Repeat purchasers in Salesforce

Introduction

Knowing which of your customers is most likely to buy again is key to keeping your customers on board and engaged to drive revenue.

The most effective way to predict likelihood to buy again is with machine learning. With machine learning, you can ingest your customer lists, predict their likelihood to buy again based on the historical data of similar shoppers, and plug your highest-scoring customers right back into your stack, no PhD required. With your repeat purchasers in your stack, you're ready to kick off a campaign to bring them closer to their next purchase.

Faraday makes predicting repeat purchasers among your customers intuitive & easy, and delivering them to any channel in your stack a breeze.

With repeat purchaser predictions in Salesforce, you'll give your team the ability to focus on the customers that are most likely to come back for more.

Follow the steps below to get your repeat purchasers predictions into your Salesforce account.

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

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

Getting started

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

Prerequisites

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

• A cohort representing your customers — or create one first
• A cohort representing your repeat purchasers — or create one first

Objectives

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

Outcomes

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

Likelihood to buy again

Let's make an outcome for likelihood to buy again.

• In the navigation sidebar, choose Outcomes.
• Click the New outcome button.
• Fill out the form:
  • For Eligibility cohort, pick the cohort that best represents your customers.
  • For Attainment cohort, pick the cohort that best represents your repeat purchasers.
  • Leave Attrition cohort blank.
  • Skip over Trait blocking.
  • Enter a memorable name, like "Likelihood to buy again".
• 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.

Pipeline

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

Create your pipeline

• In the navigation sidebar, choose Pipelines.
• Click the New Pipeline button.
• Fill out the form:
  • For Payload, choose the following:
    • Outcome: Likelihood to buy again
  • For Population to include, choose the following:
    • A cohort representing your customers
  • For Population to exclude, choose the following:
    • A cohort representing your repeat purchasers
  • Enter a memorable name, like "Repeat purchasers in Salesforce".
• Click the Save pipeline button.

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

Deploy your pipeline

CSV

• In the Deployment area, find the CSV module and click Add.
• Fill out the popup:
  • Choose the Identified option.
  • Skip the advanced settings.
• Click the Finish button.
• Click the Test deployment button and confirm the results meet your expectations. 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.

Conclusion

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

Creating a Salesforce Contact Field

First, we're going to create a Salesforce Contact Field for our repeat purchase 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 "repeat purchase score." Feel free to leave the character length limit as the default 18.

5. Click next, then choose the appropriate permissions required per your company's guidelines for which Salesforce users can view the repeat purchase score field–then click next again.
6. Finally, choose which page layouts you'd like the repeat purchase 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 repeat purchase scores CSV into Salesforce

Now that the custom field for repeat purchase 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 repeat purchase 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.

4. Select CSV in the right pane, choose the CSV you just downloaded from your deployment, then click next.
5. In the mapping step, map your contact fields appropriately, and select the repeat purchase score contact field you created to map to the row for the repeat purchase 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.

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

5. Click next and review your mappings.
6. Click Start Import to begin the import. When the import is complete, your contact cards will be populated with your Faraday repeat purchase scores, and you're ready to kick off campaigns targeting only the highest spenders.

🔒 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.