Today we welcome Ekta Chopra, a Visionary IT Executive and Digital Expert who has invested her entire career in transforming private equity-backed companies with cutting-edge technologies, high-performing teams, and digital technologies.
With over 20+ years of Technology experience from private equity and retail companies, she joined E.L.F. in 2016. Before having her current job as Chief Digital Officer, she worked as Director of Technology of the James Irvine Foundation for three years, where she was recruited to drive a complete transformation of IT team, systems, and operations for this foundation committed to enhancing the quality of life for people in California. Before that, she served as VP of Technology for Charming Charlie, a specialty retailer that grew from 17 to 120 stores nationally.
Ekta holds a B.A. in technology & operations management and a minor in finance from California Polytechnic State University. She is also a member of Silicon Valley CIO/CTO groups as a thought leader.
Question 1: First Job: You’ve been a digital officer for a while, could you talk a little bit about your background and how you got to the position where you are now?
I was born in technology; a tech geek from the beginning. But I had the opportunity to work in many different domains from aerospace to private equity, to women’s fashion accessories to reporting to the chief investment officer for a foundation, to getting my dream job at E.L.F. Beauty, which truly has been like a rocket ship. And that’s what we like to call ourselves: we’re sort of on this rocket ship with a lot of superheroes doing some really amazing things.
So, you know, I moved away and pivoted a bit from information technology to digital transformation in an era where e-commerce was really pivoting from tech to digital. And that’s something that I’ve been able to embrace and really grow at. So that’s, in a nutshell, my journey.
Question 2: Generative AI: You’ve had a long journey working digital strategy, could you put a little context around Generative AI? How does all this fit together? It isn’t necessarily a brand-new thing, but an evolution, right?
Absolutely. I’ve been doing what we call power-up sessions at E.L.F. to educate the whole company. And I’d say 1956 is when generative AI was born, essentially. It has had many evolutions over time. So, AI has been there for a long time. ChatGPT just made it very accessible in 2020. And today it almost seems like, you know, every conference, every boardroom, every investor is thinking about it. This is an evolution. Not a revolution, but an evolution.
Now is the time to find a way to really embrace it, because it is something that I see has a lot of potential from a consumer lens, which, as you know, is very dear to my heart. But then, as a public company, I also must think about it from an employee efficiency and employee experience perspective. I think it has tremendous potential.
It sounds like it’s becoming a higher priority for you and your business. Where does it fit in the prioritization you mentioned? You’re getting looked at by Wall Street, I’m sure your board is asking for more things. How high priority is it?
It’s really high priority for us. But I would say that we have already been doing a flavor of it. So, if you think about our digital business, it’s doing extremely well year over year. E.L.F. has had 18 consecutive growth quarters. We’re now the number one favorite Gen Z brand, and you don’t become the number one favorite Gen Z brand unless you really understand your consumer. So that comes with offering personalized experiences. But AI will allow me to offer hyper-personalization, which I’m really excited about when it comes to E.L.F.’s products.
And if I think about that and put it in perspective, the amount of creative, the brand messaging, and the content that you need, is exponential. How do you do that? You know, it’s not humanly possible without hiring a bunch of folks. So how do you do that effectively with either co-pilots or for your everyday content? You need a content supply chain that’s driven by AI.
I think that’s where I feel a huge opportunity, from a productivity perspective and really engaging our consumers. So that’s been our focus area as I think about our journey and acceleration.
Extra question: Could you talk about some early learnings, or what you have experienced in the effort of having more data and getting closer to your customer and understanding their needs?
I think the early learnings really are: ‘You have to be grounded in reality.’ There is, of course, all the excitement and the innovation that’s been possible since 2020, but I think there’s also the reality of us being a public company.
So, if I think about our focus areas and how the learnings have shaped them, it’s leveraging this concept of prompt engineering. And it’s also about education: getting everyone in the company comfortable with co-piloting using AI. It’s really important, right? If they don’t know how to ask the right questions or prompts, they’re not going to get the right results. And you’re not going to be able to train the AI the way you want to on your brand, voice, tone, or your own persona as an employee. So that’s number one: educating and getting our employees trained on it.
Second, whether it be Microsoft, Slack, or Salesforce, everyone is coming out with co-pilots. So, we need to test and learn. We can work with existing vendors to be the guinea pig in some cases, because as long as they’re trusted vendors and we’re being mindful about our use cases, it’s a good use of our time.
