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    Predict customer behavior in a few lines of code

    @fdy/faraday-js
    const configuration = new Configuration({
      headers: { authorization: "Bearer YOUR_API_KEY" },
    });
    const faraday = new FaradayClient(configuration);
    // upload orders, identify customers
    await faraday.uploads.createUpload("orders", "orders.csv", file);
    const cohort = await faraday.cohorts.createCohort({
      name: "Customers",
      stream_name: "orders",
    });
    // segmentation for personalization
    const personaSet = await faraday.personaSets.createPersonaSet({
      name: "Customers",
      cohort_id: cohort.id,
    });
    // activation pipeline
    const scope = await faraday.scopes.createScope({
      name: "Customers Scores",
      preview: true,
      population: { cohort_ids: [cohort.id] },
      payload: { persona_set_ids: [personaSet.id] },
    });

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  1. Recipes/
  2. Churn scores predictions

Churn scores predictions

Leverage AI to predict which customers are at risk of churning, giving your team the opportunity to act before they make that critical decision. With that knowledge, your team is primed to jump in, offer a discount, a helping hand, or some other offer to keep them on board.

All Churn scores recipes

  • Churn scores in Aurora (MySQL)

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  • Churn scores in AWS Aurora Postgres

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  • Churn scores in RDS (MySQL)

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  • Churn scores in RDS (Postgres)

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  • Churn scores in RDS (SQL Server)

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  • Churn scores in Redshift Serverless

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