Free Time Series Forecasting with Plonky.aiv1.0.1

An online retailer wants to forecast monthly revenue for the next quarter to plan inventory and marketing spend. They have daily sales data for the past 2 years. Using Plonky, they can upload their transaction CSV, analyze for seasonality and outliers, and run a daily forecast that aggregates to monthly projections. The backtest can help validate accuracy before committing to decisions.

A media website with daily page views over 3 years needs to estimate traffic for the next month to allocate server resources and ad inventory. Plonky's daily forecast can capture weekly patterns and trend changes. The user should upload daily visit data, check for missing dates or outliers (e.g., viral spikes), and interpret the forecast with confidence intervals.

A retail chain with daily sales data across multiple stores wants to forecast product demand for next month to optimize stock levels. By using the batch forecasting tool, they can generate forecasts for each store or SKU simultaneously. Pre-forecast analysis should flag seasonal peaks (holidays) and any outlier promotion effects.

A SaaS company monitors daily server CPU usage and wants to predict future demand to auto-scale infrastructure. With 6 months of daily data, they can upload the time series, get a forecast, and set budget alerts. If usage is weekly seasonal, Plonky handles it well; monthly data would be less reliable and the user would be warned.

A utility company with daily electricity consumption data over 4 years needs to forecast load for the upcoming week to manage supply. Plonky can ingest the data, detect weekly and yearly seasonality, and produce a daily forecast. The user should check for anomalies like meter outages or weather-driven spikes.

Plonky offers a free tier with limited credits per month (e.g., 10 forecasts). Users pay for additional credits or subscribe for higher limits. This model allows beginners to test the service while generating revenue from power users or businesses needing large-scale forecasting.

Plonky charges per API call (forecast, backtest, data upload) or per data volume (e.g., number of time series points). This model suits developers and businesses integrating forecasting into their own applications, with predictable billing based on usage.

Plonky offers premium support and custom forecasting solutions for enterprise clients, such as integrating historical data from databases or building dashboards. This high-touch model generates significant revenue from clients with complex needs who require expert guidance.