Over the past year, he’s been the architect behind our in-house tools like the syndication map, making data on media spread instantly accessible to PR managers instead of leaving it buried in spreadsheets. We spoke with Max about how this system came to life, why logic is the key to great media analysis, and how a strong analytical backbone is transforming the way our agency operates.
Nobody can sum up my job in one sentence. My duties are so varied that no two days ever look the same – and that’s not just a figure of speech. The core of my work is analytics, tracking syndications, and validating financial data, but tasks can come from almost anywhere.
Most mornings start with a financial routine for the sales team: checking invoice sheets and preparing client reports. That’s my daily warm-up. From there, I move into analytics for our ongoing Outset Data Pulse reports or “closing the loops” on earlier tasks. Sometimes I get very specific requests, like when our head, Anastasia, asks for Germany-only stats – how organic traffic is performing, what’s converting, and how sales look.
Right now, our media analyst, Alex, supports me with her own spreadsheets, which I then review and expand. While I can delegate some initial steps to her, most of the work still passes through me.
As for “typical” – in the early days, I could never predict what I’d be doing the next day. Now there’s a bit more structure, but unexpected challenges still pop up regularly.
Not at all. In early 2024, I didn’t even have a job. Around mid-2023, I reconnected with an old friend, and in April 2024 she suddenly asked, “Want some side work? We need someone to track syndications.” I thought, why not? She also happened to be friends with Mike – we had all studied at the same university – so it felt a bit like fate.
At first, I got a short instruction doc, and Anastasia was my main contact. Things went smoothly, and by May I was working full-time. I started with syndication tracking, but soon I was also helping sales with financial sheets – adding data on pricing, article counts, and more.
From there, the pace picked up fast. One task led to another: researching, building new spreadsheets, creating a shared database of media we worked with. After our fabulous November meetup, things ramped up even more – total crunch time. We had major campaigns for ChangeNOW, and the workload expanded. Between June and October, it was also non-stop: preparing data for client offers, building pitch sheets, closing syndication loops, and more.
Analytics was completely new to me. Before Outset PR, Excel honestly intimidated me. But I learned quickly – and even discovered I preferred spreadsheets over docs because you can pivot data in so many ways.
I wouldn’t say I had mentors in the traditional sense, but Anastasia and Mike definitely had the biggest impact on how I work. When I joined Outset PR, most of my communication was with them.
I’m naturally curious and ask a lot of questions, and they always took the time to answer. At first, it was more about being told exactly what needed to be done. Over time, I began adding my own structure and details to the tasks.
One thing that struck me right away was how different the culture here was from any place I’d worked before. No one breathes down your neck, you can adjust your schedule if needed, and there’s no rigid “9-to-5 or else” mentality. That flexibility doesn’t make you lazy – it actually makes you more invested in the results.
Anastasia and Mike often shared their vision for the final outcome of a task, whether it was a spreadsheet, an analytical report, or a client deliverable. I learned to take that vision and turn it into something not only functional but also clear and visually polished.
If we’re talking specifically about Outset PR, the syndication map moment stands out. But the real turning point wasn’t the idea itself – it was the pace of work leading up to it. November and December 2024 were intense: tight deadlines, back-to-back campaigns, no room to breathe. That urgency forced me to create tools faster, cleaner, and more adaptable. The syndication map was just one of many things born out of that pressure.
Another big moment was meeting our lead traffic hunter, Nikolai, in person. He showed me ways to automate parts of our workflow, which completely shifted my perspective. The meetup in Tbilisi was a catalyst overall: we saw how the rest of the team worked up close, which pushed us toward better collaboration and sharper execution.
It started out as nothing more than a raw stats spreadsheet – just rows of unstructured data. We had a few different ideas floating around, and I began building from there. Mike and Anastasia suggested making it more visually intuitive so anyone could quickly read and interpret the data.
Then I added my own twist: calculating the probability of getting picked up by certain aggregators. That’s when it evolved from a static table into a decision-making tool.
It all came together in just a couple of months. The idea surfaced in December 2024; by the year’s end, most campaigns had wrapped, and in early January I sat down to reformat everything from scratch. By February, it was fully functional – complete with formulas that automatically calculate the key metrics we care about.
Before we had it, a lot of work was manual. If Anastasia wanted to know which outlets had the most traffic or the strongest syndication chains, I’d have to dig through past campaigns and piece it together by hand. Now, anyone – say, our senior PR lead Seva building an offer – can open the table, filter by format or reach, and instantly see where a story will get the biggest syndication lift.
