Sramana Mitra: I’m glad you segued us in here. I’m a little bit uncomfortable with the level of sensationalization that goes on on this issue. The issue is a lot more complex and somewhat scientific than it’s made out to be. The truth is the venture-funded businesses tend to be technology-heavy businesses.
There is a lack of women in the technology industry. It is a function of the fact that there aren’t enough women in STEM. Whereas the bootstrapped entrepreneurship world is full of women because the types of companies are different. You look at e-commerce. There are hundreds of thousands of e-commerce businesses out there and many of them are run by women. It’s a very woman-heavy category.
The kinds of companies that are getting funded by crowdfunding typically are not technology companies. They are other kinds of businesses. It’s natural and it makes sense that women are finding more options in those areas.
Ann Winblad: I would add one thing there. We don’t do direct to consumer funding. I do have a number of companies that come my way and say, “Who should I talk to for my direct to consumer business?” When you think about some of the higher profile marketplaces, for example, many of the customers of Airbnb are women.
The bigger companies, even if they’re in marketplaces and commerce, the message I would say to women is, they’re going to need some technical chops. If they have it on themselves, they’re going to have an unfair competitive advantage. If they don’t hire them early, they’ll have a real disadvantage. At some point in time when you start a company, there is not a customer engagement model today that doesn’t involve a digital engagement for the future.
Major enterprises are transforming their whole enterprise to have new digital customer engagement platforms. Women, even if they don’t have STEM majors, are going to end up dealing with engineers. Post graduate or whatever, it doesn’t mean that women need to learn how to code. They should really figure out how to communicate with an engineer. How do I hire an engineer? How do I get into the digital transformation of society as a whole?
We can’t start separating women from technical and non-technical. It’s important to communicate to men and women who don’t have STEM degrees that they’re in a STEM world. They may not be writing code, but they’re going to have engineers working for them.
Sramana Mitra: Right. I’m fully with you on that. In my thesis on the evolution of the web, if you want to do Web 3.0, the way I see it, it’s personalization-heavy. Personalization can only be done at scale with very serious machine learning and AI technologies. If you want to deliver value with a user experience that is heavily personalized, you have to learn all that.
Online fashion is a very popular category right now after many years. I started one of the first online fashion companies a long, long time ago. Now it’s a hot category. It’s a category that naturally lends itself to women founders.
Today, to deliver a differentiated user experience, it’s not sufficient to just know merchandising. You have to know merchandising. You have to know branding, but you also need technology. Those are the three legs that have to come together in the founding team to deliver a really compelling user experience.
Ann Winblad: Everybody should read your book. It’s a great book. It’s very readable for a non-technical person. The reverse of that is every enterprise now realizes that the consumer expectations for engagement are very high. A consumer doesn’t want to be treated as a party of one. They want to be dialoguing with you via any device at any time.
This has been a very rapid change in driving many of the technologies we’re investing in. I’ll give you a great example here of a company that we funded in Utah fairly recently. They’re calling companies that grow really fast unicorns. It is one of those unicorns. It is also approaching about 350 employees now. They built a machine learning platform for something very simple, which is inside sales.
I once had a job as a telemarketer. My screen would come and tell me, “Make these calls in this order by this time. Here’s a little bit of information about the customer.” This machine learning platform which is in the cloud tells you also about the compute power that the cloud is able to do right now. It’s a machine learning platform that brings in all sorts of data including weather. If I’m sitting down and I’m an inside sales user, it has probably already told me that the power is out. There’s a horrible storm. People are going to be pre-occupied in the Bay Area today.
If it was a sunny day, it would say, “You should email before 8 o’clock in the morning. Don’t try to reach her after 8:30.” It’s a different engagement model, which is different than the next person. It would also say, “There’s a news event in this place. People are going to be distracted by that. It’s not a good time to call.” It brings in all the external variables as well as the personalization variable to know exactly when and how and when I should engage with each individual. It continually learns because it’s a machine learning platform.
When we talk about building a digital engagement platform, this is not a fixed target. This is a rapidly moving target. Getting in that learning stream gets your prepared for putting your head around how rapidly the personalization models and the technology under them will be able to respond to customers and engage them.
Sramana Mitra: Super! It’s been a great discussion. Thank you for your time.