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New types of data from a range of sources are transforming how marketing and sales teams reach customers, but they also present a distinct new challenge: information overload.
In the past few years, the business-to-business (B2B) world has evolved dramatically as account-based-marketing (ABM) teams adopted new digital tools to reach customers online. Yet, while the data has helped marketers contact the right buyers with the right message at the right time, the deluge of information can be overwhelming—leading to missed opportunities.
“Sellers want to be more data-driven, but they need a way to bring it all together to make sense,” says Jim Novak, Senior Director of Data Science and Customer Analytics at Dun & Bradstreet. “Otherwise it can lead to misinterpretation.”
Today, 68 percent of analytics teams feel that enterprise data goes unleveraged because of issues like poor cataloging, according to a recent industry report. In addition, online tools can be difficult to budget for, with 82 percent of data-management decision makers stating that usage-based pricing models lead to sudden cost variation, making it hard to control spending. “One of the biggest challenges decision-makers currently face is fully understanding the complexity of their organizations’ data estates,” says the report. “Many organizations are lost in the weeds. They need quick access with a low-code compass to find their way through.”
To help meet this challenge, marketing and sales teams increasingly rely on a fundamental resource: data-analytics departments. By sorting and cataloging first-party data and then comparing it with third-party information, analytics teams help marketers better understand who their buyers are and their needs, resulting in more effective omnichannel strategies.
“Marketing and sales teams need a way to make all their data play nice together,” Novak says. “We help them master that data to bring consistency, accuracy, and integrity to it across the business, so they can better understand their customers and have more meaningful conversations—and that adds real value.”
Organized Data Is the Foundation of ABM
For decades, data-analytics teams were separate from their companies’ marketing departments.
No longer.
In today’s B2B world, 33 percent of potential buyers prefer to do business seller-free, a number that’s expected to reach 80 percent by 2025. This shift is forcing ABM sales teams to rely on a data-driven omnichannel approach grounded in the most robust, up-to-date information. “Data and analytics have become foundational for sales and marketing,” says Steven Alexander, Vice President of Analytics and Insights at Dun & Bradstreet. “Our team now directly reports to our CMO.”
When buyers are deluged with digital pitches, it’s difficult for them to break through the noise. The key to standing out is having the right data that guides you to the correct person to reach with the most relevant message at the optimal time. That’s easier said than done.
“Getting ahold of a person is a lot more difficult than it was even four years ago,” Alexander says. “To connect, you need the right data and you need to be prepared with the right information. By gleaning insights from things like intent models and de-anonymized traffic reports, marketers can use that information to improve their speed to market.”
The most important first step in achieving an informed marketing approach? Organizing first-party data sets. With multiple tools at their disposal that often create data silos, analytics teams in B2B companies spend a lot of time sorting through fragmented data just to decipher how many accounts they have, hampering their ability to glean insights and create go-to-market strategies. By partnering with a company like Dun & Bradstreet, analytics teams can get help consolidating and cataloging their first-party data to gain a clear overview of internal information—and create an ideal customer profile (ICP) for potential buyers.
“We help fill in the gaps,” Alexander says. “By taking advantage of our data blocks from the Dun & Bradstreet Data Cloud, companies can get a more complete picture of their potential buyers and customers, too. With that they can profile and run programs that drive better insights for their sales and marketing teams.”
This step may sound simple, but it’s a difficult and time-consuming endeavor, making a turnkey solution a lifeline. “I read that 80 percent of a data scientist’s time is simply wrangling information and making sense of it,” Novak says. “This is before they can even do the data-science work, such as building models and making predictive insights. So the ability for companies to master their own data is huge.”
Gaining Insights for Data-Driven Action
With the right internal data in hand, the next step is to compare it with external information to create a tailored go-to-market strategy.
Data-analytics teams can use Dun & Bradstreet’s Rev.Up ABX, for instance, to match their company’s first-party data to Dun & Bradstreet’s proprietary D-U-N-S number for further offers insight into these accounts. “Our Rev.Up platform ties a data set to our own Data Cloud, pulling in key firmographic and technographic data,” says Alexander. “What are people looking at on your website? What keywords are ranking high? These are intent signals we can use.”
This added information helps illuminate the relationships companies have with their buyers, offering sales teams a clear vision of the solutions those buyers need and when.
“This is where data analytics can add value,” Novak says. “With this information, we can provide deeper insights such as corporate linkage. For instance, if one location is buying a product in California, there’s an opportunity to sell a different product to a subsidiary in New York. With a 360-degree view of a buyer, sales teams can have more meaningful conversations.”
At the core of Rev.Up ABX is a customer data platform (CDP), which provides a single system to collect, compare, and understand all of a company’s first- and third-party data—the central control point for all B2B marketing information. It includes customer data, management of the customer journey, engagement data, and more. All this is updated in near real time, too. “The CDP has a weekly cadence, and data refreshes every weekend,” Novak says. “New intent signals can come in one week, and all of a sudden a company can be in a new universe with a buyer. They can then use this almost real-time information to get to market quicker. It’s very dynamic.”
Using up-to-date data to act more quickly with more accurate information can be a game changer in today’s competitive environment. “We do data analytics to accelerate getting to market,” Novak says. “Strike while the iron’s hot and you have a better chance.”
Aligning Sales, Marketing, and Data Teams with a New Goal
While improving data quality is critical, equally important is getting buy-in from marketing and sales teams to launch a data-driven approach—and giving them clear views into the information so the right people can align to quickly make decisions.
For years, the various departments within a company acted independently. With a data-driven approach, information itself becomes a central source of truth—and analytics teams can use that to bring everyone together. “Aligning data, sales, and marketing teams with this new approach is a key step,” Alexander says. “Your product team is going to tell you something different than your sales team versus your marketing team. So we really do act as the internal consultants trying to bring all the groups together as best we can.”
In this new ABM paradigm, all decision-making starts with common, shared data. The key is to use the right data to create an omnichannel approach, one that gives each department the information they need to accomplish their goals. “Sales is a finite resource,” Novak says. “There are only so many sellers in your organization, and they can only reach out to so many buyers. You have to give them the information they need to be more tactical.”
For analytics teams, this integrated, data-aligned omnichannel approach is critical for success, and it’s only getting started. “Moving forward, we’re going to continue using machine learning and perhaps artificial intelligence to build new, different, better models,” Alexander says. “It’s all about speed. We’re getting the right insights to sellers quickly so they can have the most impactful conversations at the right time—and we’re going to continue improving and accelerating what we’re doing with an eye on the horizon for new capabilities.”
This story was produced by WIRED Brand Lab for Dun & Bradstreet.
