Marketing automation helped marketers gain a deeper understanding of their target buyer and develop the right messaging, calls to actions and campaigns. But the real big win to come from marketing automation was supposed to be lead scoring.
Lead scoring promised an end to sales’ perennial complaint that marketing wastes their time with leads that weren’t ready to buy. Finally, there would be a system that measured what prospects did and determined when leads were ready for sales. Savvy marketers involved sales in defining how a lead was measured and when to pass it along. The promise was that only those leads that met a predefined threshold were passed on to sales. Eureka! Finally, a definitive way of measuring marketing’s impact on the pipeline.
Or so we thought.
Marketing automation has had a significant impact on marketing’s efficiency and productivity. But lead scoring has not delivered on its promise. Scoring leads is complicated, confusing and produces inconsistent results. In the quest for accuracy, scoring has evolved from arbitrarily assigning points to buyer activity to predictive lead scoring. Vendors like Salesfusion and Lattice Engines use algorithms to learn the attributes and patterns of leads that resulted in closed -- as well as lost -- sales opportunities.
It's the Journey That Counts
According to Christian Nahas, CEO of Salesfusion, “Our algorithm learns from every deal and identifies both the attributes as well as the path of won and lost leads.” Salesfusion enables marketers to predictably score leads, identify which ones should be nurtured and which ones to ignore completely and gives sales the ability to rank the leads they received. “Sales can be very specific in rating if the lead was right on, off or needed more nurturing,” says Nahas.
By combining internal prospect, customer, lead and sales information with external information on target accounts, predictive lead scoring vendors believe they can identify the attributes of good leads as well as model the path these leads take in the purchase journey. Armed with this knowledge, marketers can optimize segmentation and behavior based nurturing and invest in programs that trigger the right emotional responses at key moments for the right buyer.
Salesfusion’s vision is to not score leads based on their behaviors, but to score target accounts based on the paths they take. “For every account, their touch points determine if their path matches a won or lost lead and the strength of that match. Once the path is identified, prescriptive lead scoring can then prescribe how to best personalize campaigns, assets, content and calls-to-action to pull the target account along their own journey,” Nahas said. “People are hungry for easy to digest, humanized content and clear, actionable advice on how to design and nurture campaigns that work for each micro segment.”
Working With a Complete Picture
The prescriptive lead scoring vision is compelling, but the industry’s approach to understanding the journey is flawed.
Too much effort is being spent on trying to decipher what the customers’ journey is by analyzing incomplete data. All this "inside out" analysis is not only faulty but requires a lot of time. The results still require cycles of trial-and-error and fine tuning. By the time the user has figured out buyer patterns and attributes, customers have changed their behaviors.
Lead scoring must be based on a complete understanding of the buyers’ journey. It’s not enough to know what the buyer does at certain points in the journey. The total picture is needed. Why? Because without it vendors cannot accurately determine a potential client's intentions, emotions (yes, even B2B buyers have these) or how their physical actions relate to their digital actions (because nothing is 100 percent digital).
The Customer Knows Best
The best, and quickest, way to get a detailed, holistic understanding is by asking the buyer. That’s right -- it requires a face to face conversation.