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Sponsorship Impact · for sponsors, agencies and rights holders
Visibility is not impact. Behaviour is.
A sponsorship works when fans start searching for the sponsor, follow it and talk about it. Rascasse measures exactly that: across the whole deal against your competitors, and on every single match day.
- Share of search
- Share of voice
- Match-day signals
Fictional example: FC Rascasse, Nordwind Energy and its competitors do not exist. The numbers show how the analysis reads.
Used by commercial and partnership teams in sport and the brands behind it
The weak spot
Logo visibility counts seconds, not effect
Most sponsorship reports measure how often the logo was on screen. That is useful for the media value, but it does not show whether the deal changed anything.
Logo counts measure how often a brand was visible, not whether anyone cared.
Millions of impressions say nothing about whether fans searched, followed or bought.
Visibility reports rarely show what competitors did in the same period.
The report arrives after the season, when the budget for next year is already set.
Our thesis
A sponsorship that works shows up in behaviour.
If fans notice a sponsor and like what they see, they act: they search for the brand, follow it and talk about it. These signals can be measured every day, for the sponsor and for its competitors, before and after the deal.
- Search: Google search volume and trends for the sponsor and its competitors
- Share of search: the sponsor’s share of all searches in its category
- TikTok and Instagram: followers, views and engagement, daily
- Wikipedia: page views as a signal of interest beyond the fan core
- Match days: the sponsor’s signals on every match day against the days without a match
Has the whole sponsorship moved the brand?
Share of search and share of voice show over time whether the sponsor has gained against its competitors since the deal started. Always with both periods, the absolute values and the change.
Fictional example: FC Rascasse, Nordwind Energy and its competitors do not exist. The numbers show how the analysis reads.
Which match days move your brand?
The match-day analysis compares the sponsor’s signals on every match day with the days without a match. So you see which fixtures work, and you can launch campaigns while it matters.
| Match | Result | Uplift | Searches |
|---|---|---|---|
| vs RiversideHome · Sat 18:30 · TV | W 4:2 | +89 % | 41K |
| vs BergstadtHome · Sat 15:30 | W 3:1 | +76 % | 38K |
| Cup at WeidenauAway · Wed 20:45 · TV | W 2:0 | +62 % | 35K |
| at NordheimAway · Sun 17:30 | W 1:0 | +54 % | 33K |
| vs AltmühlHome · Fri 20:30 | L 0:1 | +38 % | 30K |
| at HafenburgAway · Sun 13:30 | D 1:1 | +31 % | 28K |
Average match-day uplift: +58 %. Home matches on TV lead.
Fictional example: FC Rascasse, Nordwind Energy and its competitors do not exist. The numbers show how the analysis reads.
Rascasse inside Claude and ChatGPT
Connect Rascasse to your AI assistant through MCP and ask how a sponsorship is doing, with the same signals as the dashboards and reports.
- Works with Claude, ChatGPT and other MCP clients
- Any sponsorship in the database, any competitor set
- Available as part of your agreement, API included
Yes, the signals point clearly upwards since the sponsorship started:
| Signal | Before | After | Change |
|---|---|---|---|
| Share of search | 14.1 % | 22.6 % | +8.5 pts |
| Monthly searches | 48K | 81K | +69 % |
| TikTok + Instagram followers | 118K | 204K | +73 % |
| Match-day uplift (average) | – | +58 % |
Home matches on TV deliver the strongest uplift (+89 % against Riverside). Plan campaigns around these fixtures first.
Fictional example.
What you get
From impressions to evidence
Choosing the next partner? See Sponsorship Matching & Pitch. Planning the activation? See Sponsorship Activation.
Start small
Start with a Proof Case
One sponsorship, before and after against three competitors, plus the match-day analysis of one season. A fixed scope and a fixed price, presented to the people who decide, and credited against the Annual fee if you continue.
Renewal talks start months before the contract ends. Bring numbers, not impressions.
Questions
Before you ask
Is this causality?
We show what changed in the sponsor’s signals since the sponsorship started, compared with competitors in the same period and with days without a match. That is strong evidence, not a controlled experiment, and we say so in every report.
Which signals do you use?
Search volume and share of search, Google Trends, TikTok and Instagram, Wikipedia page views, and match-day patterns for each fixture.
How far back can we look?
4 to 10+ years of history, depending on the signal, so the period before the sponsorship is usually covered.
Can we measure a deal that has not started yet?
Yes. We set the baseline now, so the before period is clean when the sponsorship starts.
Is this personal data?
No. All signals are aggregated: no names, no e-mail addresses, no individual profiles.
Who is it for?
Sponsors who need to justify the budget, and rights holders who want to show partners what the deal delivered.
How do we start?
With a Proof Case: one sponsorship, before and after against three competitors, plus the match-day analysis of one season, at a fixed scope and price.
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