ds@mcpanalytics.aiEmail your data and your question and get an answer about your own data, with the method shown.Email your data and question. Get an answer.
Upload your data and get a complete forecast accuracy backtest report. Free.
The practical guide behind this tool: when it applies, how to read the output, and the traps that make it say the wrong thing.
Standard-library analysis: how good are the forecasts you already made? Map the period, the forecast, and the actual outcome (and optionally the horizon each forecast was made at) and get the full scorecard: MAE and RMSE in your own units, MAPE with its zero and asymmetry traps handled explicitly, sMAPE, MASE against both the naive and the seasonal-naive baseline, bias as a mean error plus the share of periods over- and under-forecast, a Diebold-Mariano test of whether the forecast really beats a baseline rather than just printing two numbers next to each other, actual against forecast over time, the error distribution, and accuracy broken out by calendar period and by forecast horizon.
Interactive line visualization
Interactive table visualization
Interactive bar visualization
Interactive histogram visualization
Interactive bar visualization
Interactive table visualization
Interactive table visualization
Plain-English reading of the results and what to do next.
Grade a demand or revenue forecasting process against what actually happened
See our FAQ for pricing, privacy and how the analysis works.
MCP Analytics. Forecast Accuracy Backtest. Free tool. https://mcpanalytics.ai/free/standard_forecast_accuracy. Accessed [date you used it].
Your turn
Bring your own data and the question you actually need answered.
MCP AnalyticsData science by email Send us your data and your question, and we will reply. ds@mcpanalytics.ai
Tell us what went wrong, in your own words. We capture the page you're on automatically, so no need to describe where you are.