SEO Forecast

Date,Clicks,Impressions,CTR,Position
2025-01-06,9800,410000,2.4%,7.1
2025-01-13,9950,415000,2.4%,7.0
2025-03-17,8200,398000,2.1%,8.3
2025-06-02,8600,405000,2.1%,8.0
2025-11-10,10400,430000,2.4%,6.6

SEO Forecast projects organic traffic from your own analytics export and treats Google algorithm updates as permanent level shifts rather than temporary blips. For the theory behind the approach see SEO forecasting; to turn a projected traffic gain into a business case, pair it with the SEO ROI Calculator.

How to read the estimate

• The big % + arrow — projected change from now to the end of the horizon. Green is favourable, red unfavourable (and for inverted metrics like average position, a lower number is the good direction).
• 80% / 95% bands — prediction intervals from each model's real backtest errors. The 80% band is your realistic planning range; it widens further out because uncertainty compounds.
• Central dashed line — the model's best single estimate; the solid line is your actual history.
• Update markers — a bold vertical line with a measured % means a Google update moved your series; a faint line means a known update had no measurable effect here and was left out of the math.
• Anomaly dots — one-off outliers (an outage, a tracking glitch) that were down-weighted so they don't distort the baseline.
• Data quality score — a 0–100 read on whether you have enough clean history (ideally two-plus yearly cycles) for seasonality to be identifiable.
• MASE in the backtest table — mean absolute scaled error; below 1 beats the seasonal-naive baseline, and lower is better.

How it works

Everything runs client-side. Your CSV is parsed and auto-format-detected, then the heavy work — decomposition, level-shift and outlier detection, model fitting, and a rolling-origin backtest — happens in a Web Worker so the page stays responsive and your data never leaves the browser. The tool fits several models (seasonal-naive, drift, ETS, Theta, and an updates-aware curve fit), scores each by repeatedly forecasting held-out slices of your own history, and picks the winner. Google updates from a bundled dates file are tested as candidate level shifts and only kept when they measurably moved your series. Prediction intervals come from those backtest errors, not from a formula — which is why they're honest about uncertainty.

Features

• Auto-detects GSC, GA4, Ahrefs (traffic + traffic value), Semrush, Adobe, Google Trends, and generic exports; weekly/monthly/as-uploaded aggregation.
• Five backtested models with an auto-pick by lowest MASE, plus a manual override.
• Algorithm updates modeled as level shifts, kept only when they moved your data; unlabeled shifts surfaced for you to label.
• Explain tab: seasonal-vs-real drop verdict, trend/seasonal decomposition, and counterfactual per-update impact.
• Backtest tab: how wrong each model was on your history, with an overlay of what the top models would have predicted.
• Compare & SoV tab: forecast multiple sites on one chart or as share of voice, with competitor-estimate calibration to your ground truth.
• Keywords tab: scenario math (volume × CTR-by-position) for ranking changes — no time series needed, with optional CTR-curve fitting from your GSC Queries export.
• Stress-test overlay, 80/95% bands, log scale, saved-scenario ghost line, and CSV/PNG/scenario exports.

Limitations

A forecast assumes no future algorithm update, content change, or SERP-feature shift during the horizon — it can't predict events that haven't happened, which is exactly why the intervals widen. It needs enough clean history (roughly two yearly cycles) for seasonality to be reliable; short or gappy series get wide bands and a low quality score. Third-party traffic and traffic-value figures (Ahrefs/Semrush) are estimates, not measured clicks — calibrate them to your own ground truth before trusting absolute numbers. The Keywords tab is scenario math, not curve-fitting, so it's only as good as the CTR curve and hit-probability you give it. And the example figures on this page are illustrative, not a benchmark for your site.

Frequently asked questions