Predictive Scoring is a feature of Marketing Cloud & use the historical CRM data to score the Lead of how much they are interested into the business.

Predictive Scoring as a Data Science

It uses the technique of data science to score the likelihood of the customer’s getting engaged. Now with the help of Predictive scoring it’s easy for the marketers to analyze the graph using Dashboards in Salesforce of how many are interested and how much they will pay to buy the product. This functionality gives marketers the power to understand the behaviors that drives the customer engagement.

Predictive Audiences is a smart tool that unifies the customer data by grouping the audiences according to the interested ones, unsubscribed ones etc. For example, if a customer has a high likelihood score & if he is tending to unsubscribe it, then a retailer can then launch a re-engagement journey with the better content to deliver the better outcomes. And when the people start getting engaged into the new outcomes their likelihood to unsubscribe goes down & then they will be automatically routed towards the new journey of leading high scores.

Predictive Scoring is a technique which tends to improve the result quality obtained by Sales teams during the qualified Stages of the Leads and thus helping them in predicting the number of Leads with greater success. This will help teams in focusing the highly qualified leads first & then on the lower qualified leads. And hence maintaining team’s effort & time.

With Predictive intelligence, B2B marketers are now able to look at the displayed contents/metrics which shows the total count of downloads to identify the top performing content through deeper insights about which portion attracts the highest quality Leads, works for larger deals.

Predictive models work by analyzing the customer data from internal systems of records like CRM system and combine it with external signals to predict about the prospect whether they are suitable for buying the product or not. By these Predictive analytics allows us to deal with real time data so as to get the relevant data & thus attractive to the buyer’s.


  • It helps in building the slimmer fit scoring models on Leads, Contacts, Opportunities & Account object.
  • It uses the activity data & implements the highly accurate behavior scoring models accordingly.
  • It increases the rep productivity by routing the high scoring Leads to Sales.
  • With the help of Reports & Dashboards, it’s easy for them to track the performance & hence helpful in decision making.
  • Serve the good leads that are getting missed.

Best App for Predictive Scoring – Infer: Predictive Lead Scoring,, Lattice Engines

These are the apps which doesn’t need more then Name & an Email to predict which all Opportunities are interested & Leads to get converted.

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About Author
Nirupama Shree
Nirupama Shree
Nirupama Shree is currently working as a Business Analyst at Girikon, managing projects related to Salesforce. She has work experience in requirement gathering, blogging, maintaining client relations and has experience in technologies like Salesforce, Magento, Opencart. In her leisure time, she loves listening to music.
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