Games, Video Creation / Data Product
Streamer Sponsorship Rate Vault (Glassdoor for Gaming Creators)
A crowdsourced, filterable database where Twitch, YouTube, and Kick gaming streamers submit real sponsorship deal terms (CCV/subs at time of deal, platform, niche, format, payout) and instantly see anonymized comparables, monetized via premium filters and a brand-side benchmarking tier.
Research Stage Progress
Composite of demand side (0-5) + competition side (0-5), scaled to 0-10, matching the scoring basis used across this library's other crowdsourced rate-benchmark data products. Demand side 3.6/5: the transparency gap is independently confirmed by five separate companies each building a formula-only or scraped-data substitute instead of a real payout database, plus a direct quote from a dedicated gaming-rates publisher (gaming creator pricing remains among the least transparent of any major content niche). The addressable population is real (7.3M monthly Twitch broadcasters, ~920K monetized nano-to-mid tier) and growing (gaming creator economy +26.2% YoY into 2026, 74% of marketers raising influencer budgets with an explicit shift toward mid-tier/micro creators), but smaller in absolute terms than adjacent freelance/salary-data analogues, and no first-person confirmation that streamers will disclose real payout numbers could be obtained (Reddit access stayed blocked through this research pass); NDA/exclusivity exposure at the mid-tier is a real, unquantified drag on data contribution. Competition side 2.9/5: zero of seven directly-checked competitors (Sponsorship.so, StreamScheme, InfluencerFee, Kenodo, SponsorRadar, StreamOptima, Collabstr) hold real crowdsourced deal data, a cleaner structural gap than most adjacent data-product categories show. Docked because three distinct competitor archetypes (rate calculators, sponsor-discovery databases, creator marketplaces) already have live distribution into this exact audience, and one of them (SponsorRadar, $29-99/month, 972K tracked YouTube sponsorships) has both the audience and the technical base to bolt on a submissions feature quickly if it chose to. Full detail, all figures sourced with clickable references and fact-checked, in the accompanying market research and competitor case-study reports.
Composite 0-10 covering financial viability, risk severity, and execution feasibility, calibrated against the same crowdsourced rate-benchmark methodology used for this library's freelance-rate analogue. Positive: the competitive gap is cleanly confirmed (0 of 7 directly checked competitors hold real crowdsourced payout data), the market tailwind is real (74% of marketers raising influencer budgets, 26.2% YoY gaming creator economy growth), technical build complexity is low, and two close analogues (Levels.fyi, Glassdoor) prove the give-to-get mechanic can reach scale. Negative and score-suppressing: bottom-up financial modeling (sourced CAC/churn/margin benchmarks, since no niche-specific data exists) shows the headline $9-15/month consumer subscription tier only clears a healthy 3:1 LTV:CAC ratio at CAC under roughly $30-40, thin to underwater at any realistic paid or referral acquisition cost; break-even under a lean cost structure (~700-950 paying customers) sits almost exactly at the top of the product's own optimistic Year 1 target, leaving little margin for error; and most importantly, the single biggest potential killer is that no first-person evidence, in either direction, could be obtained on whether streamers will actually submit real payout numbers given NDA and exclusivity exposure at the highest-value tier. This core assumption is unverified, not falsified, and is cheaply testable (estimated $48,000-67,000 lean build-and-validate path) before larger capital is committed, which is why the verdict is FEASIBLE rather than INFEASIBLE despite the unresolved risk. The B2B benchmarking tier ($200-500/month) has strong unit economics (6-30:1 LTV:CAC across base/conservative/stress scenarios) and is pre-validated by an operating competitor at the same price band, but its dataset value is entirely downstream of the unverified consumer submission assumption.
Streamer Sponsorship Rate Vault (Glassdoor for Gaming Creators)
Track: Games, Video Creation / Data Product | Market: overseas | Status: PENDING_RESEARCH | Created: 2026-07-11T08:00:00Z | Updated: 2026-07-11T08:00:00Z
One-liner
A crowdsourced, filterable database where Twitch, YouTube, and Kick gaming streamers submit real sponsorship deal terms (CCV/subs at time of deal, platform, niche, format, payout) and instantly see anonymized comparables, monetized via premium filters and a brand-side benchmarking tier.
Discovery Method
- Method: Trend Sniffer + Pain-point Extractor + Idea Generator
- Signal (Trend): Influencer marketing spend keeps climbing into 2026, with 74% of marketers planning to raise budgets and brands explicitly rotating spend toward mid-tier and micro creators over mega-influencers. Gaming carries the highest engagement rate of any content category. That rotation lands squarely on the tier of streamer (nano to mid) that has the least pricing power and the least data to negotiate with.
- Signal (Pain): A gaming-influencer rate guide states outright that "gaming creator pricing remains among the least transparent of any major content niche," tracing the cause to a market that grew through direct brand relationships instead of the agency ecosystem that standardized rates in beauty and lifestyle. Every existing "rate calculator" checked (Sponsorship.so, StreamScheme, InfluencerFee) turned out to be an algorithm applied to public viewer counts, not a live pool of what streamers actually got paid. Sponsorship.so's own documentation states it does not accept streamer submissions of past deals at all.
