Prospect 1 scores 10 out of 33 for size. 33 out of 33 for vertical. Because the manufacturing industry is this company’s main vertical target; and 20 out of 33 for director level person. is 63. Good but not great. Prospect 2 scores 33 out of 33 for size. 23 out of 33 for vertical and 33 out of 33 for position. Their total score is 89. An excellent result. This is a basic demographic model. But there are more complex ways of doing lead scoring. For example. You can award points to people bas on the time How the sales team they spend on the company’s website. The more pages they visit or the more times they return.
The more points they earn
Lead scoring even the choice to download content or subscribe to the newsletter for example could affect the score. Prospects who subscribe to the company Business Email List blog . Attend a webinar. Or download an e-book from the homepage may earn a higher score than those who don’t. The elements of a lead-scoring model are endless . The most important thing is to know which behaviors and which information typically lead prospects to transform into sales opportunities and therefore into new customers.
Once you discover these patterns
You can use this data to build your lead-scoring model. How the sales team should use lead scoring now that the scores have been establish. What should sales do with this Marketing List data? In the example above. The sales person managing both opportunities knows that prospect 2 should receive more attention. There may also be different types of content or special offers to apply to prospects who scor this high.
