Lead scoring is among the top three strengths of B2B lead management/marketing automation platforms. Yet early adopters of marketing automation are still struggling with the nuances and changing buying habits of the digital buyer. Predefined lead scoring models make marketing automation setup easier and provide an architecture for ranking and prioritizing leads. However, we recommend establishing a unique scoring model (based upon a customer persona) that more accurately defines the quality of your leads.
It’s important to recognize that lead conversion, and ultimately close rates, are by their very nature challenging to forecast. Even within a lead management/marketing automation platform, the lead scoring functionality is only as effective as the model that has been built. Lead scoring defines the quality of a lead by its attributes and digital footprints. But even the most finely honed scoring models can leak unprepared and/or unqualified leads into your CRM.
That’s because using the total score (which is typically used to determine lead migration to a CRM) doesn’t tell the whole story. Hidden challenges can be hiding behind any automatically nurtured lead score.
Even a lead that is migrated to a CRM with a score of 100 may not be fully sales-qualified. Look at this example:
A lead enters your CRM with a overall score of 95 (out of a maximum 100). The lead achieved a A grade for intrinsic qualities like company size, revenues, and # of employees. For the behavioral scoring, the lead achieved a 98 score. This lead looks like a sure conversion based upon its overall score. But missing in that terrific score is a factor that wasn’t scored: the contact is finishing a month-long resignation and the purchasing decisions will be transferred to another position. The lead owner does not recognize this transition until first touch after migrating to the CRM.
How did the lead achieve that score? Was it primarily due to lead attributes (industry, contact title, etc.) or due to online behavior? Sales agents using integrated marketing automation platforms now have the capability to review leads as they move through the marketing funnel. Your sales reps should be advised to review the details of the lead’s score early in the engagement process. This will allow them to understand clearly how the lead got to their prospect pools, discover selling opportunities, and uncover deficiencies that may need to be overcome to convert that lead.
One tactic that helps to sharpen your scoring model is to mix in minor sales engagements along the nurturing path. Information gathered through preliminary qualification calls can provide guidance when it comes to adjusting weights or adding variables to your lead scoring model.
Sure, you can’t account for every circumstance and situation but developing an accurate, rigid yet adaptable scoring model – with as many parameters included as possible and appropriate weighting of each parameter – will help prevent ineffective measurement of the quality and interest of your B2B leads.