Reference case · Brand Demand Scan · City theatre, Finland
Online revenue grew 120% in ten weeks, with no paid advertising.
A Brand Demand Scan showed Varkaus City Theatre what to fix on its website. The fixes were made in August 2026. Over the next ten weeks, online revenue grew 120% against the same weeks a year earlier, while the sales channel the website cannot reach grew 43%. The gap between the two is €17,568 of revenue that the fixes produced and the season did not.
Published with the client's permission
1 August to 15 October · 2026 against 2025
Where the growth came from
30% of the growth was the fixes. The rest was the season.
Of the theatre's 61% revenue growth in the period, 30% came from the website fixes and 70% from the production and the season. That split is measured, not modelled.
The production on stage, the season and ticket prices move both sales channels. The website moves only the online channel. The offline channel therefore shows how much growth the business would have had anyway, and the online channel shows that growth plus the effect of the fixes. Had online revenue grown at the offline rate of 43%, it would have been €17,568 lower.
No attribution model, no estimate of channel contribution, no survey: two columns from a sales export the theatre already held.
If the website also sent some buyers to the box office, that effect is hidden inside the 43%, and the €17,568 is a lower bound.
Take the two sales channels your last marketing change could and could not reach. Compare their growth over the same dates. If the reached channel outgrew the other, the gap is the first estimate of what the change produced. If both grew together, the cause was the market, the product or the season.
Who bought
The growth was new customers
The first question a CFO asks of the result above is whether existing customers simply moved from the counter to the website. The buyer history answers it. New customers at the box office grew 17%, the same rate as the offline channel overall, so nobody left the counter. New customers online grew 86%.
The online channel grew by adding buyers the business had not had before, and 68% of all new customers in the period arrived online, against 57% a year earlier.
New customers · 2026 against 2025
The testable version: split your buyer export by first-purchase date and sales channel. If new buyers in the physical channel stay flat or fall while the online channel rises, part of the online growth is channel shift. If new buyers rise in both channels, the online growth is new demand.
What remains
What the fixes recovered was smaller than what still leaks
The ten-week result came from the first round of fixes. The scan, run on 365 days of Search Console data to 12 October 2026, shows how much remains.
Nine in ten of the buyers the theatre captures already knew its name. More than half of the buyers who see the theatre in search results go elsewhere. More than a third of its growth potential sits with people who have not heard of it.
In revenue, over the same ten weeks: online revenue was €50,142. Demand Leakage of 55.88% means a further €28,019 of online revenue went to competitors from searches in which the theatre already appeared. Untapped Potential of 37.34% means a further €18,723 sat in category searches by buyers who did not know the theatre. The first round of fixes recovered €17,568. What remained unrecovered in the same ten weeks was larger than what was recovered.
Stage 02
The theatre continues into the RoI² Framework, because the leak is still larger than the recovery
The first fixes recovered €17,568 in ten weeks. In the same ten weeks the scan shows €28,019 still leaking to competitors and €18,723 sitting in category searches. That is why the engagement continues into Stage 02, the RoI² Framework. The first 90-day cycle begins in October 2026.
Stage 02 allocates marketing budget against the scan's figures rather than against last-click reports, and builds customer journeys for the searches in which the theatre already appears and loses the buyer, so that more of the demand already in the data is captured. Each cycle's result is confirmed by the theatre's own finance function against the baseline set here, and becomes the baseline for the next cycle.
The fee is a share of the incremental profit the cycle produces, confirmed by the theatre's own finance function. If there is no incremental profit, there is no fee. The only fixed cost is the build and maintenance of the system per 90-day cycle.
Online revenue was 47.7% of offline revenue in these ten weeks, against 31.0% a year earlier. If the share holds near 48% in November and December 2026, when the lead production no longer dominates, the shift is structural and the first cycle starts from it. If it falls back toward 31%, the 2026 figure was a production effect.
Method
Four exports the theatre already held. Nothing was installed.
Sales by channel. The ticketing system's sales export for Varkaus City Theatre (Varkauden Teatteri), 1 August to 15 October in 2025 and 2026, net of cancellations, split into online sales and all other sales.
Buyer history. The customer number on each sale, used to classify each buyer as new (first purchase since January 2023) or returning.
Search data. Google Search Console, the free report Google provides to every site owner.
Brand Demand Scan. The Enterprise tier on 365 days of Search Console data to 12 October 2026.
The old website stayed in production throughout the period. The new website launched on 14 October 2026, after the measurement window, so none of the growth above comes from it. No paid advertising ran at any point.
The same two columns exist in your sales export.
The test in this case needs one Search Console export and a sales report split by channel. With your average order value, the scan states your Demand Leakage in revenue, as it did here. The price is fixed and there is no follow-on commitment. If the gap is not in your data, the report says so.