent a fortune on our data initiatives. We’ve got as much data storage as you could possibly manage. We’ve got business intelligence tools and applications. We have visualization packages where we can create beautiful charts and graphs but in the end, we’re still not necessarily getting a return on that data. We’re not necessarily using that data to improve our business in a meaningful way.” We knew this to be the case but this was really the validation that we needed, which was that there was a lot of growing disillusion with the state of data and the promise of Big Data and the failure of Big Data to meet its promise.

We started working with companies and their proprietary data to help them with their reporting needs. Over the last couple of years, that’s where the business has moved. While we got customers across many different industries, the bulk of our customers are in financial services. We work with members in the US intelligence community through our relationship with In-Q-Tel, which is the CIA’s investment arm. We’re doing a lot of interesting things with a lot of interesting companies. We’re working with large enterprises. We’ve got about 60 customers today. The problem that I just described is becoming more and more acute. We’re seeing more and more demand for it. Companies don’t want another tool set to enable their employees to hunt, pack, and look for the needle in the haystack. What they want are tools and technologies to allow employees to be more efficient.

What we’re aware of and I’m sure you’re aware of, when you think about how people work today, a big part of everybody’s job is to actually figure out what’s going on. If you’re running a sales team, you want to know how your sales team is performing. What are they selling? How are we doing against our forecast? If you’re a financial advisor, you want to know how is Mr. and Mrs. Jones’ investment portfolio performing? The reason you need to know that is one, you need to do your job but two, you probably have to communicate that to somebody. We spend an enormous amount of time now going from data to some type of written document.

A big part of everybody’s job is looking at a spreadsheet, figure out what’s important and interesting, dumping that into a PowerPoint presentation or email and communicating that. As we store more and more data and want employees to access that data to make better decision making, they’re going to spend more and more time on those manual tasks of going from data to story. Quill can automate a substantial piece of that. What Quill does is it actually takes those tasks and allows employees to spend time on higher value work. If you’re a financial advisor, you don’t really want to spend your time writing up a portfolio summary for each one of your customers. You want to figure out what investments they should be holding and how you should manage their portfolio as opposed to reporting on it.

Sramana Mitra: I have a number of questions. There are certain verticals where what you’re offering is more valuable than others. You gave the example, for instance, of financial advisors. Is that a major segment for you? What is your vertical penetration?

Stuart Frankel: Let me tell you a little bit more of what we do. I mentioned that financial services is a big part of our business now. It’s a little bit over half in terms of our revenue and the number of customers. We work with organizations like American Century, USAI, MasterCard and a bunch of other companies. What we do with those organizations and how those organizations use Quill falls into a couple of different buckets. We started to create products on top of Quill. We got an investment research product, for example where organizations like Credit Suisse can embed our reporting functionality into a reporting interface that they make available to their customers. Credit Suisse has a SaaS product for equity research called HOLT. If you’re a customer of HOLT, you log into HOLT, enter a ticker symbol and up pops a very nice analysis in the form of a table and visualization about a stock. There’s a button called insights. You press that button and a research report is generated, which looks like a person created it. That’s done dynamically and is available for each equity in the database.

We have a number of other companies that use the technology in that way. One of our more recent products is is something called Institutional Portfolio Commentary, which has been in market for about a year  If you hold a mutual fund, you’ll appreciate the fact that, at the end of every quarter, what is available to you is a summary of performance of the funds. Every fund, for marketing and regulatory purposes, prepares a performance summary. This is a manual process. If you’ve a large family of funds, you might have 10 or 20 people who’ll spend a few weeks at the end of every quarter preparing this analysis and writing up these portfolio summaries and the results of the portfolio for the quarter. We’ve automated that entire process. We’ve got a product that sits on top of Quill that takes performance data, attribution data, macroeconomic data, and generates within seconds, in perfectly written English, a portfolio commentary report. There’s an increase in efficiency and time to market. Again, it’s a great example of how the technology is being used to free up time that people are spending on tasks that they shouldn’t be spending their time on.

This segment is part 6 in the series : Building a Cool Technology Company from Chicago: Narrative Science CEO Stuart Frankel
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