Scoring Leads and Identifying Value

Again, all leads are not created equal, but all leads have value. A product trial request from a large multi-national company is clearly more valuable than a feature inquiry from an individual or small company. Leads have a number of attributes, some of which are known at the time of inquiry and some are not. If these attributes are made more visible with the supplementation of information (from step 3 in the previous article in this sequence) and driven through an analytical scoring process, the organization can intelligently drive more value-added action on each lead.

Scoring a lead requires a methodology that assigns values to each lead based upon a set of weighted criteria. At a minimum, leads should be scored for urgency (how soon) and for potential (a measure of value). Clearly a customer from a large multi-national corporation with an immediate need would most merit an immediate phone call from Sales, while a web inquiry from an individual with a longer timeframe would elicit a more measured response. By thoughtfully calculating numerical values for each lead, an automated system can determine the right channel for follow-up based on these scores, and the organization as a whole can better prioritize their lead lists and focus on those opportunities with the greatest potential value.

Though each company may collect different information to score leads, some basic criteria to include are:

• Interest (an identified need for the product/service)
• Size (how large is the opportunity)
• Timing (what is the timeframe for purchase)
• Influence (who is the decision-maker)
• Intent (how likely is the sale)
• Competition (how many competitors are in play)
• Fit (does the lead suit their product strengths)
• Urgency (how large is the pain)

Many companies don’t have an identified scoring system and simply prioritize leads subjectively, then employ some heuristic methodology to assess quality (e.g., that’s a big company, or that town is wealthy) and ignore the rest of the leads. A more evolved model takes the attributes of each lead and identifies a score or scores, or a measure of quality and a measure for urgency, for that lead that determines which channel should follow up on that lead.

In addition to establishing a scoring model, care should be taken to ensure that the scoring model evolves over time as new information is added or new analytical insights are gleaned from the recent history. The best methodologies look at sales results and work backward to determine which attributes are most predictive of sales success. A periodic review of the scoring model will highlight which attributes are the best indicators of success and enable a fast response to any shifts in the market.

An important note to this step is that individual lead scores can change over time. Just because a lead has a low score at one point in time, does not necessarily mean the lead will always be of low value. As Exhibit 1 demonstrates, additional information (through supplemented data or interactions) can sometimes indicate that a lead should be re-scored. Also, scores can change over time because the prospect’s interest level and purchase timing can change.

Author

David Bartenwerfer is the founder and principal of Quantum Consulting and Technology. QuantumCT helps product and marketing organizations get smarter and prove, predict and optimize impact and ROI with economic and financial modeling that employs customizable algorithms and technology leading to fast and lasting insight and action. Mr. Bartenwerfer has over twenty years’ experience in the High Tech, Internet, Telecom, Media, Financial Services and Retail industries and holds a B.S. in Systems Engineering with minors in applied mathematics and economics from the University of Virginia and an M.B.A. from the Stanford Graduate School of Business. For further information, contact the author at davidbartenwerfer@quantumct.com.