For example, if a company needs a top list article, I filter the table for media that publish this format, cross-check costs and placement conditions, and know within minutes which outlets to pitch.
If a site isn’t there, I add it on the spot. Over time, that builds into a comprehensive database of crypto-friendly publishers – something other players in the industry don't have right now.
The map has also become a powerful sales asset. When a client sees numbers like “this outlet brings X syndications on CoinMarketCap, Binance Square, etc.” right in the pitch, it’s much easier for them to understand why it’s worth the budget. That shifts the conversation from “just trust us” to “here’s the evidence.”
The first thing I look at is syndications: how well they performed and whether there were any issues during publication. Did the piece land in the section we targeted from the start? If it ends up in the wrong place, even great content can underdeliver.
Next, I assess how well the client’s profile is positioned. In crypto media, exposure depends heavily on whether the project already has a footprint. If they’re starting from zero, even the best placement won’t spread as far.
Finally, I review how many syndications each article generated, along with the direct impact in each outlet – views, reach, engagement. A campaign’s success is closely tied to how far those stories travel once they’re live.
Domain authority, for sure. PR people talk about it a lot, but in my experience, it doesn’t drive meaningful decisions. Then there are content quality scores and media rankings from tools like Ahrefs – but those can be wildly inconsistent. The same outlet might rank high on one platform and low on another, making them hard to treat as a reliable benchmark.
Sometimes a client wants those numbers included in an offer or even tries to plan a campaign around them. But the moment the rating isn’t flattering, their interest disappears. In many ways, it’s a vanity metric, and people outside the PR world tend to overvalue it. The truth is, it rarely predicts whether a placement will actually deliver results.
I’d say I always get useful feedback, and it’s generally positive. But the most valuable kind is when I’ve done something wrong and someone shows me how to make it better.
The key is tone. No one comes at you with, “What on earth did you do?” Instead, they explain step by step what needs improving so you can refine the outcome. That approach keeps you motivated instead of defensive – and it changes how you feel about your work going forward.
I’m not the type to write long instruction docs, so my style is very hands-on: I share my screen, walk through the process, and answer questions on the spot. If something doesn’t click right away, I’ll explain it again – sometimes more than once – until it does.
If a task is left incomplete, we’ll jump on a quick call to finish it together – no blame, just closing the gaps. When you’re teaching someone who’s never done this work before, it’s important to go deep into the details and never assume they already know the context.
I keep a steady rhythm of weekly check-ins. We review what’s been done, discuss challenges, and I suggest ways to make tasks faster or less repetitive. The goal is to avoid wasting time on things that could be automated or simplified.
I’m strict with myself. I have an almost obsessive need for everything to look and feel right: no cropped edges, no wrong fonts, no off-brand colors. It has to be readable, clean, and visually consistent. If something’s off, I’ll think about it even in my sleep.
And yes, I’m also strict with others, but I don’t expect them to match my level of visual detail. If something needs adjusting, I’d rather quietly fix it than turn it into a critique. When I do give feedback, I keep it calm and constructive, explaining what I’d like to see instead. I’m not a fan of simply pointing out flaws – I prefer to guide people toward the outcome I want.
First and foremost, logic. In fact, soft skills come before hard skills. You can teach the technical side of analytics, but if someone can’t think logically or communicate clearly, it won’t work.
You don’t need to be a math wizard. A basic grasp of percentages, formulas, and structuring data is enough to start. The real value comes from curiosity – knowing how to look for answers and not being afraid to ask questions. Even most calculations can be handled by a spreadsheet or a calculator; the analyst’s role is to make sure those numbers actually tell a story.
When Mike suggested I become the analytics team lead, this was exactly his point: if someone has the right soft skills, the rest can be taught. Finding a candidate with the exact hard skills we need, fully formed, would be much harder.
That said, in professional analytics you sometimes do need technical expertise – like writing basic algorithms or automating processes beyond what Google Sheets can handle. That’s where having someone like our operations manager, Daria, is a game changer: she can code when needed. And for everything else, you’ve got AI and Google to fill in the gaps.
If not Outset PR – then what? I’m in a place where what I do genuinely matters, surrounded by a team that’s always moving forward. It’s hard to imagine trading that for anything else.