Today, we’re thrilled to sit down with Anastasia Braitsik, a global leader in SEO, content marketing, and data analytics. With years of experience navigating the ever-evolving landscape of digital marketing, Anastasia has a unique perspective on the nuances of Pay-Per-Click (PPC) advertising, especially as it transforms in 2026 with automation and machine learning at the forefront. In this conversation, we dive into the shift from seeking absolute winners in PPC testing to embracing context and probabilities, the art of uncovering hidden audience segments, and the strategies for communicating complex data to stakeholders. Anastasia shares real-world examples and actionable insights on how to adapt to an algorithm-driven world where ‘it depends’ is often the most honest answer.
How have you seen the shift from declaring clear ‘winners’ to focusing on context-dependent results play out in your PPC campaigns, and can you share a specific example where a so-called ‘loser’ headline surprised you by performing well for a niche audience?
I’ve witnessed this shift firsthand, and it’s been a game-changer in how we approach creative testing. In the past, we’d pit two headlines against each other, wait a few weeks, and crown a champion based on overall click-through rates. But now, with platforms like Google Ads serving infinite ad variations to micro-audiences, it’s all about understanding who resonates with what. I remember running a campaign for a gourmet food delivery service a couple of years back where we tested a headline like ‘Soup Delivery’ against something fancier like ‘Charcuterie Board Delivery.’ Initially, ‘Soup Delivery’ tanked across the board, and I was ready to pause it. But when I dug into the asset performance report, I saw it over-indexed at 1.2 with an audience segment interested in ‘Restaurant Delivery.’ That niche group—think busy urban professionals looking for quick, comforting meals—loved the straightforward messaging. It wasn’t a global winner, but for that 10% of our audience, it was gold. So, instead of scrapping it, we kept it in rotation and crafted more tailored ads for that segment. It taught me to value asset liquidity over a one-size-fits-all result, ensuring the algorithm has options to match the right message to the right user.
Can you tell me about a time you encountered an unexpected performance spike in your PPC data, and what steps did you take to determine if it was a sustainable trend or just a momentary glitch?
Absolutely, those spikes can be both exciting and misleading if you don’t dig deeper. I recall a campaign for a tech retailer where we saw a 119% jump in performance for ‘Computers’ in a single week. My initial reaction was, ‘Did everyone suddenly decide to buy laptops?’ But I’ve learned not to jump to conclusions about user behavior. I started by cross-referencing the Insights tab in Google Ads, looking at device trends and auction dynamics. It turned out the algorithm had likely exhausted cheaper mobile inventory and shifted budget to desktop, which it previously deemed too expensive. I also noticed a competitor’s absence in certain auctions that week, making our bids more competitive. To confirm if this was sustainable, I extended the observation window beyond a week, monitoring for consistency while avoiding knee-jerk optimizations. It ended up being a momentary algorithmic opportunity, not a user-driven trend, so I didn’t overhaul the strategy. Instead, I used the insight to fine-tune our bidding approach for similar windows of opportunity in the future. It’s a reminder that volatility isn’t always a signal to act—it’s a signal to investigate.
How do you approach uncovering unexpected audience segments in your PPC campaigns, and can you share a story of discovering a surprising segment that shaped your strategy?
Uncovering unexpected audience segments is one of the most rewarding parts of modern PPC testing—it’s like striking gold in a data mine. My approach is to start with broad signals, giving the algorithm room to roam beyond my initial assumptions, and then I analyze the Audience Segment insights for surprises. A standout moment was working with a premium food brand where we initially targeted obvious groups like ‘Dining Out Enthusiasts.’ But the data revealed ‘Gourmet Food & Wine Enthusiasts’ converting at an index of 26.5, and even more surprisingly, ‘Busy Parents & Families’ indexing at 21.4. I hadn’t anticipated parents seeing food boxes as a time-saving luxury! That insight shifted our creative strategy entirely—we developed ads positioning our product as a convenient ‘Meal Kit’ alternative for family dinners. I relied heavily on Google Ads’ audience reporting tools to spot these segments, paired with qualitative feedback from surveys to validate the data. Seeing those families engage with our new messaging, with conversion rates climbing steadily, felt like cracking a puzzle. It reinforced that testing isn’t just about numbers; it’s about discovering who your audience really is.
With so many variables in PPC, how do you prioritize what to test, especially when focusing on creative assets over mechanics in an automated world?
Prioritizing tests in today’s automated PPC landscape is all about focusing on what I can control as a strategist—creative assets, landing pages, and first-party data inputs. I start by identifying areas with the most impact on user experience, like ad copy or visuals, since the algorithm handles much of the mechanical bidding and placement. Recently, I ran a test for a client’s landing page experience in a campaign promoting a subscription service. We had two versions: one with a minimalist design and a direct call-to-action, and another with detailed testimonials and visuals. My hypothesis was that the detailed page would build more trust, but I kept an open mind. After running the test for a few weeks and analyzing user behavior metrics like time on page and bounce rate, alongside conversion data, I found the minimalist page outperformed for mobile users, likely due to faster load times and simplicity. That insight led us to optimize all mobile traffic to the simpler design while keeping the detailed version for desktop. It’s about testing with purpose—starting with high-impact elements and using data to guide the next steps, rather than getting lost in endless variables.
