Why the market needed Outset Media Index — and who it’s built for

Q: Mike, as someone who shaped the idea of the index, when did you first realize the market needed something like OMI?

Mike Ermolaev: It goes back to my first months in crypto PR. I entered the space in 2017, and within a couple of months it became obvious that there was no structured way to work with media outlets — no unified database, no clear understanding of how publications actually perform. I had to collect everything manually.

Even something as basic as a media list was a challenge. You had to build it piece by piece, and even then it was incomplete. And once you had it, it didn’t scale. Those gaps persisted for years, and nothing really addressed them — so we ended up building it ourselves.

Q: There are already tools that track traffic, SEO signals or mentions. What layer do they miss that OMI is trying to cover?

Mike Ermolaev: The first problem is fragmentation. You have Similarweb, Moz, Ahrefs, you name it. Each tool gives you part of the picture, but none provides a complete enough view to make informed decisions. To get anything usable, you have to constantly switch between platforms and combine outputs with your own experience.

Second, some data simply doesn’t exist in those tools. At the start, you don’t have a structured media list, pricing, formats or editorial requirements. You have to gather all of that yourself — talk to media, request guidelines, build internal databases and track changes over time.

Third, there’s data you can’t realistically collect without dedicated systems. That’s where our proprietary metrics, for example, Reprints and the Reprints Score, change how you look at media performance.

So OMI is not just another tool in the stack. It’s designed to replace the stack. Instead of assembling decisions from disconnected signals, you work from an organized dataset where both standard and non-obvious signals already exist — and they are already aligned.

Q: You describe OMI as a “reference layer for media intelligence.” What does that mean in practice?

Mike Ermolaev: It means this is the first product of its kind in this space. There are tools that cover parts of the problem, but nothing that structures media data this way on a global level, especially in crypto.

When something like OMI appears for the first time, it naturally becomes a reference point. Anything built later in the same category will be somehow compared to it.

Q: Do you see OMI as a tool just for PR specialists, or something more universal?

Mike Ermolaev: The audience is much broader than PR. First, advertisers, who need to understand where resources are best allocated, what to buy and what kind of return to expect.

Second, practitioners: PR, marketing, SEO, media buying. These are the people working with media daily, and for them OMI replaces guesswork with data-driven confidence.

Third, media outlets themselves. The index gives them a more complete overview of their own strengths, weaknesses and positioning in the market.

There are also researchers and analysts. We already see how our own Outset Data Pulse (ODP) uses OMI data to explain content dynamics, global media trends and regional patterns.

And finally, there are founders and C-level executives. They may not work with media directly, but they need to see where budgets go and what outcomes they drive. For decision-makers, OMI provides clarity without requiring operational depth.

From idea to product: How Outset Media Index was actually built

Q: OMI analyzes media across 37 different metrics. Sofia, as someone who turned the idea into a working product, how did the team arrive at this structure, and how did you decide which signals matter?

Sofia Belotskaia: It started with research. I ran a series of customer development interviews with PR and marketing managers, Outset PR’s partners and clients and media representatives, trying to figure out what people actually struggle with when working with media outlets.

The key insight was that while teams aim for visibility, they don’t fully understand what they get in return. That’s partly due to the nature of PR — it’s not performance marketing with clear conversion metrics. You’re dealing with attention, awareness and trust that can’t be measured in the same way as clicks. But that creates a problem: how do you know if you chose the right outlet to meet your concrete business goals?

And once that question appears, another follows — how do you justify budget decisions if the outcomes are vague? The market accepts that PR works, but measurement is still indirect and inconsistent. That’s why teams often stick to the same media brands. The process is more familiar and controlled: they know how fast editors reply, how submissions work and how coverage affects their brands.

But that limits options. Other outlets may perform just as well or better, but get overlooked because they’re less predictable. OMI is designed to surface those alternatives.

Meanwhile, not everyone needs the same thing. So the idea was to give teams a unified system that reflects different use cases. Some care about audience behavior, others about speed of publication. In many cases, needs are highly specific, and that’s why the structure includes several proprietary metrics.

A good example is Editorial Rigidity. We developed it ourselves to formalize something that usually exists as a “feeling” — how easy or difficult it is to place content in a publication.

At the same time, we acknowledge no one wants to analyze raw data for hours. That’s why some metrics are compressed into single indicators. For example, Composite Score captures traffic dynamics in one number, showing whether an outlet is growing, stable or declining.

