Systems and methods for real-time lead grading
AssigneeLeadscorz Inc.
InventorsBernard Patrick Murphy, Santiago Diez-Perez
Life of this patent
Estimating the term…
Abstract
A method for a lead grading platform can include: receiving a lead from a lead vendor, wherein the lead comprises lead attribute values; converting the lead attribute values to benchmark values; assigning the lead to a pre-determined cluster and a pre-determined sub-cluster based on the benchmark values; determining a grade for the lead based on the pre-determined cluster and the pre-determined sub-cluster; and responding to the grade being greater than a threshold grade by delivering the lead to a lead consumer.
Claims12
A method for a lead grading platform, the method comprising:
- receiving a lead from a lead vendor, wherein the lead comprises a plurality of lead attribute values;
- converting the plurality of lead attribute values to a plurality of benchmark values;
- assigning the lead to a pre-determined cluster and a pre-determined sub-cluster based on the plurality of benchmark values;
- determining a grade for the lead based on the pre-determined cluster and the pre-determined sub-cluster;
- and
- responding to the grade being greater than a threshold grade by:
- delivering the lead to a lead consumer.
A lead grading system, comprising:
- a processor;
- and
- non-transitory memory storing instructions, that when executed cause the processor to:
- receive a plurality of leads and a plurality of conversion event records for the plurality of leads, wherein each of the plurality of leads comprises a plurality of lead attribute values;
- convert the plurality of lead attribute values into a plurality of benchmark values based on the plurality of conversion event records;
- filter the plurality of benchmark values to produce a plurality of filtered benchmark values;
- encode the plurality of leads as a plurality of lead vectors comprising the plurality of filtered benchmark values;
- cluster the plurality of lead vectors to form a plurality of clusters;
- determine average conversion probabilities for each of the plurality of clusters;
- and
- grade the plurality of clusters based on the average conversion probabilities of each of the plurality of clusters.
Dependencies are inferred from the claim text.