At the annual kick-off event, Brad Myers, Chief Revenue Officer at a growth oriented SaaS company, rolled out ambitious new sales goals. His team's reaction was swift, predictable, and unfortunately far too common.
Sales vehemently protested. To hit these goals, they declared, Sales needed more quality leads from Marketing.
Marketing’s response was equally pointed. Sales was not following up on the Marketing Qualified Leads (MQLs) they already provided.
Brad managed both teams, so there was no one to point a finger at but himself. He needed to find a way to drive more revenue from existing team resources and budget.
NECESSITY IS THE MOTHER OF INVENTION
Brad observed that Sales needed no invitation to follow up with prospects who submitted demo request forms. These ”Hot” leads, however, accounted for just 10% of all the digital signals Marketing generated.
Over 90% of the digital signals that Marketing generated were ”Activity-based” leads such as content downloads, registrations, and site visits. A lead score assigned values to these intent signals. When a prospect accumulated a sufficient score, Marketing designated it a Marketing Qualified Lead (MQL).
Unfortunately, Sales had very little visibility into these digital signals. Worse, Sales didn’t believe these leads were “qualified” despite Marketing’s well-intentioned efforts to get Sales to subscribe to the lead scoring logic.
The week after introducing the new sales goals, Brad studied the digital signal data that Marketing captured in their marketing automation platform.
One name caught his eye. A former prospect had just visited the pricing page. Three years earlier, Sales had quoted this prospect $50,000 but lost the deal. According to the CRM, Sales hadn’t spoken to this prospect since.
The lead score was incapable of surfacing this valuable context. Sales had absolutely no idea this prospect had just visited the pricing page.
So Brad Slacked his sales rep a message:
Two days later, his sales rep closed the deal for $35,000.
Encouraged by this anecdotal success, Brad continued to monitor the digital signals Marketing generated and connect the dots for Sales.
Digital signals that his team assumed were ”low intent” suddenly looked promising. Previously overlooked opportunities came to light. The pipeline grew. The sales team began closing more deals more quickly.
Several months after the first Slack message, Brad had an epiphany. If he could write an algorithm to replicate his manual effort, he could spoon-feed Sales with context and insights in a more automated and consistent manner.
Brad reverse engineered his messages and built an MVP. In the days following its release, ”Brad-in-a-Box” began delivering valuable, actionable insights at scale. Within months these stories led to double digit growth in pipeline and new revenue, all from signals Sales previously dismissed.
MORE THAN A SCORE. TRANSFORMING DATA INTO STORIES.
A discussion with his friend and SaaS technology leader, Ben Wolf, led to new ideas that marry Brad’s algorithms with advanced machine learning technologies on a highly scalable serverless platform. The two decided to found RevMethods with the singular vision of helping growth-oriented companies derive powerful insights from their earned data and create more value for their prospects, their clients, and their organizations.
RevMethods believes that a fundamental problem with today's dominant B2B revenue platforms is that they reduce people to impersonal objects. We rate, weigh, and score various attributes and behaviors to substitute for understanding all sorts of things: e.g., lead scores, health scores, customer satisfaction.
The problem is not necessarily the numbers themselves. It’s how people use them. The scores start out as a tool for thinking; they end up replacing thought. And they inspire no one.
RevMethods’ ambition is to rethink the modern revenue tech stack. To build an AI-enabled, integrated platform that recognizes the humanity underpinning business relationships and facilitates more meaningful interactions to all parties. To utilize technology to tell stories that bring people closer together.
Storytelling is, after all, a fundamental part of what makes us human. Stories allow us to share information and establish emotional connections. In a commercial context, stories can give energy, encourage thought, and inspire action.