Lead scores in Salesforce

Why use predictions for lead scores?

Knowing which leads are worth chasing–and which aren't–is key to keeping your teams focused and efficient in driving revenue.

The most effective way to predict a lead's likelihood to buy is with machine learning. With machine learning, you can ingest your lead lists as they come in, predict their likelihood to buy based on the historical data of similar shoppers, and plug the highest-scoring leads right back into your stack, no PhD required. No more time wasted on leads that were never going to convert in the first place.

Faraday makes predicting likelihood to buy for your leads intuitive & easy, and delivering them to any channel in your stack a breeze.

With lead score predictions in Salesforce, you'll give your team the ability to focus on only the leads most likely to convert.

Follow the steps below to get your lead scores predictions into your Salesforce account.

In this guide, we'll show you how to:

  • Organize your customer data into cohorts
  • Describe predictive models for lead scores with outcomes
  • Deploy lead scores predictions to Salesforce using Pipelines

Getting started with lead scores in Salesforce

Make sure you have a Faraday account (signup is free!) and that it's not in test mode.

Requirements for this lead scores recipe

You'll need the following cohorts available in your Faraday account:

Screenshot of the cohorts listing that includes Leads and Customers

Building predictions for lead scores in Salesforce

Now you'll create the prediction objective(s) necessary to complete this use case with Faraday.

Describe your lead scores predictions with outcomes

Outcomes use machine learning to predict whether or not people will exhibit a certain behavior.

Creating an outcome for likelihood to convert.

Let's make an outcome for likelihood to convert.

  • In the navigation sidebar, choose Outcomes. Screenshot of the outcomes list
  • Click the New outcome button.
  • Fill out the form:
    • For Eligibility cohort, pick the cohort that best represents your leads.
    • For Attainment cohort, pick the cohort that best represents your customers.
    • Leave Attrition cohort blank.
    • Skip over Trait blocking.
    • Enter a memorable name, like "Likelihood to convert". Screenshot of the new outcome form, filled out
  • Click the Save outcome button.

Faraday will do some magic in the background, so you can proceed with the rest of the instructions. When your outcome is done building, you'll get an email, and you can review your outcome.

Using Pipelines to deploy predictions to your stack

Now you'll configure the pipeline that deploys your predictions to salesforce.

Create your pipeline for lead scores in Salesforce

  • In the navigation sidebar, choose Pipelines. Screenshot of the pipelines list
  • Click the New Pipeline button.
  • Fill out the form:
    • For Payload, choose the following:
      • Outcome: Likelihood to convert
    • For Population to include, choose the following:
      • A cohort representing your leads
    • Enter a memorable name, like "Lead scores in Salesforce". Screenshot of the new pipeline form, filled out
  • Click the Save pipeline button.

Your pipeline will start building in the background. You can proceed immediately with the next set of instructions.

Deploying your pipeline to Salesforce


  • In the Deployment area, find the CSV module and click Add. Screenshot of the ready pipeline with no targets yet
  • Fill out the popup:
    • Choose the Identified option.

    • Choose Human friendly column headers.

  • Click the Next button. Screenshot of the new target form, filled out
  • Expand the Structure section of Advanced Settings
    • From the dropdown, select the salesforce preset. Screenshot of the second page of the new target form, filled out
  • Click the Finish button.
  • Click the Test deployment button and confirm the results meet your expectations. Screenshot of a target after hitting its test button the first time Faraday will finish building your pipeline in the background. When it's done, you'll get an email—return to the pipeline and click the Enable pipeline button to activate it.

How to use your lead scores predictions in Salesforce

With your pipeline deployed, it's time to plug your lead scores into Salesforce. Follow the steps below to see each Salesforce contact enriched with their lead score.

Creating a Salesforce Contact Field

First, we're going to create a Salesforce Contact Field for our lead scores so that we can assign them to our contacts appropriately.

  1. Navigate to the Fields & Relationships tab under Lead in Salesforce Object Manager.
  2. Click New in the upper right to create a new field.
  3. Select the number bubble, then click next.
  4. Name the field something unique like "Lead score." Feel free to leave the character length limit as the default 18.

Image of new custom field creation

  1. Click next, then choose the appropriate permissions required per your company's guidelines for which Salesforce users can view the lead score field–then click next again.
  2. Finally, choose which page layouts you'd like the lead score field to display on. We recommend including any layout that is used by your team. Click save to finish creating the custom field.

Importing your lead scores CSV into Salesforce

Now that the custom field for lead score is created, let's upload the CSV output from your pipeline.

  1. In your Faraday pipeline, click the Download CSV button under the deployment to download your lead scores as a CSV.
  2. Navigate to Salesforce's Data Import Wizard and select either Accounts and Contacts or Leads depending on how your account is configured. For this example, we're selecting leads.
  3. Select Update existing records, and ensure you're matching records by Email.

Image of update existing records selected

  1. Select CSV in the right pane, choose the CSV you just downloaded from your deployment, then click next.
  2. In the mapping step, map your contact fields appropriately, and select the lead score contact field you created to map to the row for the lead score. See the bottom row's "2, 69, 87" example below where each value is a score. The second-to-last row–the raw score–can be safely left unmapped and ignored.

Image of Salesforce import mapping data

For lead scores, the higher the score, the more likely it is that the contact is going to buy.

  1. Click next and review your mappings.
  2. Click Start Import to begin the import. When the import is complete, your contact cards will be populated with your Faraday lead scores, and you're ready to kick off campaigns targeting only the best ones.

🔒 It's a best practice to permanently delete any file that contains personally identifiable information (PII) after use. Any deployment from Faraday that is unhashed contains PII, and should be deleted after uploading it to your destination for security purposes.