Managing Director & Senior Partner, Leader Deep Customer Engagement AI by BCG
Madrid
By Alfonso Abella, Ignacio Hafner, Basir Mustaghni, Lluch García, Johannes Goltsche, Patrick Müller, and Wolfgang Walther
This is not the time for B2B sales organizations to make unforced errors. But Boston Consulting Group finds that many businesses are underusing data and analytics in their sales functions––and missing out on as much as 5% to 10% net revenue uplift annually. The reason in most cases is based on false perceptions about the practical value of sales intelligence and a lack of awareness about what it takes to deploy data and analytics efficiently and at scale.
The good news is that these perceptions are reversible. Our project experience shows that B2B organizations that make data and analytics a bedrock of their sales motions reap massive benefits, generating significantly higher rates of revenue growth, improved productivity, and lower churn. This article walks through how other organizations can do the same.
Sellers in a leading logistics company thought they were doing everything right. Their senior account reps had cultivated deep relationships with key buyers, stepped up coaching to younger sellers, and begun crafting more customized offerings to clients. But sales growth was still well below their target. A closer look revealed that the issue had little to do with the caliber of sales talent. Compared with faster-growing B2B organizations, this company lagged in its use of data and analytics, and the lack of ready insights was forcing sellers to spend their time chasing down information and validating leads, creating inefficiency and missed opportunities.
This company is not unique. In our conversations and client work with sales teams across industries, we hear three common sentiments that help to explain the low levels of engagement.
While the attitudes we’ve just described remain pervasive, some sales organizations have moved beyond them—with notable results.
Our research shows that B2B companies that employ advanced analytics across the deal cycle enjoy the highest rates of revenue growth. They have better lead generation, lead nurturing, and prioritization, and more targeted engagement once a customer has onboarded. Those insights are contributing to significantly higher sales performance. (See Exhibit 1.)
One fast-growing B2B has integrated its CRM system into its discount matrix platform, which requires that sales reps enter information such as conversion probability and lead stage into the system before they can obtain pricing approval. The CRM integration creates a “push” and “pull” for sellers, mandating data inputs that help leaders minimize discounting disparities while providing sellers with the pricing insights they need to achieve their targets more easily.
Likewise, rather than assume that their data and analytics processes are beyond repair, some companies adopt the mindset of building what they need and refining as they go. For example, a midsize communications company wanted to create a dashboard that would allow sellers to see all their customer opportunities in one place along with a prioritized set of next-best actions, so they figured out what data was mission critical for that task and made acquiring and cleaning it a priority.
Having laid the foundations, top-performing companies can press ahead more easily and adopt newer, next-generation technologies—raising the competitive bar higher for other sales organizations. A large telecommunications company has begun using generative AI to help sellers complete proposals. The tool populates request-for-proposal (RFP) responses with needed information, tailors it to the client context, and does so within minutes. Sellers love the system, which has removed a major time constraint. And the quality of the proposal is also better because the GenAI system pulls from a continually updated source of best-in-class company information and ensures that all RFP requirements are met.
Other organizations can begin building similar capabilities.
With the right tools and practices, organizations we have worked with have overcome their data and analytics barriers to drive significantly greater revenues. We recommend four specific actions that companies can take. (See Exhibit 2.)
Effective use of data and analytics is becoming a key differentiator between the “good” and the “great” in sales. And the bar is only going to rise as today’s leaders become evermore proficient at creating, deploying, and integrating data-driven approaches across the buying journey. Companies that have been slow to embrace these developments can still catch up—and outpace their competitors. But now is the time to start. The approaches we cite here can make that catch-up process both manageable and attainable, transforming today’s laggards into tomorrow’s leaders.