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Why Data is the Key to Navigating the SiriusDecisions Demand Waterfall

Who would have guessed that frameworks, funnels, and the notion of buying groups could cause an entire industry to lose its collective mind? Well, that’s exactly what has been happening since SiriusDecisions unveiled its new Demand Waterfall last month in Las Vegas.

Long considered the bible for mapping the B2B buyer’s journey, the SiriusDecisions Demand Waterfall has been used by countless organizations to influence how they’ve approached, managed and tracked lead management. Yet over the past few years, as the sales and marketing space has grown increasingly more complex, the traditional demand waterfall that focused on nurturing a single lead through the funnel has become a bit outdated. Understanding that a B2B marketer’s ideal customer is no longer a single individual, but rather a group of buyers, SiriusDecisions modernized the Demand Waterfall to focus on identifying and targeting buyers aligned to specific buying groups that have demand for your product or service. They call this a demand unit, and it’s been driving some of the recent hysteria we’re seeing among journalists, analysts, and thought leaders – and for good reason.

The New B2B Demand Waterfall

The latest incarnation of the Demand Waterfall finally reflects the reality of how B2B demand generation actually works. Today’s B2B buying decisions are not being made by a single person, they involve multiple individuals from different departments with different responsibilities; it’s essentially a buying committee, and you must engage and convince each of the buyers why they should work with you throughout every stage of the sales funnel.  What’s more, there may be multiple demand units in the same enterprise, all with different needs and at different phases in the planning process. So, while there’s certainly a lot more to think about, the new SiriusDecisions Demand Waterfall is helping marketers move beyond a single, lead-focused approach toward a broader, account-based strategy.

Leverage your data and analytics to determine which enterprises are best suited for your solutions.
 

For many of us, this is nothing new. Account-based marketing (ABM) and the group buying approach has been widely adopted by many B2B organizations, yet it’s still reassuring that SiriusDecisions is validating the approach. Even so, we are left with questions on how to operationalize the waterfall without drowning. Obviously, the answer is going to be data. But knowing what data to use will be vital to staying afloat. You’re going to need to understand multiple levels of information to be successful.

 

How to Not Drown in the Waterfall

First, you’re going to need to identify the right enterprises to prioritize before they engage with you. Leverage your data and analytics to determine which enterprises are best suited for your solutions.

Second, you’ll need to find the right buying groups within each organization to accelerate sales conversations. This involves not only understanding key people in a prioritized target company, but also understanding how they relate to each other. The combination of data and analytics should inform your strategy and help you produce better content, drive quality and measurable conversions, and make the sales process much more efficient. The biggest implication is that by leveraging the right mix of data and analytics, marketers will be even bigger drivers of their company’s strategy.

new sirius demand waterfall

We Are Doing This at Dun & Bradstreet

Our customer analytics team really led the charge – combining art and science to establish a data-driven, analytic approach that was optimized with sales intelligence and then put into practice through a partnership with sales operations. We wanted to recommend relevant, high-value customer groups (demand units) based on real-time insights for our sales team to call on, and move away from subjective categories - like spend - as the primary segmentation attribute.

Our targeting and segmentation strategy started with leveraging clean, integrated, and organized data and firmographics to ensure we were engaging the right contacts. We accomplished this through a master data strategy that combined our first and third-party data and then linked the data to key identifiers like IP addresses, mobile IDs, and data in our CRM systems to target the right activities by demand unit. This is all done through our patented Dun & Bradstreet D-U-N-S® Number, which is the foundation for ensuring we’re always reaching the right contacts.

Next, we continued to leverage our first and third-party data and analytics to determine our buying groups before ever talking to prospects, which was really the lynchpin to creating successful outcomes. Our advanced analytic techniques helped us identify the right set of criteria for each buying group, leveraging:

  • Customer-centric data in the context of the business we were targeting, company size, and industry metrics (e.g.  growth/decline)
  • Existing first-party data, including offline data in our CRM and other systems
  • Propensity models, which predict the likelihood of a customer or prospect to purchase Dun & Bradstreet products and services. These use firmographics, purchasing behavior and other predictive variables and are tailored for Dun & Bradstreet’s line of products
  • Attrition risk models, developed by Dun & Bradstreet for its customers and solutions, which predict the likelihood of a customer to attrite from a product (these use some of the same indicators that are used in propensity models)
  • Historical factors such as renewals, payment history, and complexity of purchase

This new approach would re-segment accounts within the three existing sales channels (Strategic Vertical Accounts, National Accounts, and Inside Sales) to map our “best” customers/prospects with our “best” sales executives and to take advantage of team-based selling and buying. This meant rebalancing portfolios and reprioritizing accounts.

Strong analytics facilitate the grouping of customers with similar needs into sales and service models that best serve their needs and identifying what Sirius calls “demand units.” This grouping leads to increased opportunities for cross-sell and upsell, superior retention, and increased customer satisfaction.

Employing these strategies has significantly helped us increase our pipeline, grow existing accounts, and drive new demand. All of which is what the new SiriusDecisions Demand Waterfall is expected to help B2B marketers focus on.

 

 

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