The evolution of Lucy: Equals 3’s AI-powered assistant gets even smarter

The intelligent assistant gets predictive modeling, automated workflows and more added to its expanding skill set.

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In 2016, we told you about Lucy, an artificial intelligence (AI) platform that answered marketers’ questions via menus or conversational English queries, using data from multiple platforms.

Two years have passed since its debut, so we checked in on Lucy’s creator, Equals 3, to see if the AI-powered assistant had changed.

We discovered that there’s a new Lucy in town: Lucy 2.0 is an evolution of its earlier iteration with an expanded skill set. Or is it toolkit?

Lucy 2.0 has been in beta since January with new capabilities, including the ability to create automated workflows and use predictive modeling.

Getting smarter all the time

Like any good AI, Lucy 2.0 has been learning and is getting smarter. She now has a Snapshots feature through which users can automate workflows. She can work with increasingly complicated data sets and predict how specific marketing messages will perform against certain personas.

And yes, she can also offer suggestions for improvement.

“Lucy 2.0 marks a vital milestone in Lucy’s evolution, where marketers can leverage more data and tools to inform their decision-making,” Scott Litman, co-founder of Equals 3, said.

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Lucy’s home screen

The original role for Lucy was to help enterprise-level marketers, and advertising and media agencies, manage and analyze structured and unstructured marketing data across channels.

“This is the core problem we’ve been addressing — the explosion of data,” Litman told me. “And if you think about it, if I’m a marketer — whether it’s today or 10 years ago — I have a core responsibility: drive engagement of audiences and [drive] actions. How do I help my customers acquire? How can I help them retain? That’s the job of marketing. And in those 10 years, the universe of data has exploded. It’s more data than any one marketer could deal with.”

Lucy is trained in natural language processing and understands grammar and context. She’s been studying intentions — learning more than 5,000 in a span of six months — so she can better understand the intention behind the questions she’s asked.

Litman told me that Lucy’s evolution followed the needs of marketers dealing with such extensive stores of data.

“We’re really doing a lot of enterprise knowledge management. We’re doing predictive modeling and forecasting for media that didn’t exist before, and we’re running personality insights to provide a level of understanding into an audience that is not easily available in audience tools today,” Litman explained.


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About the author

Robin Kurzer
Contributor
Robin Kurzer started her career as a daily newspaper reporter in Milford, Connecticut. She then made her mark on the advertising and marketing world in Chicago at agencies such as Tribal DDB and Razorfish, creating award-winning work for many major brands. For the past seven years, she’s worked as a freelance writer and communications professional across a variety of business sectors.

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