Sales and marketing departments have actively started counting on lead scoring because it helps them save money and time by enabling them to focus their time on potential and most important customers. But, what is lead scoring?
Lead scoring is a powerful methodology that helps sales and marketing teams to identify their most potential prospects and worthy leads, and their current sales funnel. Basically, lead scoring is how organizations rank their leads on the basis of several behavioral and demographic factors to help you determine the most potential leads.
This presentation helps you to learn more about 'Predictive Lead Scoring With Salesforce Einstein'.
4. Lead scoring is a
powerful
methodology that
helps sales and
marketing teams
to identify their
most potential
prospects and
worthy leads, and
their current
sales funnel.
Lead scoring is
how
organizations
rank their leads
on the basis of
several
behavioral and
demographic
factors to
determine
potential leads.
6. Initially, lead scoring
was done manually.
It included running
thorough research on
potential customers,
registering their
information on a
spreadsheet, and
scoring them.
8. The
Adoption
of CRM
Assisted
Scoring
With the help of
CRM, companies
started collecting
data about every
single lead and
scoring them by
the software on
the basis of the
selected criteria.
10. When companies couldn’t find a
solid plan to reduce the time
invested in the research-based task,
marketing automation
emerged as the savior.
Marketing automation made it easy
to track the online behavior of leads.
12. Fast forwarding to today’s
time, predictive lead scoring
has been introduced to fulfill
the purpose of determining
which criteria identifies as a
strong lead. With the
introduction of Einstein AI,
Salesforce gave a new
approach to predictive lead
scoring. Salesforce has a
huge contacts and sales
database.
13. Sales Cloud Einstein, a
product of Salesforce,
analyzes fields that are
attached to the Lead object.
Then, it attempts using
distinct predictive models
such as Naive Bayes, Random
Forests, and Logistic
Regression. When it finds the
apt model, it selects the best
leads with its predictions.
16. Official Blog Link -
https://www.algoworks.com/blog/salesforce-
einstein-predictive-lead-
scoring/?utm_source=Slideshare&utm_campai
gn=Slideshare2algo