Lead scoring is a method to evaluate and prioritize leads based on the their potential value to
Lead Scoring by Likelihood
This example uses a
user table to lead score potential users. The table contains basic information like the origin of the interaction (search, social, direct), the page they landed on, device used, and country of origin. If a user signs up, they will be assigned a user_id and otherwise this will remain NULL.
SELECTdata from the
usertable to create a CTE called "conversion". In this CTE, we create a new column
convertedwhich describes when a user has converted (signed up) or not.
PREDICTfunction is used to predict a value for the
convertedcolumn for each row in the
- To look at the lead potential, we select the rows where the model predicts conversion (
prediction='Converted') but the user has not yet signed up (
user_id IS NULL).
- The resulting rows are then ordered by the
probabilitycolumn in descending order. We return all of the columns from the
conversiontable (* indicates to return all columns), as well as the
The final result shows the users most likely to be converted! Try reaching out!
Understanding Lead Scores
This example shows how you can easily understand the drivers of lead scoring.
It's super simple - all you need to do is wrap your
PREDICT function with
EXPLAIN ! Infer then uses Explainable AI to examine your lead scoring model, and figure out what the drivers of conversion are.
The final result shows the importance of each column (features) in your conversion model. Now you can understand where is driving sign up and you can use this information to action on future targeting efforts!
Forecasting Lead Value
This example shows how you can forecast the value of a potential lead.
Here we simply predict the average user spend, for those that have not yet signed up. You could combine this with the previous example by multiplying the probability of signing up with the expected spend to get an overall lead score!
The final result orders the results by largest expected spend, so now you can focus on the customers with the biggest pockets!