High spenders in Poplar

Why use predictions for high spenders?

Knowing which of your leads and prospects are most likely to spend big gives you the opportunity to serve them just the right offers at just the right time to drive revenue.

The most effective way to predict high-spend customers is with machine learning. With machine learning, you can constantly keep your lists of leads and prospects up-to-date with high-spend predictions based on the historical data of similar shoppers, and plug your high spenders right back into your stack, no PhD required. With your high spenders in your stack, you're ready to kick off a campaign to drive them to conversion.

Faraday makes predicting your high spenders intuitive & easy, and delivering them to any channel in your stack a breeze.

With high spend score predictions in Poplar, you'll give your team the ability to target not just those likely to become customers, but those most likely to spend big.

Follow the steps below to get your high spenders predictions into your Poplar account.


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

  • Organize your customer data into cohorts
  • Describe predictive models for high spenders with outcomes
  • Deploy high spenders predictions to Poplar using Pipelines

Getting started with high spenders in Poplar

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

Requirements for this high spenders recipe

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

Screenshot of the cohorts listing that includes Customers and High spenders

Building predictions for high spenders in Poplar

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

Describe your high spenders predictions with outcomes

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

Creating an outcome for likelihood for high spend.

Let's make an outcome for likelihood for high spend.

  • 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 customers.
    • For Attainment cohort, pick the cohort that best represents your high spenders.
    • Leave Attrition cohort blank.
    • Skip over Trait blocking.
    • Enter a memorable name, like "Likelihood for high spend". 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 poplar.

Create your pipeline for high spenders in Poplar

  • 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 for high spend
    • For Population to include, choose the following:
      • A cohort representing your customers
    • For Population to exclude, choose the following:
      • A cohort representing your high spenders
    • Enter a memorable name, like "High spenders in Poplar". 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 Poplar

CSV

  • 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 poplar 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 high spenders predictions in Poplar

With your pipeline deployed, it's time to plug your high spend scores into Poplar. Follow the steps below to create an audience in Poplar.

Creating a new audience in Poplar

  1. In your Faraday pipeline, click the Download CSV button under the deployment to download your high spend scores as a CSV.
  2. Navigate to Poplar's Audiences dashboard, then click new audience in the upper right.

poplar new audience

  1. Give your audience an appropriate name and optional description, then click create audience.
  2. In the view for your new audience, click upload CSV in the upper right.

poplar upload csv

  1. Select your Faraday deployment CSV in the file picker, and the page will load briefly.
  2. Map your CSV fields to Poplar fields. Most fields are likely to map automatically.

poplar field mapping

  1. As we already know that this CSV includes only the highest spend scores, we can safely select ignore this column for the two final columns indicating predictive scores.
  2. When finished, click continue to start the upload process.
  3. Once the upload is finished, you'll be presented with a confirmation screen indicating the total records imported. Click finish importing to finalize the import. You'll receieve an email from Poplar when your audience is ready, after which you can use it to launch campaigns to target these high 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.