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Response Curves

Response Curves provide a visual representation of how a specific variable affects your KPIs (Key Performance Indicators). This tool allows you to explore the impact of varying a particular variable within a defined range, offering valuable insights into the relationship between the variable and your business outcomes, including identifying the saturation point where increasing the variable’s value no longer enhances the effect on your KPIs.

Steps to Generate a Response Curve

  1. Select a Country, Region, Grouping, Model, and a Dataset

  2. Select a Variable of Interest:

    • Choose the variable whose effect on your KPIs you want to analyze.
      3. Set Minimum and Maximum Values:
    • Define the range for the chosen variable by setting a minimum and maximum value. These values will be used to run the simulations.
      4. Advanced:
    • Select number of posterior samples.
    • Select a Date Range to be used.
      5. Submit:
    • Alviss AI will run a set of simulations using values between the defined minimum and maximum. For each value within this range, the app will calculate the difference in prediction compared to the prediction using the minimum value. The result is the predicted effect.
      6. View the Response Curve:
    • Go to the Response Curve’s details page to visualize the results.
    • The obtained effects are plotted as a function of the variable’s values. The response curve will show how changes in the variable influence your KPIs.

Benefits of Using Response Curves

  • Understanding Impact: Gain a clear understanding of how specific variables affect your business outcomes.
  • Identifying Trends: Visualize trends and relationships that may not be apparent from raw data alone.
  • Identifying Saturation Point: Determine the point at which increasing the variable’s value no longer results in an increase in your KPIs, helping to avoid unnecessary investments.
  • Informed Decision-Making: Use the insights from response curves to make data-driven decisions and optimize your strategies.

Example Use Case

If you are analyzing the impact of marketing spend on sales, you can use a response curve to see how different levels of marketing investment affect your sales KPIs. By setting the minimum marketing spend to $0 and the maximum to $100,000, you can observe how incremental increases in marketing spend influence sales. The response curve can also help you identify the saturation point, where further increases in marketing spend do not lead to additional sales, allowing you to determine the optimal marketing budget.

Response Curves are a powerful feature in Alviss AI, enabling you to explore and visualize the effects of specific variables on your KPIs comprehensively. Use this tool to enhance your analysis, identify key inflection points, and make more informed, data-driven decisions.