<s>I</s>mprove sales performance and increase prospect engagement.
Create a list of specific data points from your buyer persona that are important for your business when assessing lead quality.
The approach you take might be different depending on whether you are in the B2B or B2C space.
For example, in the case of B2B, you may want to qualify leads based on their annual revenue or number of employees, or years in business. If you’re in the B2C space, you might want to look at things like their income, age, or gender.
Include any specific data point you see in your customer data files that would merit assigning a prospect a higher rating.
For example, a data point could be Company and its description could be Fortune 500, Amazon, or Facebook.
Assign a positive or negative score for each data point in your table based on their value to your business when qualifying leads.
For example, assign a score of +10 if the lead’s Company is Amazon, or a score of -20 if their Average Income is less than $100,000.
This is partially a subjective measure, and therefore, you will need to use your best judgement and past data when assigning scores.
Use a tool like Salespanel to create scoring rules in your CRM for each data point.
Not all CRM tools have lead scoring built-in, sometimes you may have to link an app or a third party system to access this feature. Check your CRM documentation to find out how to assign scoring rules.
Add sample data like annual income, revenue, or any other data points to a sample lead, and check the sample lead score to ensure your system is working correctly and assigning scores as it should.
Evaluate your scoring model every month based on customer interactions and conversions, and adjust lead scores as needed.
If you have recently acquired a new customer in an industry that you were otherwise not targeting, it may be helpful to add a lead scoring rule based on the business category and assigning a higher value to the data point.