High spenders in MySQL

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 MySQL, 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 MySQL 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 MySQL using Pipelines

Getting started with high spenders in MySQL

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

Screenshot of the connections listing that includes MySQL

Building predictions for high spenders in MySQL

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 mysql.

Create your pipeline for high spenders in MySQL

  • 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 MySQL". 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 MySQL

MySQL

  • In the Deployment area, find the MySQL module and click Add. Screenshot of the ready pipeline with no targets yet
  • Fill out the popup:
    • Provide the specified parameters for MySQL.
    • Click Next.
    • Choose the Identified option.
  • Click the Next button. Screenshot of the new target form, filled out
  • Skip the "Advanced Settings" by clicking the Finish button.
  • 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 MySQL

With your pipeline deployed, your high spend scores are loaded into your MySQL warehouse and ready to be plugged into your favorite marketing activation platform, where you can kick off a campaign to target not just those likely to become customers, but those most likely to spend big.

🔒 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.