Data Base Management for Lead Scoring

Data Base Management for Lead Scoring

lead scoring

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.

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