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The model evaluation dashboards answer questions about how well your predictive models are actually working. They are predictive and forward-looking: they show you the accuracy, behavior, and business impact of the scores generated by Allyy. (For descriptive historical reporting, see Analytics dashboards.)
Every model evaluation dashboard is automatically updated as new campaign outcomes roll in, letting you see exactly where a model hit the mark or where it needs tuning.

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Business Performance

These dashboards focus on the bottom line — helping you evaluate model quality, predict customer choices, and measure the real-world impact on your business objectives.

Classification

Propensity & Probability. Track how accurately the model predicts specific actions like email opens, conversions, or subscription churn.

Regression

Value & Amount. Track how closely the model estimates continuous numbers like expected donation amounts and lifetime value.

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Explainability (SHAP)

These dashboards peel back the “black box” of AI using SHAP values. They show you the exact donor data points, behaviors, and features driving the model’s predictions.

Classification SHAP

Why they take action. See the core behavioral features driving propensity scores, segmentation, and churn risks.

Regression SHAP

Why they give that amount. See which variables push expected donation amounts higher or depress customer lifetime value.

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Available business cases

Depending on your campaign goals, you can dive into dedicated dashboards for specific channels and supporter behaviors across the sections above.

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Classification metrics

Use these to prioritize outreach, optimize campaign budgets, and understand customer risk.
  • DM Propensity – Likelihood that a customer responds to direct mail.
  • TM Reachability – Probability that a customer can be reached via telemarketing.
  • TM Conversion – Likelihood that a telemarketing call results in a monthly donor signup.
  • SMS Conversion – Probability that an SMS campaign leads to a desired action.
  • Email Open & Click – Metrics tracking the likelihood of a recipient opening an email or clicking a link.
  • Subscription Churn – Probability that a subscriber cancels their recurring support.
  • Donor Segments – Models predicting Middle donor status, Active donor status, or Subscription Acquisition.

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Regression metrics

Use these to estimate expected revenue and long-term value to optimize your ask strings.
  • Expected Campaign Amounts – Individual tracking for expected revenue from direct mail (DM), telemarketing (TM), and SMS campaigns.
  • Lifetime Value – Estimated long-term financial value of a customer over their entire lifecycle.
Evaluating a new campaign’s success? Start with Business Performance → Classification to see your lift charts, then jump into Explainability → Classification SHAP to see why the model selected those donors.