Volta Charging operates the largest free electric car-charging network in the United States. Its expanding regional networks of charging stations, strategically located at high-traffic retail centers across the country, help promote electric car usage and encourage environmentally sustainable practices—while also providing brands with a powerful media platform to deliver their messages directly to consumers.
Volta Charging offers a potent combination of benefits to owners of electric vehicles and to retail brands interested in attracting customers while associating themselves with increased sustainability. Driving these benefits is data: about the usage and performance of Volta charging stations, about the habits of the people charging their electric cars, and about the companies sponsoring charging networks and running ads on the stations’ digital screens.
In fact, Volta Charging is awash in data. The challenge, according to Mia Yamauchi, the company’s Marketing Manager, was probing all the various data warehouses to gain insights from that data without knowing beforehand exactly what she was looking for.
“I knew we had a data gold mine, but there was no practical way to take all the material in the mine and sift, sort, categorize, visualize, and explore what was there,” she says. “Besides gold, was there also platinum or silver? There was no way to tell.”
While not a coder, Yamauchi is a self-described ’big data nerd’. “I get excited about figuring things out on my own,” she says. And yet, facing large volumes of data living in separate cloud data warehouses, she was at the mercy of Volta’s data engineers and their SQL skills to analyze it all and report back to her, or to provide SQL queries she could attempt to edit for her needs.
And Yamauchi isn’t the only Volta business user with data analytics challenges. She recalls one frustrated person in the company’s finance department—who was preparing a big report for a board meeting that sliced and diced SalesForce, physical charging network, and other data—saying: “I know all my data’s in there. I wish I could just pick up my computer and shake it and have it all fall out.”
Volta Charging turned to Sigma to close the gap between Volta’s data experts - responsible for the architecture, governance, and performance - and their business experts - responsible for understanding and driving strategy and operations.
“With Sigma, it’s like I can now have a conversation with my data,” says Yamauchi. “I can muse, for instance, about whether charging usage per hour is different for stations near a grocery store or a gym. Or if the content of ads on the digital boards translates into higher foot traffic for the sponsoring retailers. I can get answers to my questions right away without having to break my conversational ‘tone’ to dive into SQL coding.”
She can find out if data supports hypotheses, such as whether electric vehicle drivers are more likely to patronize shops near a charging station. Volta can also use its data to help persuade retailers of the advantages of installing an electric vehicle charging station at their site.
“Some retailers worry that the free charging stations will be monopolized by parked cars instead of active shoppers, but now we can quickly pull together and present data in multiple ways to demonstrate that, in fact, the people using the charging stations are also shopping,” says Yamauchi. “As an example, we can show that dwell time at the stations correlates with increased retail foot traffic, or how many people with electric vehicles are choosing to stop at a grocery store with a Volta charging station rather than any other grocery store along their commute.”
Yamauchi can also explore data she never thought to look at before. “In the past, taking time to answer questions might have meant creating nested joins for a bunch of tables—worth the time only if I knew what I was looking for,” she says. “Now with Sigma, I can just dive right in and start exploring our data. I know I’ll end up with something interesting and useful, even if it wasn’t what I was originally expecting.”
The insights are helping improve Volta’s operations and bottom line. By knowing more about the behavior of electric vehicle drivers, the company can more quickly identify promising retail locations for new charging networks. And the sales team is able to close deals with sponsor brands more quickly by showing retailers hard data about how usage of Volta charging stations aligns with their customers’ shopping habits.
“Sigma makes my data-driven decisions more accurate and timely,” says Yamauchi. “And at a personal level, being able to converse with my data makes my job more fun.”
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