Today, the creator economy is evolving faster than ever. However, there are still few tools available that truly help to understand which content formats perform well and which do not. While platforms offer vast amounts of data, they often lack the precise context needed to clearly explain what exactly works and why.
Against this backdrop, Yoola – one of the leading global creator-centric ecosystems, has recently launched YoolaStats, a next-generation YouTube analytics platform, which is rethinking how creators, networks, and brands approach performance and decision-making. By addressing key gaps in the market, from the lack of distinction between content formats to limited visibility into real performance trends, the product is offering a fresh, forward-looking way to amplify data insights, reframing how insights can be applied to the creator industry.
About the vision behind YoolaStats, the challenges it is aiming to solve and how data is shaping the future of the creator economy – read in the interview with Yury Smagarinsky, CEO of Yoola.
Q: What makes YoolaStats stand out among other products?
Yury: Most analytics tools just show you numbers. YoolaStats shows you what to do with them.
We’ve built three important and unique things:
- Full separation of Shorts and long-form content, because mixing them in one dashboard is an analytical mistake.
- Trending Score with Outlier Score, a metric that tells you whether 1 million views is a success or a failure for that specific channel.
- AI-driven analytics that optimize creators’ decision-making processes
We’re not building another dashboard with charts. We’re building a decision-making system for the entire creator ecosystem.
Q: If you had to pick just one “blind spot” in the current market that YoolaStats solves best, which one would it be?
Yury: The lack of context.
The market is obsessed with absolute numbers: here’s 1 million views. But what does that actually mean for a specific channel? If they normally get 5 million, it’s a failure. If they have 10,000 subscribers, it’s a breakthrough.
Most platforms don’t give you the answer. YoolaStats does. The Outlier Score compares results to the channel’s own historical baseline. That closes the biggest blind spot: not knowing where you’re actually heading.
Q: Why is it so important for creators to see their Shorts and long-form videos on separate dashboards?
Yury: Because long-form and short-form types of content are completely different universes. They do not just differ economically; they are operating like separate ecosystems with distinct patterns of engagement, retention, audience behaviour, conversion dynamics, and monetization metrics.
Aggregating views from Shorts and long-form videos into a single number can be misleading because it represents different levels of creator performance.
However, many platforms still combine these metrics into one total. Even if the numbers are looking similar, they are measuring completely different things.
Example: a creator sees 30% total view growth. Sounds great. But if Shorts drove 90% of that growth while long-form views are dropping, that creator has a business problem. Most tools hide this. We surface it.
Q: How does this separation change a creator’s strategy for audience engagement?
Yury: It forces creators to stop guessing and start managing.
With separation, creators see the real effectiveness of each format. They notice Shorts convert to subscribers at 2% while long-form converts at 8%, so they change their call-to-action. They see long-form retention drops after 60 seconds, so they change their hook structure.
Without separation, it’s just noise. With separation, it’s a strategy, not a guessing game.
Q: How do you define “next-generation analytics” in the creator economy?
Yury: Next-gen analytics isn’t about “what happened”, it’s about “what to do next.”
First-generation tools told you: you had 100K views.
Second-generation: your retention drops at 45 seconds.
Next-generation tools, like YoolaStats, tells you: relative to your baseline, this video is 40% stronger. Here’s why. And here are three steps to take next.
It’s the difference between a rearview mirror and a GPS. The rearview shows where you’ve been. The GPS guides you to your goal and recalculates when you make a wrong turn. We’re building the GPS.
Q: How does the platform help rights buyers identify territories where content is “ripe” for acquisition but currently under-leveraged?
Yury: Through our geo-blocking and localization filters.
It’s simple. A rights buyer logs in, selects a niche, region, and audience threshold. Then they apply the localization gap filter, which highlights channels already performing well in one region but lacking localization (subtitles, metadata, dubbing) in another.
Real case: A Korean animation channel was getting more than 2 million monthly views in Mexico despite having no Spanish metadata, subtitles, or localization.
Most analytics tools would look at those numbers and say, “Great job.” But we looked at them and saw a problem. Why was there so much demand from a market the creator wasn’t even actively serving?
Using our internal tools, we spotted the opportunity, helped shape a localization strategy, and the channel grew 4× in the following six months.
Stories like these are a big reason why we decided to turn our internal analytics stack into a product. The pattern remained the same: creators already had growth opportunities, which were actually hidden in their data. However, existing tools weren’t surfacing them. So, we built these tools for ourselves first, and after seeing the real impact they could have, it felt wrong not to make them available to other creators.
This isn’t hypothetical. This is how the market works when you have the right data.
Q: YoolaStats also targets rights buyers and localization providers. Why did you include these non-traditional users in a creator analytics tool?
Yury: Because the creator economy isn’t just about creators.
Rights buyers and localization providers work with the same public YouTube data, but they need different answers: “Which channels are undervalued in Germany?” “Who has viral potential in Brazil with no local presence?”
No one was building tools for them. We thought that was strange. They have budgets and pain points. We can provide a solution. They don’t need to be “traditional analytics users”; their unmet needs are enough.
Q: Network owners without CMS access are an important audience segment. How large is this underserved segment, and why has it been overlooked?
Yury: We’re talking about tens of thousands of mid-sized networks, aggregators, and talent managers worldwide.
Big analytics vendors chase enterprise contracts from the top 1%, networks with CMS, legal teams, and six-figure budgets. Everyone else simply isn’t on their radar.
They’re forced to work with Excel, exports, and a dozen open tabs. YoolaStats gives them what they should have had years ago: consolidated analytics across all their channels in one interface, no CMS required.
That’s not a luxury. That’s a basic operational necessity. And we’re solving it.
Q: YoolaStats provides data on creators involved in ad campaigns. How does this change how brands select influencers?
Yury: Brands stop choosing “the biggest” and start choosing “the right fit for the job.”
Right now, most brands look at subscriber counts. That’s an expensive and inefficient habit.
YoolaStats shows:
- Which creators are actively doing brand integrations?
- which brands they’re already working with (to avoid conflicts or find synergy);
- How their relative engagement compares to peers.
A brand can say: “I don’t need the biggest gaming channel. I need one whose audience over-indexes on eco-products, has run three campaigns in six months, and has an Outline Score above 80.”
That’s precision. And it’s only possible with the right data.
Q: YoolaStats includes ROI predictions and strategic recommendations. How advanced are these today, and how much is AI-driven vs. rules-based?
Yury: Right now, it’s a hybrid, and we don’t pretend it’s all AI.
Rules-based handles the fundamentals:
- historical baseline comparisons;
- format separation;
- threshold alerts.
AI handles the predictive layer:
- ROI forecasts based on historical campaigns;
- recommendations like “your audience engages best on Thursdays at 6 PM in this region;”
- Surfacing rising channels before they blow up.
The AI is trained on Yoola’s proprietary data, over a decade of managing thousands of channels. That’s our advantage. You can’t copy that in a month.
By the end of the year, we expect 60%+ of strategic recommendations to be AI-generated. But we will never be a black box. Every prediction comes with an explanation of why we think that way. Because trust matters more than magic.
