Cresta CEO Zayd Enam on AI That Brings Out Our Best
By: James Kotecki
Tags: Customer Experience, Artificial Intelligence, Business, Technology, Communication

Audio + Transcript

Zayd Enam:

The really big change that happened was with the printing press. Folks could extract the lessons that they had and write it down in a book, and then replicate that book and share it with everyone else. AI is going to become the book that writes itself.

James Kotecki:

This is Machine Meets World, Infinia ML’s ongoing conversation about artificial intelligence. I’m James Kotecki. And my guest today is the co-founder and CEO of Cresta, Zayd Enam. Thanks so much for joining me.

Zayd Enam:

Thanks, James, for the invitation.

James Kotecki:

So as I understand Cresta specifically, what you’re doing is, I’m sitting in a call center, maybe I’m a sales person or I’m a customer service representative, and I’m looking at a screen and Cresta is using AI to provide me with a script of things that I should be saying to the person on the other side of the call. Am I basically getting that right?

Zayd Enam:

Yeah. So what it’s doing is it’s a system that’s constantly learning and listening from all the conversations that are happening and identifying what is resulting in success, measured by sales, conversion. It might be measured by customer satisfaction or average handle time. And it’s identifying what are the behaviors, the responses, what are the best people doing to result in success? And then it’s, in real-time, prompting everyone else, “Hey, here’s what’s being really effective and here’s how to handle this conversation to result in the best possible conversation.” Our vision for companies is that every single representative within the company is armed to be the very best representative of the company.

James Kotecki:

And is it learning just from my company, my reps, or is it kind of an anonymized synthesis of everybody who’s doing that kind of work?

Zayd Enam:

For particular verticals that we go into, we’re able to build a model, 60% of the model based on the best practices of that vertical and industry. So for financial services, identifying what are the best practices of all the financial services companies or what are the best practices of the best SAS companies or the best retail companies. And then the rest of that 40% is company-specific because that’s specific to the product, the knowledge, the promos, the offers, all these companies’ specific information.

James Kotecki:

And what kind of things might it suggest?

Zayd Enam:

It’s a wide range of things. So if it’s a customer support interaction, for example, it might be that it identifies the answer within the knowledge base. So a customer might come up with a question and it identifies where that answer is in the knowledge base and gives the rep that answer. But there’s subtleties to that. Sometimes the way the customers frame the problem is different [than] the way the answer exists in the knowledge base. Just as an example, a customer might say that their mattress has gone flat. If you search within the mattress industry and all the knowledge bases for all these companies, they won’t have any knowledge base for flat mattresses because the words that they use is bladder. And so that’s the word that they use for the internal part of a mattress with these air mattresses.

James Kotecki:

Bladder? Like the human body bladder? Is that what you said?

Zayd Enam:

Yeah.

James Kotecki:

Ok.

Zayd Enam:

And this was just one of those humorous things that we found in the course of deployment. The language that they use is just dramatically different than the way the customer perceives the problem. What we’ve been able to do is really identify how do you map those customer intents and those customer conversations, and the way that the answers might exist in these systems into a shared semantic space.

James Kotecki:

So would you say that you’re using AI to increase human empathy?

Zayd Enam:

I think naturally humans are, I think humans are empathetic. When a person is sort of in between multiple conversations, is trying to find the answer to the conversation, doesn’t have the confidence to know how to answer a customer question, that’s when they become less empathetic. But when they feel confident that, “Hey, I have the systems and the tools to be successful with these conversations, I know the answer here,” then they can worry less about the answers, the technical piece of it, and more on the empathy side of it and how to really connect with the person and understand them and really seek to understand them. That’s the right combination of humans and machines is how do you give a person confidence to give the answer so they can focus on the empathy and building that empathy with the customer?

James Kotecki:

If I was a cynical person, I would say, “Okay, in the short term, what you’re saying makes sense. It’s humans and machines together accomplishing something better than either one of those two entities could do alone.” In the long-term maybe, what one might suspect is that you’re really training a system that ultimately could replace humans, right? Because you’re collecting more and more data about what’s effective, voice analysis and synthesis technology is getting better and better. All of us talk to bots all the time on the phone right now. And so if those bots got more and more sophisticated, one could imagine them replacing more and more of the tasks that people do. So even though you might not be looking at totally replacing people, is the long-term vision to move a lot of people out of these roles so that you only need a few kind of hardcore specialists in them? And you can really eventually, using the data that you are collecting now, automate everything else?

