Lead scoring

Lead scoring is a methodology used to rank prospects against a scale that represents the perceived value each lead represents to the organization. The resulting score is used to determine which leads a receiving function (e.g. sales, partners, teleprospecting) will engage, in order of priority.

The most accurate lead scoring models include both explicit and implicit information. Explicit scores are based on information provided by or about the prospect, for example - company size, industry segment, job title or geographic location. Implicit scores are derived from monitoring prospect behavior; examples of these include Web-site visits, whitepaper downloads or e-mail opens and clicks.^[1] A new type of score is the Social Score - it predicts lead relevancy based on analyzing a person's presence and activities on social networks.

Lead Scoring allows a business to customize a prospect's experience based on his or her buying stage and interest level and greatly improves the quality and "readiness" of leads that are delivered to sales organizations for followup.

When a lead scoring model is effective, the key benefits are:

• Increased sales efficiency and effectiveness. Lead scoring focuses sales attention on leads that the organization deems most valuable, ensuring that leads that are unqualified or have low perceived value are not sent to sales for engagement.
• Increased marketing effectiveness. A lead scoring model quantifies for marketers what types of leads or lead characteristics matter most, which helps marketing more effectively target its inbound and outbound programs and deliver more high-quality leads to sales.
• Tighter marketing and sales alignment. Lead scoring helps strengthen the relationship between marketing and sales by establishing a common language with which marketing and sales leaders can discuss the quality and quantity of leads generated.
• Increase in Revenue

See also

• Business intelligence
• Balanced scorecard
• Customer Intelligence
• Customer service
• Database marketing
• Enterprise Feedback Management (EFM)
• Enterprise relationship management (ERM)
• Marketing automation
• Predictive analytics
• Sales force management system

References