Definition:
Lead scoring is a process that consists of assigning a value, usually in numerical points, to each lead generated.
What is lead scoring?
Lead scoring is about scoring leads and depends on multiple factors. Among the factors we can highlight the demographic information that is provided through a form, the actions that have been carried out through the web or your interactions with the brand on other internet sites.
Lead scoring is a way to know how to prioritize leads, interact with them properly and improve the conversion rate.
There is no single model for assigning points to leads. Typically, data from the past is used to create an allocation system. You should examine the leads that have become customers and those that have not. It is a way to identify what aspects each type has in common and from there see what are the characteristics that indicate that a lead has a good chance of becoming a customer.
What is lead scoring for?
Lead scoring is widely used in digital marketing thanks to its usefulness when it comes to qualifying the business opportunities that can be generated in a company based on the degree of proximity to the lead.
For this, it is essential to take into account the interaction of users with the contents and RRSS of the brand. It is extremely useful to know whether or not the user is interested in carrying out any activity with our brand / company.
It is a way to know the interest that users have for the company, since they can be profitable or not aligned with the commercial criteria of the firm.
Types of lead scoring
As already mentioned above, there is no single way to do lead scoring. Each company has to decide how it is going to do it, which formula makes the most sense based on its characteristics and objectives. Lead scoring is generated by an algorithm that can be developed both manually and through artificial intelligence solutions.
Lead scoring can be:
- One-dimensional lead scoring. One-dimensional lead scoring is based on giving each of the leads a single score. The score ranges from 0 to 100. The higher the score, the more interest there will be in the company. In turn, it can be:
- Predictive. The final score incorporates a behavioral analysis that helps to know the probability that the conversion we are looking for will be made.
- Retrospective. The final lead score incorporates an analysis of their behavior that helps determine the likelihood that they will perform the conversion we are looking for.
- Multidimensional lead scoring. Multidimensional lead scoring assigns several variables to the same lead. In this way, several points about a user’s profile can be taken into account. For example: ideal customer, level of knowledge they have about our brand, phase of the sales process.
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