How do you handle tricky conversations with stakeholders when PPC results aren’t black-and-white, and can you recall a moment where a client pushed for a clear answer?
Navigating those conversations is an art form, especially when stakeholders crave certainty in a world of ‘it depends.’ I focus on transparency and relatability, often leaning on analogies to bridge the gap. I had a client last year who was frustrated after a campaign test didn’t yield a definitive ‘winner’ for ad copy. They pressed me in a meeting, asking, ‘Just tell us which one is best overall!’ I took a deep breath and used the weather forecast analogy, explaining that PPC testing is like planning a picnic with a 60% chance of rain—you can’t predict the exact outcome, but you can prepare based on probabilities. I walked them through the data, showing how different headlines resonated with specific audience segments, and emphasized that our strategy was to let the algorithm match messages dynamically. I could see the tension ease as they nodded, appreciating the logic behind the ambiguity. By framing myself as their navigator—someone interpreting the data to steer the ship—I built their trust. They ended up more engaged, even asking deeper questions about audience insights in our next meeting. It’s about turning uncertainty into a collaborative journey.
How do you go about identifying patterns and affinities in your PPC campaigns, and can you share an example where focusing on ‘who likes what’ led to a breakthrough?
Identifying patterns and affinities is at the heart of modern PPC—it’s less about a single metric like click-through rate and more about understanding connections in the data. I spend a lot of time in asset reports and audience insights, looking for recurring themes in who responds to specific creatives or offers. A breakthrough moment came with a campaign for a home decor brand where I noticed a pattern: a certain visual style of minimalist furniture ads consistently resonated with an audience segment tied to ‘Urban Professionals.’ By focusing on this affinity, I realized they weren’t just buying decor—they were buying into a lifestyle of simplicity amidst chaos. We doubled down, creating a whole series of ads and landing pages with clean, uncluttered designs and messaging about ‘streamlining your space.’ I worked closely with the creative team to align every element, and we saw engagement rates soar within that segment. Turning that insight into action meant not just tweaking an ad, but reshaping the campaign narrative to speak directly to their values. It felt like we’d unlocked a secret conversation with that audience.
How do you identify and present quick wins to stakeholders to keep them engaged, and can you tell me about a time you shared an early victory that boosted their confidence?
Quick wins are essential for keeping stakeholders invested, especially in the gray area of PPC testing. I focus on mining the data for small, tangible victories—think a high-performing audience segment or a creative asset driving unexpected clicks—and I present them with clear visuals and context. Early in a campaign for a fitness app, I spotted a specific ad copy variation resonating strongly with a niche segment of ‘Busy Parents’ within the first two weeks. I put together a concise report highlighting the engagement metrics and paired it with a simple line like, ‘This messaging is already connecting with parents looking for quick workouts—let’s build on it.’ During our next call, I shared my screen, walked them through the numbers, and tied it to their broader goal of reaching everyday users. The client’s reaction was palpable—they lit up, asking how we could expand on this win. That early victory not only boosted their confidence but also opened the door for more experimental testing. It’s about showing progress, no matter how small, and framing it as a stepping stone to bigger results.
How do you adapt your mindset to work with probabilities rather than hard conclusions in PPC, and can you describe a campaign where embracing uncertainty paid off?
Adapting to probabilities over certainties has been a mental shift, but it’s incredibly freeing once you embrace it. I’ve trained myself to see data as a guide rather than a verdict, focusing on likelihoods and iterative learning instead of chasing a final answer. A campaign for a travel agency stands out where we tested multiple ad creatives without expecting a clear winner. I leaned into the uncertainty, using asset reports to understand which messages worked for different micro-audiences, like adventure seekers versus budget travelers, rather than forcing a single ‘best’ ad. Week by week, I adjusted based on probabilities—shifting budget toward creatives with higher likelihoods of resonating with specific segments—and watched conversion patterns emerge. Over time, this flexible approach led to a more dynamic campaign that outperformed our initial benchmarks, as we could serve the right message at the right moment. It felt like conducting an orchestra, blending different notes rather than playing a single tune. Embracing the gray area allowed us to innovate in real time, turning ambiguity into opportunity.
What is your forecast for the future of PPC testing as we move further into an automated, algorithm-driven landscape?
I see PPC testing becoming even more intertwined with machine learning and real-time adaptability over the next few years. The focus will likely shift further from manual control to strategic input—curating high-quality creative assets and first-party data to feed the algorithms. I anticipate that audience discovery will take center stage, with platforms offering deeper insights into micro-segments and affinities, pushing us to think beyond traditional targeting. My forecast is that successful marketers will be those who master the art of interpretation, turning probabilistic data into actionable stories for their brands. We’ll also need to get even better at communicating complexity to stakeholders, perhaps with new tools or visualizations to make the ‘it depends’ nature of PPC more tangible. Ultimately, I think the opportunity to learn and innovate in this space will only grow, as long as we’re willing to embrace the uncertainty as a strength rather than a hurdle.
