> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.termina.ai/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.termina.ai/_mcp/server. ## Metrics Guide For detailed definitions of all metrics used in the Termina platform, see our comprehensive [Glossary of Metrics](https://www.termina.ai/glossary-of-metrics). --- ### Metric Availability To view which data is available for a deal, consult the `Deal` model, for example at the [Deal endpoint](/api-reference/deal-management/deal/get-deal). Any `Deal` model will contain metadata in the `data` field specifying which data 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](/api-reference/data/financials) with the `deal_id` will return the financials metrics response. * `talent_exists` specifies if talent/employee data has been processed for this deal. * `product_metrics` contain the list of `user_type` and `metric` combinations that have been parsed from the raw data, which are then available for query through the [Product](/api-reference/data/product) module. * `unit_economics_metrics` contain the list of `user_type` whose unit economics are available in the [Unit Economics](/api-reference/data/unit-economics) module, which require the `user_type` to have a `revenue` metric. * *Note: at this time each `user_type` is treated independently, and holistic unit margin calculations are not supported.* * *Each `user_type` is treated as receiving the entirety of acquisition spend. Unit margin can be modeled from these constituents.* * `benchmark_user_types` contains the list of user types with benchmarks available for this deal. Benchmarks will exist for *every* `user_type` that contains a `revenue` metric. * `benchmark_categories` (deprecated) specifies the list of major categories for which a company was labeled. Use the `/available-categories` endpoint instead for current category information. * `excel_export_exists` specifies whether the data export is available for this deal. --- ### Benchmarking Data The Benchmarking module provides comparative analysis against Termina's proprietary dataset of 1000+ companies. Data is available at three levels: #### Global Metadata General metadata about the benchmarking modeling provided by Termina, accessible via `/data/benchmark/metadata/` endpoints: | Endpoint | Description | | ------------- | ----------------------------------------------------------------------------------------------------------------- | | `/columns` | Describes each field in the benchmarking data responses, including units, scaling type, and performance direction | | `/models` | Describes the classes of models (scaling and tradeoff) with their constituent metrics | | `/categories` | Lists benchmark categories with friendly names and default user types | #### Account-Level Benchmarks Endpoints specific to an account/group with benchmarking models tuned to the group's data partition: | Endpoint | Description | | ------------------------------- | --------------------------------------------------------------------- | | `/quantiles/{category}` | Get quantile benchmarks for a specific revenue level and category | | `/scaling/{category}` | Get scaling models showing how metrics change with revenue | | `/tradeoff-at-scale/{category}` | Get tradeoff models for metric relationships at a given revenue scale | #### Deal-Level Benchmarks Benchmarking data for a specific deal within a group: | Endpoint | Description | | ----------------------------------- | ------------------------------------------------------- | | `/available-models` | List available model names for the deal's account | | `/available-categories` | List categories available for this deal's company | | `/quantiles/{category}` | Get quantile benchmarks using the deal's actual revenue | | `/tradeoff-at-scale/{category}` | Get tradeoff models for the deal | | `/combined-time-series/{user_type}` | Get time series of all benchmark metrics | | `/time-series-endpoint/{user_type}` | Get the most recent combined metrics snapshot | --- ### Understanding Benchmark Models #### Scaling Models Scaling models use Gaussian Process regression to show how metrics evolve as companies grow. Each model contains: * **raw_data**: Actual data points from the benchmark dataset. Each point is a dictionary with two metrics (e.g., `{"rolling_3m_annualized_revenue": 500000, "cmgr12": 0.05}`). * **pred**: The predicted trend line showing expected values at each scale point. * **bands**: Confidence intervals at different significance levels (alpha). A band with `alpha: 0.2` means 80% of companies fall within the low-high range. **Available Scaling Models:** | Model | X-Metric (Scale) | Y-Metric | Interpretation | | ------------------------------------ | ---------------- | --------------------- | ---------------------------------------------------- | | `12m_growth_vs_scale` | Revenue | CMGR12 | How 12-month growth rates decline as companies scale | | `6m_growth_vs_scale` | Revenue | CMGR6 | How 6-month growth rates decline as companies scale | | `12m_retention_vs_scale` | Revenue | Revenue Retention 12M | How retention varies with company size | | `margin_vs_scale` | Revenue | Operating Margin | How margins improve as companies mature | | `revenue_vs_person_years` | Person-Years | Revenue | Revenue efficiency relative to cumulative effort | | `employee_retention_vs_person_years` | Person-Years | Employee Retention | How employee retention varies with company maturity | #### Tradeoff Models Tradeoff models use normal distribution fitting to show the relationship between two metrics at a given revenue scale. Each model contains: * **scale**: The revenue range for this tradeoff analysis. * **raw_data**: Data points used in the model, each with two metrics (e.g., `{"quarterly_operating_margin": -0.25, "cmgr12": 0.06}`). * **discarded_raw_data**: Outlier points excluded from the model. * **areas**: Elliptical confidence regions. An area with `alpha: 0.2` contains 80% of companies. **Available Tradeoff Models:** | Model | X-Metric | Y-Metric | Interpretation | | ----------------------------------- | ------------------- | -------- | -------------------------------------- | | `12m_growth_vs_margin` | Operating Margin | CMGR12 | Growth vs. profitability tradeoff | | `6m_growth_vs_margin` | Operating Margin | CMGR6 | Short-term growth vs. profitability | | `12m_growth_vs_sales_and_marketing` | S\&M % of Employees | CMGR12 | Growth vs. sales investment | | `6m_growth_vs_sales_and_marketing` | S\&M % of Employees | CMGR6 | Short-term growth vs. sales investment | --- ### Metric Definitions For detailed definitions of all metrics including CMGR, LTV/CAC, retention rates, and financial metrics, see the [Glossary of Metrics](https://www.termina.ai/glossary-of-metrics). Key metric categories covered: * **Cohorts**: Logo retention, revenue retention, LTV * **Concentration**: Gini coefficient, revenue share metrics * **Financials**: Revenue, margins, magic number, rule of 40 * **Growth Accounting**: CMGR, churn, expansion rates * **Talent**: Employee metrics, retention, productivity * **Unit Economics**: CAC, LTV/CAC ratios