- Evidence: assets/evidence.md, direct-fetched quotes and figures from influencerfee.com, aspire.io, sponsorship.so, and backlinko.com
Demand Details
Who: An estimated 7+ million unique Twitch broadcasters go live monthly, with roughly 920,000 pulling in any platform revenue at all (about 13% monetize), a huge nano-to-mid tier that fields sponsorship offers with zero comparable data. YouTube gaming creators and the growing Kick creator base face the identical problem.
What they want: A place to check whether an offer is fair for their size and niche before replying to a brand DM. It's the same job Levels.fyi does for tech salaries and the same job lane 6 (Freelance Rate Benchmark Database) does for freelancers, except gaming sponsorship deal terms (flat fee, CPM-per-CCV, usage rights, exclusivity windows, VOD/clip add-ons) have no equivalent public pool anywhere.
How they express it: Every rate guide surveyed opens by acknowledging the same gap: streamers negotiate off formula-based estimates (CPM x CCV x hours) rather than real comparables, because no one has built the submission side of the equation. Direct Reddit search (r/Twitch, r/streaming) is blocked by the usual anti-scraping wall (see cross-cutting learning); the paper trail instead runs through the aggregator/rate-guide ecosystem that exists specifically to fill the void these guides admit is there. It's a strong indirect signal, graded at medium-high confidence rather than treated as a smoking gun.
Monetization model:
- Free: submit a deal, see the aggregate range for your CCV tier and niche
- Premium ($9-15/month): granular filters (game genre, deal format, brand category, exclusivity terms, geography)
- Brand/agency tier ($200-500/month): benchmarking access for sponsorship buyers who want to avoid overpaying nano/micro tiers relative to market
- Optional add-on: AI-drafted counter-offer / rate-card generator once a streamer has enough comparable data pulled up
7-Dim Triage Scores
Demand Pull 4 / Acquisition Feasibility 4 / Agent Advantage 3 / Low-Volume Economics 3 / Operator Hand Lightness 4 / Market Trend 4 / Policy Redline 4 -> Total 26/35
Score rationale:
- Demand Pull 4: The transparency gap is stated outright by industry rate guides and confirmed by inspecting three separate "calculator" competitors, none of which take real deal submissions. Docked one point because the evidence trail is aggregator-sourced rather than raw first-person streamer complaints (Reddit access blocked).
- Acquisition Feasibility 4: Streamer communities are dense, public, and used to sharing screenshots of offers already (Twitter/X creator circles, Discord servers, streamer subreddits), so a submission-and-share loop is a natural fit, mirroring the freelance rate benchmark playbook.
- Agent Advantage 3: An agent handles normalization, outlier flagging, and the query interface well, but the core asset is the crowdsourced dataset itself, not something AI generates on its own. Same structural ceiling as lane 6.
- Low-Volume Economics 3: Classic data-product cold start. The tool is close to worthless until it holds a few thousand submissions across enough niches and tiers to return a real comparable, not just an empty search.
- Operator Hand Lightness 4: Mostly a submission form, aggregation pipeline, and light moderation for spam or clearly fabricated entries; no professional-license or regulated-advice exposure.
- Market Trend 4: Budgets rising and shifting toward exactly the underserved tier (mid/micro/nano) that this product serves. A live tailwind, not a maybe.
- Policy Redline 4: No hard redline (this is factual rate benchmarking, not financial/legal/medical advice), but sponsorship contracts sometimes carry confidentiality clauses on payout figures. The product needs a clear "share only what you're free to disclose, figures displayed as ranges/aggregates" posture from day one, the same discipline lane 6 built in for freelance rates. Docked one point versus lane 6's 5 because sponsorship deals carry NDA risk more often than freelance invoices do.
Downstream Hints
- Key assumption to falsify: will streamers actually submit real deal numbers, or treat sponsorship terms as more sensitive than freelance rates (brand relationships, perceived leverage loss)? Research should check submission rates on any existing informal rate-sharing threads/Discords as a proxy, the same way lane 6's research checked Bonsai/lemon.io survey response rates.
- Known competitors are all algorithm-only: Sponsorship.so (confirmed via direct fetch: "does not accept streamer submissions of past deals"), StreamScheme's rate-card formula, InfluencerFee's tier guides, Kenodo's calculator. None hold real crowdsourced deal data. Closest structural analogue outside gaming: lane 6 (Freelance Rate Benchmark Database) and Levels.fyi for tech comp, both of which validate that professionals will trade data for peer comparables once a critical mass forms.
- Compliance: display only anonymized aggregates/ranges by default (never a single identifiable submission tied to a named brand plus named streamer without consent); add an explicit "you're responsible for checking your own NDA before submitting" disclaimer at the point of submission; no financial or legal advice framing, this is rate benchmarking, not deal-negotiation counsel.
- Cross-track note for research: this lane straddles Data Product (track 5) mechanics and the Games/Video Creation vertical (track 8). Track 8 had zero prior lanes in this library before this one; flag in _learnings.md track registry if research confirms this combined-track framing is the right shape going forward.
assets/ Evidence List
- assets/evidence.md, direct-fetched quotes and stats from influencerfee.com (transparency gap quote + rate tiers), aspire.io (74% budget-increase stat + mid-tier shift), sponsorship.so (confirms calculator-only, no submissions), backlinko.com (Twitch streamer scale)