As a global leader in SEO, content marketing, and data analytics, Anastasia Braitsik has a unique vantage point on the evolving digital advertising landscape. We sat down with her to unpack the latest wave of updates from Microsoft Advertising, which promise to give marketers more control and deeper insights into their campaigns. Our conversation explored the strategic nuances of Performance Max, from acquiring new customers and gaining a competitive edge to balancing the power of automation with the need for creative oversight. We also delved into new targeting capabilities and the practical, day-to-day impact of a smoother cross-platform workflow.
With the new customer acquisition goal in PMax, how should advertisers decide between prioritizing new customers versus exclusively targeting them? Could you walk us through the best practices for assigning higher conversion values to find these new users effectively?
That’s a fantastic question because it gets right to the heart of business strategy. The choice between “prioritizing” and “exclusively targeting” really depends on your growth objectives. Prioritizing new customers is a balanced approach; it tells the system, “Hey, I value new customers more, but I still want to capture sales from returning users.” This is perfect for steady, sustainable growth. Exclusively targeting is a more aggressive, land-grab strategy. You’re telling the algorithm to ignore everyone else and focus only on net-new acquisitions, which is ideal for a new market launch or a major push for market share.
When it comes to assigning value, this is where advertisers need to move beyond last-click revenue. Don’t just add an arbitrary 20% to the value. You need to understand your customer lifetime value. If a new customer, on average, brings in three times more revenue over their lifetime than their initial purchase, that’s your starting point. You’re essentially teaching the machine what a new customer is truly worth to your business long-term. This transforms PMax from a short-term sales engine into a strategic tool for building a healthier, more valuable customer base.
PMax campaigns now include share of voice metrics like impression share and losses. How can advertisers practically use this data to become more competitive across Search and Shopping? Please provide an example of how this new visibility changes day-to-day campaign management.
For a long time, PMax felt a bit like a black box, and this update brings some much-needed light. These share of voice metrics are a game-changer for daily management because they provide competitive context. It’s no longer just about your own CPC or ROAS; it’s about how you stack up against everyone else in the auction. Imagine you’re a campaign manager and you see your conversions dip. Before, you might have just tweaked your budget or bids and hoped for the best. Now, you can look at your impression share lost due to rank. If that number is high, it’s a clear signal that your assets or ad quality are not competitive enough, not just that your bid is too low.
This changes the daily huddle. Instead of just asking “What was our CPA yesterday?”, the team is now asking, “Why did we lose 30% of our impression share to rank on our top-performing product group?” That insight immediately triggers a more strategic response—like refreshing creative, improving product feed data, or refining landing pages—rather than just throwing more budget at the problem. It’s a shift from reactive tweaking to proactive, strategic optimization.
Given the smoother import process for Google campaigns, specifically the support for more search themes and more forgiving asset group uploads, how does this practically reduce friction for advertisers? Could you share a couple of common, frustrating import errors this update helps solve?
The friction was immense, and these updates are a huge quality-of-life improvement for anyone managing campaigns across both platforms. One of the most common and maddening errors was the “all-or-nothing” import. You could have a perfectly structured asset group with dozens of components, but if a single auto-generated logo or an image with a slightly off aspect ratio was deemed ineligible by Microsoft’s system, the entire asset group would fail to import. It was incredibly frustrating and time-consuming to hunt down that one tiny issue. Now, the system is more forgiving; it will import the valid assets and simply skip the one that’s ineligible, which saves a massive amount of troubleshooting time.
Another major headache was the limit on search themes. Advertisers often build very granular campaigns in Google, and being forced to consolidate them to fit a smaller theme limit on import felt like you were compromising your strategy from the get-go. Bumping that limit up to 50 search themes means we can now mirror our complex Google structures much more faithfully in Microsoft Advertising, maintaining that strategic granularity without hours of manual rework. It’s about respecting the advertiser’s original intent and making multi-platform management feel less like a translation and more like a sync.
Autogenerated assets are now the default for new Responsive Search Ads, with reports of a 5% CTR lift. For marketers wary of automation, what are the key trade-offs between creative control and performance? What steps should they take to effectively monitor and guide these assets?
This is the classic control versus performance dilemma that defines modern PPC. The trade-off is clear: you’re relinquishing absolute control over every single headline and description in exchange for the machine’s ability to test combinations at a scale no human ever could, which can lead to that reported 5% lift in click-through rate. For a marketer who has spent years honing their ad copy, letting an AI write it can feel deeply unsettling. However, the key is to reframe your role from a copywriter to a creative strategist or editor.
You don’t just “set it and forget it.” The best practice is to provide the system with a strong foundation of your best, on-brand headlines and descriptions. Then, on a weekly or bi-weekly basis, you must review the “Asset details” report. See what the system has generated. Is it on-brand? Is it performing well? You can then “pin” the high-performing assets you like, remove the ones you don’t, and use the AI-generated winners as inspiration for your next round of human-written assets. You are essentially guiding the automation, steering it toward what works, rather than just handing over the keys.
With Content Targeting for Audience ads now widely available, how should advertisers decide between targeting specific placements like MSN versus broader content categories like Finance? What key insights should they look for in the new placement reports to refine their contextual strategy for better results?
The decision between specific placements and broader categories really comes down to your campaign funnel stage. For top-of-funnel awareness campaigns, casting a wide net with content categories like ‘Travel’ or ‘Finance’ is a great way to introduce your brand to a large, relevant audience. It’s about being present where your potential customers are spending their time consuming content related to your industry. As you move down the funnel toward consideration or conversion, targeting specific placements like MSN or Outlook becomes much more powerful. This is a more direct, high-intent approach, akin to buying a billboard on a very specific, high-traffic highway.
The new placement reports are your roadmap for refining this strategy. The first thing I’d look for is performance outliers. Are there one or two specific websites within a broad category that are driving the majority of your conversions? If so, you should consider creating a separate campaign to target those placements directly with a more aggressive bid. Conversely, you should be hunting for budget drains—placements with high impressions and clicks but zero conversions. Add those to your exclusion list immediately. This report allows you to continuously evolve your contextual strategy from a broad starting point to a highly optimized, efficient machine.
What is your forecast for the evolution of Performance Max on platforms like Microsoft Advertising over the next few years?
My forecast is that Performance Max will evolve from being just a “campaign type” to becoming the core operating system for advertising on these platforms. We’re seeing the first steps now with increased transparency and advertiser controls, and that trend will accelerate. I expect to see a move toward a “glass box” model, where the AI’s decision-making process becomes more visible to advertisers, building trust. We’ll likely see much deeper integrations with first-party data, allowing the system to optimize not just for a conversion, but for high-value customer segments defined by the business itself. The creative automation will also become far more sophisticated, moving beyond simple text generation to dynamic video and image creation tailored to specific audiences. Ultimately, the goal will be to create a true partnership between the advertiser and the AI, where the advertiser sets the strategic direction and provides the core ingredients, and the AI executes and optimizes at a scale and speed that’s impossible to achieve manually.
