AUTOMATICALLY PRIORITIZING SALES LEADS FOR EDUCATIONAL TECHNOLOGY PRODUCTS
The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of features associated with a sales lead for an educational technology product, wherein the set of features includes profile data from an online professional network. Next, the system uses the set of features to generate a set of quality indicators for the sales lead. The system then aggregates the quality indicators into a lead score representing a quality of the sales lead. Finally, the system outputs the lead score for use in managing sales activity with the sales lead.
1 . A method, comprising:
obtaining a set of features associated with a sales lead for an educational technology product, wherein the set of features comprises profile data from an online professional network;
using the set of features to generate, by one or more computer systems, a set of quality indicators for the sales lead;
aggregating, by the one or more computer systems, the quality indicators into a lead score representing a quality of the sales lead; and
outputting the lead score for use in managing sales activity with the sales lead.
2 . The method of claim 1 , further comprising:
using one or more of the features to identify the sales lead in a set of members of the online professional network.
3 . The method of claim 2 , wherein using the one or more of the features to identify the sales lead comprises:
applying a set of filters to the profile data for the members to obtain a subset of the members as sales leads for the educational technology product.
4 . The method of claim 3 , wherein the set of filters comprises at least one of:
a market segment;
an employment status;
a student status;
an employer; and
a company size.
5 . The method of claim 1 , wherein the set of quality indicators comprises:
one or more member-level indicators; and
one or more company-level indicators.
6 . The method of claim 5 , wherein the one or more member-level indicators include at least one of:
a learning and development indicator;
a prospect score;
an email domain indicator; and
a contact information indicator.
7 . The method of claim 5 , wherein the one or more company-level indicators include at least one of:
a learning and development indicator;
a customer ranking;
a potential spending; and
a predicted purchase behavior.
8 . The method of claim 1 , wherein using the set of features to generate the set of quality indicators for the sales lead comprises:
inputting one or more of the features into a statistical model; and
using the statistical model to produce one or more of the quality indicators.
9 . The method of claim 1 , wherein aggregating the quality indicators into the lead score comprises:
normalizing the quality indicators; and
combining the normalized quality indicators with a set of weights to produce the lead score.
10 . The method of claim 1 , wherein the set of features further comprises at least one of:
a company feature;
a recruiting feature;
a learning culture feature; and
an engagement feature.
11 . An apparatus, comprising:
one or more processors; and
memory storing instructions that, when executed by the one or more processors, cause the apparatus to:
obtain a set of features associated with a sales lead for an educational technology product, wherein the set of features comprises profile data from an online professional network;
use the set of features to generate a set of quality indicators for the sales lead;
aggregate the quality indicators into a lead score representing a quality of the sales lead; and
output the lead score for use in managing sales activity with the sales lead.
12 . The apparatus of claim 11 , wherein the memory further stores instructions that, when executed by the one or more processors, cause the apparatus to:
use one or more of the features to identify the sales lead in a set of members of the online professional network.
13 . The apparatus of claim 12 , wherein using the one or more of the features to identify the sales lead comprises:
applying a set of filters to the profile data for the members to obtain a subset of the members as sales leads for the educational technology product.
14 . The apparatus of claim 13 , wherein the set of filters comprises at least one of:
a market segment;
an employment status;
a student status;
an employer; and
a company size.
15 . The apparatus of claim 11 , wherein the set of quality indicators comprises:
one or more member-level indicators; and
one or more company-level indicators.
16 . The apparatus of claim 15 , wherein the one or more member-level indicators include at least one of:
a learning and development indicator;
a prospect score;
an email domain indicator; and
a contact information indicator.
17 . The apparatus of claim 15 , wherein the one or more company-level indicators include at least one of:
a learning and development indicator;
a customer ranking;
a potential spending; and
a predicted purchase behavior.
18 . The apparatus of claim 11 , wherein aggregating the quality indicators into the lead score comprises:
normalizing the quality indicators; and
combining the normalized quality indicators with a set of weights to produce the lead score.
19 . A system, comprising:
an analysis module comprising a non-transitory computer-readable medium storing instructions that, when executed, cause the system to:
obtain a set of features associated with a sales lead for an educational technology product, wherein the set of features comprises profile data from an online professional network;
use the set of features to generate a set of quality indicators for the sales lead; and
aggregate the quality indicators into a lead score representing a quality of the sales lead; and
a management module comprising a non-transitory computer-readable medium storing instructions that, when executed, cause the system to output the lead score for use in managing sales activity with the sales lead.
20 . The system of claim 19 , wherein the set of quality indicators comprises:
one or more member-level indicators; and
one or more company-level indicators.