Faraday helps you solve this opportunity with data science. With our propensity modeling, you can see which current customers have the highest potential to buy more and other products of yours. According to a recent study by Gartner, for most organizations 80% of their future profits will come from 20% of their existing customers; Faraday can help you will find that key 20%.

The general concept of Faraday's machine learning models remains the same: Faraday compares your ideal most profitable customers to those who use your services and products at a minimal level. Then, we identify patterns in the data that correlate with one outcome or the other. For more on the basic idea of propensity modeling, see this article: How does Faraday propensity modeling work?

Key difference: "non-conversions"/bad outcomes are in fact customers—they're just customers who do not spend much money with you. On the opposite side, the desired outcome we're modeling for isn't just any customer, it's a customer who will stay with and be the most profitable. This way, when you go to score your general customer base, you get a clear contrast of the potential for Upsell and/or Cross Sell.

One key note: modeling for cross sell and upsell opportunities can have exceptional power because you tend to have so much more data on your existing customers than your prospects. Communication history, total sales to date, service calls, NPS, and more can fuel your predictions.

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