Amanda Koprowski,
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Jeff Bell, the vice president of Sales Operations at Key Equipment Finance for the last eight years, has spent much of his career in sales, working directly with clients. But despite such a people-friendly focus, it’s where his interest in data analytics began.

“I’ve been in sales, I’ve been in customer facing positions, and I’ve done a lot of work in Six Sigma in project management,” he says. “I find sales operations interesting because it pulls all of that together. The big picture — and especially the data and analytics aspect — is what really interested me in joining Key.”

Bell primarily views himself as a problem solver, using the tools at his disposal to define a client’s needs and figuring out the best way to meet them. The use of data analytics, a method of consolidating and modeling data to assist in decision-making, has become one of his and Key’s go-to ways for arriving at solutions, incorporating it into sales models early on, which helped them stand out in the more traditional equipment finance industry.

“The way data is used in our industry is primarily from a credit perspective. The industry does that quite well and has been doing it for a while,” he says. “Bringing that use of data to a sales role or a sales team may not be as unique today as it was eight years ago, but back then, it was difficult to get a sales organization to really think hard about using data to become more successful.”

The incorporation of data analytics can pay dividends for a company; not only can a business assist its existing clients, it can also figure out which direction to go in next by analyzing current trends and determining which products to concentrate on and which to leave behind.

Bell breaks down his process into a few easy steps. “First, I have to find and retrieve the data, then I have to deliver it to the right people in a usable format that’s easily accessible, and finally, determine what the data is telling us. This includes analyzing whether the data gave our team the results we needed, and if not, thinking about what we have to do differently to make it more impactful.”

The Two Types of Data

Bell and his team pull information from, broadly, two different sources: internal data and external data. Internal data can be found via customer relationship management (CRM) tools and measures areas such as performance, effectiveness and conversion on the sales side and financial or loan history on the client side. The information can be used to examine the entire sales process from start to finish and then reviewed to create more effective sales in the future.

When viewing all of this data, Bell asks, “What activities are working and what activities aren’t giving us the results we wanted? We can use this data to help our sales reps be more successful in closing deals.”

If internal data is best used for improving on metrics or client relationships already present within the team, external data can be used to scout out new prospective clients. It can, however, be a little harder to come by as external data, as the name implies, is generated from external sources. That doesn’t mean it’s unavailable though; it simply requires a bit more time and research.

“External data could include UCC data or general business information, such as revenue size, industry, the type of products a company buys or sells, or if they spending money on capital expenditures,” Bell says. “It could be a variety of things.”

As this data is maintained by third-party sources, Bell recommends hunting around a little until you find the best fit for your organization. Not all of the information in any given database will be relevant for sales reps looking for new clients, so the analytics team needs to be sure to edit and narrow down the fields for relevant detail.

Data Integration

The next step after gathering external data is synthesizing and integrating it with the internal CRM systems.

Bell gives an example. “Let’s say I’m in sales, and I’m going to make a few prospect calls. I load up my CRM tool and I have a dashboard with 10 hot prospects, but I want to better understand what makes them hot. Now, we can drill down for more information. Maybe they just filed a UCC for a big piece of equipment, or there was news that they’re building a new plant down the road. This all helps inform how we interact with clients.”

By giving the sales team access to a complete data picture of both current and potential clients, Bell can ensure reps don’t waste time pursuing prospects that are unlikely to ever result in a sale. Alternatively, he can also help the sales team maintain the clients they already have.

“With the Internet of Things, every single asset is potentially connected to the internet,” Bell explains. “If we have a good partner and they share that information with us, we can better help them monitor when it’s time for a refresh, when actual usage isn’t in line with predicted usage, when we might have a financing offering that is a better fit for them, or other variables that might impact how they make equipment decisions.’”

Building a Better Partnership

One of the advantages to having access to so much data is the way it can build better relationships with both the data providers and with current and prospective clients. The third-party originators of external data may be looking for financial partners who can regularly use that data and provide feedback for better data quality. Clients may be directed toward more effective equipment based on their current use or get offered better financing based on past history. Even manufacturers can find an advantage in coordinating their information with the finance partner.

“This information allows the end user and a capital provider like Key Equipment Finance to make smarter decisions by sharing information about the life of the asset along the way,” Bell says. “This is just another way that all three parties — the user, the manufacturer and the finance company — can be better partners.”