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How our data works

How Streamforge data works

Streamforge began with the data. We started collecting our own because the numbers influencer marketing platforms reported didn’t match what the social platforms themselves said. This is how that data is built, how it has been tested, and how to test it against the creators you already know.

Our story

We built the database we needed ourselves.

Streamforge started in 2018 as a Discord community of gaming creators. Running it meant living inside Twitch’s API every day, so we could see what the platform’s own data said about a channel. When we compared that with what influencer marketing platforms were reporting, the gap wasn’t subtle. The industry was running on stale, flawed numbers.

We decided the only data we could trust was data we collected ourselves, and started building our own database. Then we put it to work. For years we ran creator campaigns for gaming publishers on it, Twitch first, then YouTube, Instagram and TikTok, and every claim the data made got tested against a real campaign. In March 2023 we opened the platform to customers.

That history is why data comes first here. Search results, audience reports and campaign numbers are only as good as the records underneath them, and we learned that with our own campaigns on the line.

If your current platform keeps missing creators you know exist, or tells you too little about their audiences to choose between them, bring those cases to an evaluation. They are the ones we would rather be tested on.

Data foundations

From platform records to creator intelligence.

Collecting a profile is the easy part. What makes the data useful is what happens next: connecting creator identity, content, performance and audience context so you can search, compare and explain a shortlist.

  1. Connect profiles and content

    Platform-specific records are organized into a shared model. Profiles are linked across platforms where identity evidence supports a match, while metrics retain the meaning of their source platform.

  2. Build creator context

    Creator analysis combines directly supported evidence from creator profiles, published content, and other public web sources with model-inferred qualitative details.

  3. Understand the audience

    Audience analysis combines demographic and psychographic estimates with interests, authenticity and community health, so you can compare a creator’s audience with the people your campaign needs to reach.

  4. Separate real engagement from noise

    Streamforge analyzes the comments on a creator’s posts, videos and streams using AI to detect bot behavior, writing styles, and repetitive phrases or comments that do not engage with the content.

Gaming context is part of the foundation.

Streamforge uses IGDB as its source of truth for game and genre metadata, then connects that taxonomy to creators and content on social platforms.

Explore game and genre context

Validation

Tested against platform data, and against other vendors.

Against first-party audience data

Streamforge’s audience analysis is AI-based and does not require the creator to authenticate through OAuth. The model was trained on first-party audience data, and in Streamforge’s tests its results are extremely close to the platforms’ direct metrics.

Audience analysis is supported across YouTube, Twitch, TikTok, Instagram, and X. Because no creator has to connect an account, you can research an audience before the creator has heard from you.

Read the audience analysis method

By buyers, side by side

Fortune 500 companies have tested Streamforge’s creator data side by side against other vendors. Streamforge came out ahead in every completed evaluation.

You can run the same test. Bring creators you know well and the audience you need to reach, then compare what comes back with what you already know to be true.

Book a demo

Methods

Explore how each part of the data works.

Follow the method behind the fields you use: how they are produced, how to interpret them and how they support creator decisions. Each explanation includes the coverage and context relevant to that data type.

Questions

Common questions

Has anyone outside Streamforge tested the data?

Yes. Streamforge has benchmarked its audience-analysis technique against first-party audience data from the platforms and found it to be highly accurate. Buyers have tested it side by side too. See “By buyers, side by side” above.

Who is Streamforge’s data built for?

Brands choosing creators for the customers they want to reach, agencies running campaigns for clients, and gaming teams planning creator partnerships. Streamforge is an influencer marketing platform for creator discovery, audience analysis, competitive intelligence, campaign workflow, and API data access.

Do creators have to join Streamforge for audience analysis?

Streamforge’s audience analysis is AI-based and does not require the creator to authenticate through OAuth. Audience analysis is supported across YouTube, Twitch, TikTok, Instagram, and X. This lets teams research audiences before a creator joins their program.

What should I test when evaluating creator data?

Start with creators you already know and the audience criteria that matter to your campaign. Check whether you can find those creators, compare their content and audiences, and explain why each belongs on the shortlist. Review the fields and update times you would actually use for the decision.

Can I use the data in my own product?

The Streamforge API provides programmatic access to creator, content and analysis data. Start with the public documentation, then bring your required platforms, fields and expected volume so we can work through the integration with you.

Influencer marketing guides

Put the research to work.

The guides take the research into campaign planning, creator vetting, outreach, rates, creative briefs and measurement. Build on the data with a process your team can use.

Try it against the creators you know.

Bring your current shortlist, the creators you’ve struggled to find, and the audience you need to reach. We’ll work through the data with you.