Lead Scoring Attributes: Hidden Information That May Not be Included
When you use a lead ranking system like the one in our Lead Management Automation™ platform, you’ll find that leads are prioritized according to fit and behavior. Lead scoring combines a grade for explicit attributes, which indicates fit, with a score for implicit attributes, which indicates an interest level. While implicit attributes measure digital body language, such as website visits or email click-throughs, explicit attributes rank how well a prospect meets an optimal lead profile.
Grading leads according to fit seems straightforward; each grading category will include easily definable attributes which help determine a good or poor fit. Scoring leads according to interest may also seem simple enough; online body language can be easily captured to show whether there is enough interest to justify pursuit. However, there are usually non-apparent factors which may not show up in a “standard” lead scoring matrix. Here are a few examples of critical information that may not be reflected in a standardized lead scoring matrix, these lead scoring attributes should be included.
Annual revenue figures can be easily defined and included in a lead form, but the figures may be misleading. A company representative may either not have that information or be reluctant to select a revenue amount when filling out a form. Usually providing a set of amount ranges to choose from may be effective. For example, $0 to $500K, $500K to $1MM, etc. may be appropriate.
Also, current revenue figures don’t reflect future earnings. A lead that earned $750K last year may not rank highly in your matrix, but if revenues rise to $1MM, its rank may rise accordingly. In this case, it’s important to avoid discarding a lead because of its low current revenues grade. (It may be effective to include a revenue projection category in your lead form.)
Number of employees
Company size is an important determinant to a lead’s fit. But employee numbers only tell a part of the story. The number of employees, like revenue figures, is a dynamic characteristic. For instance, the company may have just completed a downsizing or may have merged with another company. These actions won’t be easily captured in a lead form.
Another factor that isn’t usually reflected in a lead scoring matrix is: what are the possibilities for growth for a lead? Certainly, if a lead employs 500 workers then it may qualify for a high score in your matrix, but where will that lead be in a year or two? Is the industry growing? Are there more competitors entering the space? While it should be easy to collect and score the current company size, potential growth may be a more subjective score to determine.
Website product pages visited
Many lead scoring matrices include negative scores which decrements a lead’s overall rank. One scoring example would be a lack of page views about products. It may be difficult to capture through a standard lead form why a prospect visited your site but viewed no product pages. The reason could be due to a lack of need or incorrect timing. If a contact has only visited certain pages, such as investor relations, careers or about us, the reason for the site visit may not be a product purchase. Some visits to management pages may be part of a company review in anticipation of a purchase; however, visits to those pages should accompany product views if a lead is to be scored high.
For more thoughts on effective lead scoring, connect with our revenue generation blog regularly and learn how Lead Liaison can drive revenue through marketing automation.