One important distinction is between two final outputs for actual benchmarking: the General Score and the Convenience Score. While the former reflects the strength of an outlet — its audience, traffic dynamics and how content travels across the media space, the latter signals how it works in practice — pricing relative to reach, turnaround time, editorial flexibility.

These are deliberately separate. A media outlet doesn’t become “worse” just because it’s harder to work with. Larger publications often have more rigid processes — that’s a natural consequence of scale. The same applies to pricing.

Separating these dimensions allows teams to analyze media without distorting performance with operational factors.

Q: Each media outlet in the index has its own Media Profile page. What kind of insights can users get from these profiles?

Sofia Belotskaia: Formally, OMI is an index — a ranked list based on a defined methodology and two scoring logics. One of its core goals is to save time. What would normally take one or two days, we try to reduce to 10–15 minutes.

But if you look at OMI as a dataset, it becomes research-ready intelligence. Media Profiles add depth beyond the table view. They include parameters that are harder to organize in a single row, such as targeted markets, localization setup, aggregator presence and other practical insights, helping answer a simple question: is this outlet worth working with?

Media Profiles also contain historical data, giving a more comprehensive picture over time. In a year or two, they will allow retrospective analysis — how outlets evolved, what patterns repeat and what factors influence outcomes.

That’s valuable for anyone analyzing the market more broadly.

Q: The index is developing alongside Outset Data Pulse. From a product perspective, how do these two infrastructures work together?

Sofia Belotskaia: Outset Data Pulse actually came first and helped shape the index. Today, they are closely connected. OMI provides structured data. ODP builds on top of that to explain what’s happening across the media landscape.

The difference is in usage. OMI is a working tool that helps choose outlets, compare options and make decisions. ODP is an analytical layer. It examines the same data over time to identify patterns: how media outlets behave, how attention shifts, and what external factors influence visibility.

Raw data is sometimes enough. But often, context is what matters. Media doesn’t exist in isolation — especially in crypto, where external triggers strongly affect traffic and performance.

What comes next: From a single product to a broader analytical infrastructure

Q: Launching OMI effectively sets a new standard for media analytics. Do you think this could change how the industry works with media outlets?

Mike Ermolaev: That’s exactly the intention behind OMI: we want to move media work toward a more conscious approach. Right now, a lot of decisions are still based on intuition. What OMI introduces is a system where those decisions can be grounded in data.

If this approach spreads, it raises the overall level of how the industry operates. Teams become more precise in how they choose publishers, and publishers become more aware of how they perform and where they stand. In the long run, that benefits everyone — brands, communications specialists and editorial teams.

Q: If we look a few years ahead, how do you see OMI evolving?

Mike Ermolaev: OMI is just the starting point – the foundation for a larger ecosystem of products focused on how teams work with media outlets. What we have now is essentially an MVP: usable, but still an early version.

The advantage is scalability. We can expand beyond crypto into fintech, edtech, gaming and other verticals. The methodology is flexible enough to apply across categories. We can also improve the metric system by adding new signals and refining existing ones.

On the product side, we’re exploring features like allowing media representatives to contribute data directly, including GA analytics, pricing and editorial guidelines, with moderation to ensure consistency. From there, it could grow into a new interaction model between media and advertisers — potentially even a marketplace for placements.

Right now, OMI is in soft launch where the focus is on collecting feedback and prioritizing the next steps.

Q: If OMI reaches its full potential, how do you think it might change media strategy in the next five years?

Mike Ermolaev: The timeline is likely longer than five years. The platform will evolve with the market, and ideally, slightly ahead of it. I see OMI becoming a baseline tool — part of how decisions are made in this space. If it works as intended, the index will help brands approach media strategy with a clearer understanding of what they’re getting, how outlets behave, and what outcomes to expect.

Q: What improvements are planned after the soft launch?

Sofia Belotskaia: Right now, the focus is on user experience. One priority is more convenient benchmarking. Currently, users move between pages to compare outlets. We want to make that seamless — so multiple media profiles can be analyzed side by side.

We’re also improving how historical data is visualized. The numbers are already there, but they need to be easier to read. Another priority is expanding the dataset by adding more publications.

There’s also an open question around classification. We avoided traditional labels like Tier-1, Tier-2 and Tier-3 because they’re subjective. But users still need a way to interpret rankings correctly.

For example, local outlets in smaller markets may rank lower, but that doesn’t make them less valuable — they just serve different purposes. We’re exploring ways to reflect that through more accurate segmentation and filtering.

In sum, the methodological work is ongoing. As the index evolves, new questions emerge. And refining the model becomes part of the product itself.

P.S. Originally this article was published on OMI Blog.