Machine learning can transform how you understand and interact with your customers. Join our latest VB Live interactive event for a deep dive into how Farmers Insurance is implementing machine learning to super-power their customer service.

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Effortless customer engagement is top of mind for Quinn Banks, senior product marketing manager at Farmers Insurance — and he’s spearheading the implementation of machine learning to get the company there.

“We are working with machine learning to make our app more efficient when customers come in, or even to anticipate what a customer will need when they come into the application, based on their habits, their environmental changes, even social media changes,” Banks says. “The blue sky is to be able to have a model for all of our customers — essentially having an in-depth profile of our customers and even the employees. And being able to anticipate what they’ll need before they need it.”

Getting executive buy-in is at the top of his list, Banks says. And in most companies, it’s not often easy to get everyone on board the new technology train.

The essential part is pushing past the flashiness of the technology, the bells and whistles, and drilling down to exactly what machine learning can do — and how it can transform your customer-facing service.

“It’s getting execs to understand at the very beginning that we need to have it in place for us to understand our customers,” he explains. That means you have to find the core objective you want to accomplish with machine learning. Is it to assist the customer through a process? Assist an employee with a process? Is it to facilitate communication when somebody is calling in?

The second step is a deep dive into current technology, back end systems, analytics — any system capable of helping you deliver on that objective. Do you have to bring in a new set of servers? Are you collecting the right analytics — or do you need to find a way to bring in more data?

“Machine learning requires analytics,” Banks says. “You need to know how customers or how your employees are engaging with their activities, where the best points are, where the difficulties are.”

“So it’s lining up these pieces — it’s a painful deep dive, to see what you have — before you really go down the avenue of machine learning,” Banks says. “I’ve been spending a lot of time with my IT department going through various systems and identifying where we can have some short wins. What we have in place today, how can we tie those in together and start creating a roadmap or a platform to start building machine learning.”

But once you are starting to move past short wins and getting into the long-term strategy, it’s too easy to forget you need to have a system in place to continue to grow.

“A lot of times companies will get something in, they spend all the money and all the time, but they don’t plan or budget to maintain it and to keep it and to keep it growing,” Banks says. “It’s going to continue to grow, so you have to have a department that can grow with it, and have people who are savvy and understand it on multiple levels. Not just marketing, not just the IT level, you need people who eat, sleep, and drink it — that’s what we say on my mobile team.”

“And once that is done,” he adds, “you need a complete team to manage it. Because once you put that in place, and your customers are used to it, you can’t back off. You must keep moving forward.”

To learn more about how AI and machine learning can revolutionize the customer experience, how to implement the infrastructure, where social media data comes in, and more, don’t miss this VB Live event.

Don’t miss out!

Register here for free.

In this VB Live event, you’ll:

  • Learn how cognitive technologies scale across mobile devices (including cars)
  • Evaluate the value of a machine learning product to your organization
  • Tailor your data structure to optimize for future machine learning initiatives


  • Quinn Banks, Sr Product Marketing Manager, Farmers Insurance
  • Stewart Rogers, Director of Marketing Technology, VentureBeat


  • Wendy Schuchart, Analyst, VentureBeat