Scott Litman is an entrepreneur in search of new ways that technology can advance the mission of chief marketing officers, advertising, and media agencies. Litman and his business partner Dan Mallin have a broad history of building businesses that help clients, including Fortune 1000 marketers and large ad agencies, take advantage of cutting-edge digital transformation.
We’re tech trend watchers. We saw technologies emerge to give professionals in some fields the ability to unearth crucial insights from massive amounts of data and convert those insights into strategies. That’s our goal at Equals 3.
Tell us about your journey into Artificial Intelligence? What’s the idea behind launching ‘Lucy’?
As a veteran entrepreneur in marketing services and ad tech, we’ve had a front row seat to the explosion of data available to marketers over the years. Data in various databases, data from subscriptions and data that’s in the tens of thousands of PowerPoints, PDF’s and Word documents floating around a company’s file systems. And as a matter of perspective, think about that data from 5 years ago and then 10 years ago.
If you could graph the volume of data over time, most would draw a hockey stick. So that’s the challenge we were contemplating. And then about 3 years ago, we saw that IBM was taking the billions they’ve invested in AI and making it available to third parties as API’s and Services that developers could utilize in building apps. My partners and I began to explore the opportunity to apply AI in solving this problem and we began to recognize that we could tackle these huge data problems in areas like Knowledge, Audience Analysis and Media optimization.
Lucy is a unique creation of Equals 3 with six patents pending and includes components of IBM Watson. Her architecture includes our unique IPs along with some of Watson’s APIs and services.
When developing Lucy, we looked to partner with an IT leader offering cutting-edge cognitive capabilities and a global cloud hosting platform. After evaluating different options, we chose teaming with IBM for support. We found the Watson technology was the most robust and varying in its offerings, and IBM had a specific roadmap for continuing to develop cognitive offerings. Since then, we have continued to collaborate with many IBM business units to introduce Lucy to their clients. It has been a great partnership. In fact, last September IBM announced Watson Advertising with Lucy as one of its cornerstone product offerings.
How does Lucy leverage AI to deliver better marketing experiences across the organization?
Finally, with Lucy, there is a technology that leverages every asset of data, combing through more data in minutes than an entire marketing team could go through in a year — unlocking, democratizing, and making it instantly accessible to those who need it. She allows marketers to leverage the entirety of the enterprise data to make quicker, more informed decisions across the board.
For example, when an organization is rich in valuable data, pulling out the information can be incredibly time consuming. Marketers tasked with reoccurring reports or repetitive research processes have little time left for real analysis by the time the data is captured and assembled. Lucy can automate these workflows and deliver reoccurring key information instantly — turning what used to take hours, or days, into minutes. By automating these time-consuming tasks, Lucy delivers a boost in productivity and more time for strategic insight.
How do you make AI deliver economic benefits as well as social goodwill?
AI allows you to maximize vast amounts of data to make more informed decisions, pinpoint where to take action and improve productivity. This same technology can be applied to any real-world problem that could benefit society as well. My partner, for example, leads development of the Monkey Doodle instructional program for Literacy Matters. The Monkey Doodle learning program uses an AI, research-based curriculum and follows the Orton-Gillingham instructional approach. The program provides engaging, kid-friendly literacy instruction and assesses a student’s learning advancement in real time. By understanding students’ individual differences and progress, they receive personalized instruction, which improves outcomes. They also flag potential learning disabilities, allowing for appropriate RTI/early intervention.
Would AI close the gap between media planning and customer experience along the marketing journeys? How does Lucy work to build audience segmentation for better media planning/buying?
Here’s the challenge we solve with Lucy’s Media capability. Modern marketers use many channels to deliver their messages to their audiences – typically relying on specialist to manage any given channel of marketing (search, programmatic, social, retargeting, marketing automation, various forms of TV etc).
The problem is the search specialist has great data to tell you why search is working and why you should spend more. But so does the programmatic team and the social team and so on. How do you know who’s right and where your dollars are best spent?
This is a huge and difficult data problem, it’s not easily solved and it’s exactly the sort of challenge that’s perfect for Lucy.
What does the future of segmentation technologies look like beyond 2020?
Over the past 20 years, there has been a continuous evolution of the tools and technology to drive deeper and deeper levels of understanding of audiences for marketers. With greater understanding comes the ability to deliver greater levels of personalization, audience relevancy and engagement.
Up to this point, most of this personalization was based on transactional data – knowing where an audience lives, what they bought, membership type, page history, what they clicked on to come to the site, etc.
For us, the next frontier is to add the layer of personality insights. Through personality insights, we can understand an audience at an emotional level as well.
Now one challenge that marketers will face is that as we create a greater 1:1 understanding of an audience, do we have the right content to meet the needs of that audience? The demands on content generation will be magnified with higher levels of personalization.
Tell us about your AI research programs at Equals3 and the most outstanding digital campaign at Equals3 or elsewhere?
Over the past three years, we have invested over 40,000 people hours into the development of Lucy and we have six patents pending. Our team continues to be heads down on product development and evolving Lucy – both through the development of new features and the enhancement of existing ones. We have a roadmap that spans the next two years for how we will continue to evolve our technology.
What are the major challenges for AI technology companies in making it more accessible to local communities? How do you overcome these challenges?
We are selling nationally, so this isn’t a challenge we are focused on.
What AI start-ups and labs are you keenly following?
What technologies within AI and computing are you interested in?
Deep learning, Unsupervised learning for ontologies, video recognition AI, object localization and natural language generation.
As an AI leader, what industries you think would be fastest to adopt AI/ML? What are the new emerging markets for AI technology?
From our standpoint, our focus has been on marketing as we see this as an early adopting industry.
At some level, almost all industries are already being affected by AI and the benefits are going to come through automation. Can a business manage larger sets of data efficiently, can they make smarter / better decisions through the use of data, can they automate task that previously were labor intensive?
What’s your smartest work related shortcut or productivity hack?
We run our business using EOS, the Entrepreneurial Operating System. It’s an agile framework for running a company and one of its greatest benefits is that it makes meetings dramatically more productive, in particular it provides a format so that problems are addressed, resolutions are tracked as to do’s and those responsible for to do’s are held accountable for getting it done. It makes meetings useful and avoids the syndrome of people meeting about things and never getting things done.
Tag the one person in the industry whose answers to these questions you would love to read.
Mitch Coopet; Mitch is the founder of Aftercode, an AI startup and previously founded Code 42, the maker of Crashplan Pro.
Thank you Scott! That was fun and hope to see you back on AIThority soon.