Actuals — Forecast

eCommerce Revenue Planner

Full-year revenue (2026)
206,6 mill. kr
+14.7%vs 180,2 mill. kr (2025)
Revenue — actual to date
75,5 mill. kr
+14.6%vs same period 2025
Full-year orders
272.5K
+11.0%· 10.2M sessions
Blended AOV (full year)
758 kr
+3.3%vs 2025

This year vs last year

Solid = actual · dashed = forecast
Last year (2025)This year — actualThis year — forecast forecast begins

Forecast assumptions

Auto-derived from actuals vs the same periods last year. Override any to plan a different rest-of-year.
TrafficAuto
Flat index: +6.3% vs 2025 · 5 actual periods
% vs LY
Conversion rateAuto
Flat index: +4.4% vs 2025 · 5 actual periods
% vs LY
AOVAuto
Flat index: +3.3% vs 2025 · 5 actual periods
% vs LY
Avg order qtyAuto
Flat index: +1.3% vs 2025 · 5 actual periods
% vs LY

Period detail

12 periods · 2025 baseline vs 2026. Forecast rows are read-only — tick Actual to enter real numbers.
Tick Actual to enter real numbers
PeriodActual2025 — baseline2026 — actual / forecast
TrafficCVR %AOVQtyTrafficCVR %AOVQtyTransactionsYoYOrder linesYoYRevenueYoY
Jan
23.5K+15%53.6K+19%17,4 mill. kr+17%
Feb
18.7K+15%41.6K+16%14,3 mill. kr+21%
Mar
19.6K+11%42.7K+10%14,3 mill. kr+11%
Apr
19.1K+9%43.3K+12%14,6 mill. kr+15%
May
19.7K+5%43.4K+5%15 mill. kr+10%
Jun
18.1K+11%40.4K+13%13,5 mill. kr+15%
Jul
17.3K+11%38.5K+13%12,9 mill. kr+15%
Aug
19.7K+11%43.9K+12%14,8 mill. kr+15%
Sep
22.4K+11%50.1K+12%16,9 mill. kr+15%
Oct
25.1K+11%56.5K+12%19,1 mill. kr+15%
Nov
36.9K+11%85K+12%28,9 mill. kr+15%
Dec
32.3K+11%73.7K+12%25 mill. kr+15%
Full year9.6M10.2M272.5K+11%612.7K+12%206,6 mill. kr+15%

Math: Orders = Traffic × CVR · Order lines = Orders × Avg qty · Revenue = Orders × AOV. Forecast = last-year shape × your tracking index. Export CSV, edit in Excel, and import back — row count picks the granularity (12 = month, 52 = week, 365 = day).

Forecast methods

Flat indexActive

Divides total TY actuals by total LY same periods — one ratio applied uniformly to all remaining periods.

+ Simple and transparent. Easy to explain to stakeholders. Fully predictable.
- Weights January equally with last month. Misses acceleration or deceleration trends.

Best when: Stable businesses with consistent YoY growth throughout the year.

Recency-weighted

Each future period gets its own index. Near-term follows the EWMA level of recent YoY ratios (λ = 0.82). Reverts toward the long-run average the further out it goes (reversion ≈ 0.88/period — by week 16 the signal is mostly flat).

+ Captures recent momentum without locking in a single rate for all 52 weeks. Near-term is responsive, long-term is stable.
- A noisy week near the cutoff still skews the immediate forecast.

Best when: Businesses where recent weeks diverge noticeably from the annual average.

Trend-projected

Each future period gets its own index. Near-term extrapolates the OLS slope from the last actual period, blended with the long-run mean via the same reversion factor. Falls back to recency-weighted with fewer than 3 actuals.

+ Follows the direction of travel for the near term, then gracefully flattens out. Avoids both the flat-rate problem and runaway extrapolation.
- A short acceleration/deceleration period can produce a steep near-term slope.

Best when: Businesses with a clear, multi-week directional trend in YoY performance.