Trend Forecasting

It depends on your industry's volatility and how much historical seasonal data we have to work with — some categories forecast reliably 2-3 months out, others with strong cyclical patterns can go further. We're upfront about the confidence window for your specific data rather than promising a fixed horizon that doesn't hold up.

Both, when it helps — your internal sales and operations history is the core signal, and we layer in relevant external data like search trends, seasonality, or category-level indicators where it measurably improves accuracy. We validate that any external signal actually improves the forecast on your data before including it, rather than adding it for the sake of looking sophisticated.

A trendline extrapolation assumes the future looks like a straight continuation of the past, which breaks down around seasonality, promotions, or category shifts. Our models are trained to recognize those patterns specifically and adjust the forecast around them, which is why they hold up better around inflection points where a simple trendline usually fails.

We build the output to fit how your team already plans, whether that's feeding directly into your BI dashboard, a scheduled report to your planning team, or an API your systems can query. The forecast updates as new sales data comes in, so it's a living model rather than a document that goes stale after a month.