Likely buyers in Poplar

Why use predictions for likely buyers?

To be able to know which of your leads and prospects are most likely to buy your product is to have the leg up on your competitors.

The most effective way to predict likelihood to buy is with machine learning. You can take people just like that lead or prospect you're looking at–similar hobbies, income, lifestyle, and more–and use their historical actions to predict whether or not your they'll take that leap and convert.

Faraday makes predicting likelihood to buy for both individuals and geographies intuitive & easy, and delivering it to any channel in your stack a breeze.

With likely buyer predictions in Poplar, you'll give your team the ability to focus on only those people that are most likely to buy, meaning time is never wasted on bad fits.

Follow the steps below to get your likely buyers predictions into your Poplar account.


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

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

Getting started with likely buyers in Poplar

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

Requirements for this likely buyers recipe

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

Screenshot of the cohorts listing that includes Mailable U.S. population and Customers

Building predictions for likely buyers in Poplar

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

Describe your likely buyers predictions with outcomes

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

Creating an outcome for likelihood to buy.

Let's make an outcome for likelihood to buy.

  • In the navigation sidebar, choose Outcomes. Screenshot of the outcomes list
  • Click the New outcome button.
  • Fill out the form:
    • Select Everyone. This option will be disabled unless you have a contract with Faraday. Contact sales for a to demo.
    • 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 buy". 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 likely buyers 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 to buy
    • For Population to include, choose the following:
      • A cohort representing your mailable u.s. population
    • Enter a memorable name, like "Likely buyers 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 Filter section of Advanced Settings
  • Click Add payload filter
  • From the dropdown, choose an outcome from the list
    • In the dropdown on the left, choose Greater than or equal to
    • On the right, enter the value 86.
    • Click Add another condition.
    • In the dropdown on the left, choose Less than or equal to
    • On the right, enter the value 100.
  • Expand the Limit section of Advanced Settings
    • From the dropdown, choose an outcome from the list
    • From the next dropdown, choose Only the top (count)
    • Set the count to 100000 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 likely buyers predictions in Poplar

With your pipeline deployed, it's time to plug your likely-to-buy 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 likely buyers as a CSV.
  2. Navigate to Poplar's Audiences dashboard, then click new audience in the upper right.

Image of Poplar new audience creation

  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.

Image of Poplar CSV upload

  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.

Image of Poplar field mapping

  1. As we already know that this CSV includes only the most likely buyers, 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 only the best fits.

Prior to mailing to your new likely buyers list, we recommend running a National Change of Address (NCOA) scrub to ensure strong deliverability rates. 🔒 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.