In this episode, Ray discusses Demandbase Data Labs, which specializes in data sets, and how they have built data sets that inform users when a contract is up for renewal and how customers can sell into businesses that manage fleets of vehicles. Fleet insight is a data set that allows customers to identify the size of businesses with fleets, the function of fleets within those businesses, and what technologies are being deployed. By understanding these details, customers can target potential business prospects or customers.
Ray Renteria is a veteran of the data industry born of the Austin startup scene. In the last 25 years, Ray has crafted data solutions for companies ranging from small businesses to Fortune 500 behemoths using a wide variety of data sources and integrated them into the business data machinery used to support Sales, Marketing, and Strategic initiatives. Still a data entrepreneur, today he plays a leading role in the Demandbase Data Labs program that brings “surgically precise” targeting solutions to Demandbase’s customers.
“Obviously, we are in sales. The goal is to close business, but in order to build long-standing relationships that will grow and grow as time goes on, and as the economic downturn goes and turns back up, again, we’re planting those seeds with these customers and focusing on that value… That is why you should work with us, not simply because we have the lowest price or because we’re willing to get in there and negotiate.”
– Ray Renteria
The Demandbase Data Labs team is responsible for creating bespoke solutions for customers who need something beyond what Demandbase offers out of the box. These solutions are then standardized and promoted to products if multiple customers need them.
These include a dataset that tells users when a contract is up for renewal and a dataset that provides insights into fleets of vehicles – the types of fleets, how many of each are needed, etc. These datasets are designed to help customers target specific businesses more effectively.
Essentially, the customer could get information on any company with a fleet, including data on the size of the fleet, the technologies used, and the projects related to fleet management. This would allow the customer to more accurately target their marketing efforts and better understand the full scope of the market.
The use cases are broad, and some examples are fleet management, warehouse automation, vehicle maintenance, environmental services, and skills replacement.
The future for this kind of novel dataset is to provide more precision in targeting with other attributes about growth capabilities, hiring patterns, etc., of organizations.
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