Agero's Digital Transformation Strategy Validated by Digital Edge 50 Award

 

Innovation is a buzzword that’s tossed around a lot these days, and as with most buzzwords, it’s been drained of meaning. At Agero we believe true innovation— that is, innovation that has value and isn’t just an empty word—is change for the sake of the customer. This customer-centric focus means that, for established industry leaders like Agero, innovation can’t come at the head of rapid and reckless change. It has to be carefully planned out and unveiled in a way that delivers exceptional experiences for current customers, while moving the industry as a whole forward.

That is why Agero’s path to digital transformation was a bit different. It’s also why it’s been so successful. And the industry is noticing! Agero was recently awarded the Digital Edge 50 Award for our Proactive ETA (estimated time of arrival) Risk model, which leverages machine learning to monitor roadside services in real-time to predict when service providers will be late, and allows for proactive engagement to address issues and improve customer experience. This award, presented by the AGENDA18 conference and produced by IDG Enterprise, validates Agero’s strategic approach to digital transformation, and also demonstrates the critical value of customer-centric innovation.

Agero has been in the roadside assistance business for over 45 years, and over that time we’ve seen customer needs and expectations change. Though the need for the core services often remains constant, how consumers want that service delivered can vary wildly from customer to customer. Taking this into account, we realized that the most effective way to take our organization into the digital age without alienating our clients’ customers is by leveraging digital tools to make the overall roadside experience as seamless as possible. This is the motivation behind our entire digital transformation effort, and it’s why we developed our own proprietary machine learning technology for our Proactive ETA Risk model.

We knew that one of the biggest pain points for customers isn’t the roadside assistance itself, but the struggle of not knowing how long you were going to be stuck on the side of the road. Failing to meet expectations, and in this case missing an ETA, is one of the most critical factors leading to a negative customer experience. With customer satisfaction and driver safety in mind, we built an automated model that uses both historical and real-time data to continuously evaluate service risk factors and permit Agero’s triage agents to proactively intervene for a seamless service experience. On average, the model can predict an event requiring intervention with greater than 90 percent accuracy. By taking early action and leveraging real-time data to monitor progress, Agero can proactively communicate with drivers, which is a major source of relief for customers who often are experiencing a high level of stress. We can see the impact of our efforts in the data. For example, we see a 30% reduction in overall complaints when our model is used.   

Through the receipt of the Digital Edge 50 Award, our strategy of making our customers our motivation for digital transformation has been validated and broadcast to the larger industry.

Award-3

It was a privilege to receive the award on behalf of our data science, engineering, product, and operations teams that worked on the Proactive ETA Risk model and related process enhancements. To be recognized as a technology and innovation leader not just in our industry, but across industries was an amazing honor. I am particularly proud of the fact that our advanced data analysis methods and machine learning algorithms are making a positive impact for drivers when they’re most in need of help.

 

 
 

Meet the Author: Michael Bell - Senior Director of Data Science and Analytics

Dr. Michael Bell is the Director of Data Science & Analytics at Agero. He and his team use data, advanced analytics and machine learning to help drivers in need - everything from detecting a car crash using a smart phone, to predicting breakdowns in a city during a severe weather event to improve service. Before joining Agero, Michael was an astrophysicist at the Max Planck Institute for Astrophysics in Munich, studying cosmic magnetism and developing new algorithms to apply to data from radio telescopes. He obtained his PhD in Physics from Brandeis University.
 
 

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