Four Steps to Successful Lead Scoring
How do you know which lead is qualified? First, you have to make sure the leads fit your profile and second, they should have a high propensity to buy. The following is a step by step approach to lead scoring.
Step 1: Get Sales Insight on Scoring Criteria
The interactions the sales force has with your customers will enable key insight into identifying information and behavior to indicate sales-readiness. Integrating the feedback loop to the scoring model can also build support for the results and drive in-process refinement.
Step 2: Develop the Models and Calculate the Lead Scores
Lead scoring is based on a systematic process of assigning each lead a probability and a weight on specific criteria and behavior. This model should comprise both explicit and implicit information. Explicit data is static such as company size, industry segment, job title or geographic location, while implicit metrics are derived from monitoring interactions with your web properties, inside sales force or direct sales force.
To get the bigger picture, couple your fit model with a propensity to buy. Propensity modeling is a powerful modeling and targeting technique which has the ability to identify valuable leads and facilitate their acquisition at a maximum return. By using this type of model, you will be able to better understand your current customers and thus, better target new leads. Start by looking at your existing customer base. Analyze their behavior compared to a universe of recently acquired leads, using historical data to identify predictors of buying behavior. Your conversion funnel provides insight into both lead leak or conversion drivers. Using logistic regression models, categorize your leads according to the propensity to buy and target them more effectively.
Step 3: Develop an Action Plan
Once you have categorized the leads according to their fit and propensity to buy, develop an action plan for each lead quadrant based upon the propensity to buy and the fit with your existing customer base.
- Route qualified leads that represent a good fit and present immediate sales opportunities to sales.
- Plan customized nurturing efforts for warm leads that are not yet ready to buy, but fit your customer profile.
- Abandon the leads that are neither a good fit nor probable to buy.
Step 4: Measure Performance
Lifts and Gains are two indicators you can use to measure the model performances.
Lifts: This indicates the relative measure of the effectiveness of a predictive model or how much better a model performs against a control group. It reveals how much more likely you are to convert leads to sales if we use the model than if we contact a random sample. You can compute it as the ratio between the results obtained with the model to the results with no model.
Gains: This measure shows the percent of total possible leads converted by targeting specific percent of the customers. You can draw cumulative gains and charts to better visualize and compare the model's performance.
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Great article.
Very good article. Useful information. Thanks
Nice article. Really interesting information outlined in the four steps.
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