The third piece is that we have to consider where it makes sense to plug in some of platforms that are already built for certain use cases versus building new things ourselves. For example, why do we need data analysts? Why couldn’t we build something to provide access to our data at the fingertips of different people? This would have the potential to create a lot more speed an actionability.
Furthermore, there’s not just one model. You have Llama, you have Bison, you have Open AI. Each one needs to be trained differently, so they won’t necessarily train the same answers, or react to the same use cases in the same way. So how do you play around in that sandbox?
And finally, AI governance and security enhancements are critical. You can’t afford to not be thinking about them, especially as an enterprise leader. So, we need to stay grounded in those realities. There are things where we’ll go deep and things where we’ll just tiptoe a little bit and just test and learn.
So, is that a planning exercise? Or is it really just better communication throughout the entire project?
Great question. It’s a combination of both. You start with the planning, and then you take it all the way through execution. And you build the muscle memory so that it becomes almost second nature that you must communicate. So, it’s a planning thing as well as a communication thing.
Question 3: New metrics: How will you measure success? You’ve got both internal productivity opportunities and then you’ve got consumer brand, and of course, customer adoption. So, what are the unique metrics that generative AI is creating for you?
I think it falls into three buckets.
One is: “What impact is it having on our business?” And that could range from increased revenue, new revenue streams, reducing cost of how you serve, or your consumer, or things like improved consumer experience through the implementation of chatbots. The impact on your business is very real and quantifiable.
Then there is technical feasibility. Is it really technically feasible? Is it costing you too much? You know, as you try to build these cases, you have to also take that into consideration.
And I think the third is availability of data. You have necessary data models that you’ve trained to get solutions that are actually making an impact. So, you have to be able to measure it. You know, we have many use cases right now that we’re trying out, and some of them frankly don’t even make sense. They’re not even AI use cases. I think it’s about evaluating where the juice is worth the squeeze.
Bonus: What are some of the technology gaps or issues you need to address when thinking about all this from a venture capital perspective? Where would you like more investment? Is it more about technology or are people and process more of the gaps for you?
I would say it’s not one thing you know? My Head Developer or Engineer would say there’s always a caveat. So, in this case, there’s a great degree of complexity. There are technical challenges, of course, which are huge. How can you really make this technology fit into your ecosystem and work with many of the other platforms?
Then, there are data challenges. You’re working with a huge amount of data. How do you build something that is going to move at the speed of the business? We work at E.L.F. speed. So, for me, it’s really important that whatever I bring in can actually move quickly.
And then there are ethical challenges. As a brand we’re extremely grounded in our purpose. E.L.F. is for every eye, lip, face, and skin concern. I cannot discriminate. So, how do I make sure that the models I’m building are ethically right, that we’re serving the consumer the right color shade, matching, and so forth? And we really want to make sure that we’re very sensitive to that.
And of course, the nice bow on top is security and privacy. That’s always a concern as a public company. I would never even consider prototyping or doing something that already inherently might have security concerns around it.
And then of course, an issue I know my employees are concerned about is how this is brought into the organization. Are you doing this to get rid of jobs? And the answer should be no. It’s to make sure your smartest people are as effective as possible, and you’re actually making their jobs easier. So, the framing of that is so important as well.
Question 4: What’s a generative AI takeaway. If you had to tell Grandma what Generative AI is, how would you go about describing it?
I would say it’s like a Magic 8 Ball because you don’t know what’s happening on the inside. But it’s a more effective Magic 8 Ball that is capable of providing you precise information, depending on what you’re asking. And the more you engage with it, the more fine-tuned it is to what you’re looking for. It’s going to improve the broader quality of the work individuals are doing inside the business, and can serve in many new revenue streams, while creating new ways to engage with consumers.
Ekta Chopra is a Visionary IT Executive and Digital Expert who has invested her entire career in transforming private equity-backed companies with cutting-edge technologies, high-performing teams, and digital technologies.
Digital Expert, Metaverse and Web 3.0 enthusiast, Board Advisor with experience in private equity and retail, she has over 20+ years of Technology experience. She has invested her entire career in transforming private equity-backed companies with cutting-edge technologies, high-performing teams, and digital technologies. She also leverages cutting-edge technical solutions to maximize operational efficiency and drive unprecedented results.
She currently works at E.L.F. Beauty as Chief Digital Officer. Ekta holds a B.A. in technology & operations management and a minor in finance from California Polytechnic State University. She is also a member of Silicon Valley CIO/CTO groups as a thought leader.