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Tutorials

Score prospects in real time using Signals and ML

Solution accelerator

  • Introduction

  • Set up notebook

  • Configure Signals attributes

  • Train the ML prospect scoring model

  • Create intermediary API endpoint

  • See scores in the browser

  • Conclusion

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Conclusion

In this tutorial you've learned how to build a prospect scoring system using Snowplow Signals together with a machine learning model, your own website, and your own Snowplow data.

What you achieved:

  • Used Signals to calculate attributes
  • Scored prospects using an ML model
  • Served live prospect scores in the browser

This tutorial is a starting point for exploring and using Signals APIs for your own needs and use cases.

Next steps​

Here are some ideas for further exploration:

  • Define more Signals attributes that are specific for your use cases and tracking
  • Act on the prospect scores and predictions in your application
  • Use attributes to trigger actions and decisions without the ML step
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