Zayd Enam:

In any company, in any type of work, there’s always more strategic work to be done. There’ll be simple things that can be automated. There’ll be basic FAQ’s like, “what’s my order?,” all these things that can be automated. But there’s actually very strategic roles in any company, and that’s building relationships with customers, really focusing on higher-level strategy, creative things. And that’s what we really want to enable and make possible. The best companies, I think, will invest in these roles from a strategic perspective because they recognize that customer relationships are really the most important thing for a modern company.

James Kotecki:

I suppose another way you could maybe answer that question is “Look, have you ever been on hold for more than a couple minutes? Didn’t you hate that experience? Wouldn’t it have been better if there was a person to answer the phone? And the fact that you were on hold meant that there wasn’t a person to answer the phone. So clearly we still have more jobs for people to do.”

Zayd Enam:

Yeah, absolutely. I actually think there’s a latent demand for conversations in the United States or the world. There would be a hundred times as many conversations if calling your phone provider or your bank was as easy as picking up your phone and immediately getting connected to somebody knowledgeable, a very talented specialist who really understood your problem. The reason you don’t do it right now is because when you call them, it takes 30 minutes to find someone, and they’re not really clear on what your problem is. You need to transfer to somebody else.

Zayd Enam:

And I think in some ways it’s actually a little bit like the car industry in [the] early 1900s. There was a latent demand for transportation in the sense that folks wanted to get from point A to point B, but it wasn’t until we could build efficient cars with the assembly line that everyone could afford cars and roads could be built. And all of a sudden, everybody in the United States could drive a car and get from point A to point B. I think the same thing is holding back conversations where people just aren’t having conversations because they’re painful and they’re just, they’re not solving the things that they want to solve.

James Kotecki:

Okay. So you are one of three co-founders. Can you just quickly tell me what the other two co-founders are kind of bringing to the table and how you work together to put this puzzle together?

Zayd Enam:

My two co-founders are Tim Shi and Sebastian Thrun, who is the chairman of our board. And Tim and I were PhD students together at Stanford, working with Sebastian. And Sebastian had sort of, has a very interesting background, sort of having built the first self-driving car that won the DARPA Grand Challenge and then founding Google X and Udacity, and his sort of mandate to us in the lab was basically, “Let’s go figure out what are the biggest problems that we can solve with AI, and let’s focus singularly on solving those problems.”

James Kotecki:

Stanford, AI, Google X, these are very sexy things. And then when you think, when you tell someone, “Oh, I’m working on technology for call centers,” that might initially to people seem kind of unsexy. How do you see what you’re doing fitting into this broader picture of AI? I’ve often wondered, is AI going to transform the world to make it into some kind of Star Trek utopia, or is it going to basically just make the world a little bit better so that I have more good days that I recognize? I have fewer crappy experiences on the phone with a customer service rep, but it’s not creating some holographic doctor to solve all my problems.

Zayd Enam:

I generally believe that the vision for Cresta is, perhaps, probably the largest possible vision that you could have with AI. For us, the recognition was that the biggest impact that artificial intelligence will have is it’s a machine that will learn from the very best of any team, of all of us, identify what traits are we being successful at, and really coach and improve and share that knowledge with everyone else.

Zayd Enam:

And so if you look at it before, the way this was done, you have cave paintings and folks sharing knowledge through these — kind of talking to each other. And the really big change that happened was with the printing press, when you had this — when folks could sit down, identify and extract the lessons that they had, and write it down in a book, and then replicate that book and share it with everyone else. But the challenge there in these books is it’s actually really hard to write a book, like sitting down and extracting what’s happening and identifying what’s happening, and then you have to write it and then folks have to read, have to absorb it. And in some sense, what we believe is AI is going to become the book that writes itself, where it’s constantly learning and identifying what are things that are successful and what is the knowledge to extract from each example — training example in the world.

Zayd Enam:

And we’ll build these networks that identify these things and then are able to distribute them in a way to everybody in the world that’s helping them live in the moment, coaching them in those conversations, identifying how do we distribute this knowledge to everyone. It’s not just in the call center, it applies to every type of knowledge work and every type of office work. We think that’s the biggest thing that we can impact.

James Kotecki:

Zayd Enam, CEO and co-founder of Cresta, thanks for joining us today on Machine Meets World!

Zayd Enam:

Thanks James, it was such a pleasure to be here.

James Kotecki:

Thanks so much for being part of the conversation, and don’t forget you can email the show: mmw@infiniaml.com. You can also like this, share this, rate this, you know what to do! I’m James Kotecki and that is what happens when Machine Meets World.