Churn scores in Poplar

The most effective way to predict likelihood to churn is with machine learning. With machine learning, you can constantly keep your list of customers up-to-date with churn scores based on the historical data of similar shoppers, and plug your likely-to-churn customers right back into your stack, no PhD required. With churn scores in your stack, you're primed to jump in, offer a discount, a helping hand, or some other offer to keep them on board.

Faraday makes predicting churn scores for your customers intuitive & easy, and delivering them to any channel in your stack a breeze.

With churn score predictions in Poplar, you’ll give your team valuable insight to intervene before the customer makes that critical decision, exactly where and when they need it.

Try this recipe
or read the documentation
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Faraday + Poplar

Sync data from your stack
Use churned_customers propensity
Predict for customers
Deploy to Poplar

You can stay ahead of churn. Learn how from some of the best.

See how practical, powerful AI gives brands everywhere the boost they need to beat their goals.

Reebok and Walmart-Mattel pair with Faraday and Lob to share how they use data to drive retention.

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Learn how the meal delivery subscription brand was able to identify likely churners 5X better with machine learning predictions.

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Use Faraday for churn scores in Poplar and you’ll get . . .

  • Turnkey AI

    —

    no messing with code, models, or algorithms. Just point and click.

  • Built-in data

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    rich, responsibly-sourced profiles of 300 million U.S. consumers.

  • Deep integration

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    deploy your predictions throughout your stack.

  • Responsible AI

    —

    do AI right with industry-leading record-keeping and bias controls.

Let’s get predictive

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