Metrics

Metric Availability

To view which data is available for a deal, consult the Deal model, for example at the Deal endpoint. Any Deal model will contain metadata in the data field specifying which metadata exists. The metric data is populated by Termina based on the raw data, financials, and other files uploaded for any given deal.

Within the data field of the Deal object, the following fields specify the requisite parameters to access the various available metrics:

  • financials_exist specifies if the financials exist, where the Financials with the deal_id will return the financials metrics response.
  • product_metrics contain the list of user_type and metric combinations have been parsed from the raw data, which are then available for query through the Product module.
  • unit_economics_metrics contain the list of user_type whose unit economics are available in the Unit Economics module, which require the user_type have a revenue metric.
    • Note: at this time each user_type is treated independently, and holistic unit margin caculations are not supported.
    • Each user_type is treated as receiving the entirety of acquisition spend. Unit margin can be modeled from these constitutents.
  • benchmarks_exist specifies whether or not benchmarks have been materialized.
    • Benchmarks will exsit for every user_type that contains a revenue metric.
  • benchmark_categories specifies the list of major categories for which a company was labeled.

Metadata and Data Explanations

We strive to provide comprehensive descriptions and documentation of the metrics we calculate. The Product, Financials, and Unit Economics modules are largely self-descriptive, and we will update our documentation with more detail on their glossary as it is completed.

The Benchmarking metadata comes at multiple levels

  • Global metadata: General metadata about the benchmarking modeling provided by Termina. Some examples:

    • Describe each field in the benchmarking data responses.
    • Describe the classes of models produced:
      • Quantile models, mapping quantiles of individual metrics at a given revenue scale.
      • Scaling models, mapping how one metric varies as another scales.
      • Tradeoff models, which describe the relationship between too fields at a given revenue scale.
    • Describe the benchmark categories.

  • Group-specific metadata: Metadata specific to an account / a group. Each group gets its own custom benchmarking labels and models tuned to the group’s private data partition.

    • These endpoints contain just the {group_id} as a path parameter.
    • Some examples:
      • List all of the available benchmark categories.
      • List available model names for the group.

  • Deal-specific metadata: Metadata for a specific deal.

    • These endpoints contain the {group_id} and the {deal_id} as path parameters.
    • For example, list the categories for a deal, the same as in the Deal.data.benchmark_categories model.