Anastasia Braitsik is a renowned strategist in the digital advertising space, recognized for her ability to decode complex data into actionable growth. As Microsoft Advertising rolls out deeper publisher-level reporting for Performance Max campaigns, Anastasia shares how these updates are changing the landscape for media buyers who have long felt limited by automated systems. By moving beyond basic placement visibility into concrete spend and conversion metrics, this shift provides the transparency required to refine strategies with surgical precision.
Performance Max campaigns are often criticized for being “black boxes” because they hide the mechanics of how money is spent. Now that publisher-level conversion and spend data are visible, how should advertisers adjust their weekly auditing routines, and what specific benchmarks indicate a placement is worth scaling versus excluding?
With the addition of conversion and spend metrics to the Performance Max Website Publisher URL report, the “set it and forget it” mentality is officially dead. Advertisers should now spend time each week comparing the cost-per-acquisition across individual placements to see where the budget is truly leaking. A placement is worth scaling when it shows a healthy ratio of conversions to spend, proving it can drive real outcomes rather than just racking up empty impressions. Conversely, if you see a site consuming a significant portion of your budget with zero conversions to show for it, that is a clear signal to act. This new transparency allows us to feel the pulse of the campaign, moving from vague guesses about “algorithmic magic” to hard financial accountability every single week.
When specific URLs show high conversion rates but low impression volume, what is the step-by-step process for migrating those insights into Audience Ads or remarketing strategies? How do you balance these manual interventions with the platform’s automated bidding logic?
Identifying those “hidden gem” URLs is the first step toward building a robust multi-channel approach that lives outside of the standard Performance Max loop. Once you spot a high-performing placement, you can isolate that specific inventory to inform your Audience Ads strategy, perhaps by building dedicated remarketing campaigns for users who engaged with those specific sites. It feels like a surgical strike; you take the data provided by Microsoft and use it to carve out more predictable results that the broad automation might otherwise dilute. The key is to avoid over-correcting, as you still want the automated bidding logic to have enough room to find new opportunities. You are essentially feeding the algorithm better signals by hand-picking the winning inventory and doubling down on it through separate, more controlled channels.
Brand safety often relies on account-level URL exclusion lists to filter out poor-fit placements that don’t align with a company’s values. Beyond just looking at high spend without conversions, what secondary metrics should an advertiser analyze before permanently blocking a publisher, and how does this impact overall campaign liquidity?
While it is tempting to block any site that doesn’t immediately produce a sale, we must look at how a publisher aligns with the brand’s image and the overall intent of the user journey. You have to consider the context of the content and whether a high-spend, low-conversion site might still be contributing to the top-of-funnel awareness that eventually leads to a conversion elsewhere. Over-blocking can lead to a “choking” effect on campaign liquidity, making it harder for the machine to find the necessary volume of inventory to scale efficiently. It is a delicate balance of protecting the brand’s reputation while ensuring the algorithm has enough “room to breathe” and find potential customers in unexpected places. By using account-level exclusion lists strategically, we can prune the garden without killing the entire crop.
Reporting transparency is shifting from basic click data to deep financial outcomes at the placement level, giving marketers more leverage. How can teams use this granular data to justify advertising budgets to stakeholders, and what are the risks of over-optimizing based on short-term placement performance?
The ability to show stakeholders exactly where every dollar is going—and more importantly, exactly what it’s bringing back—radically changes the conversation in the boardroom. Instead of explaining “estimated” reach or “projected” clicks, we can now point to specific publisher URLs and show a direct line to revenue, which builds immense trust and helps secure higher budgets. However, the risk lies in knee-jerk reactions; cutting a placement because it had a bad forty-eight hours can destroy long-term momentum and lead to a fragmented strategy. We have to resist the urge to over-clean the campaign every day, as the real value often comes from letting the data accumulate enough weight over a week or a month to make a truly informed decision. It is about finding the sweet spot between being data-driven and being patient enough to let the automation find its rhythm.
What is your forecast for Microsoft Advertising?
I anticipate that Microsoft will continue to bridge the gap between full automation and manual control by releasing even more granular signals across their entire suite of tools. We are likely to see this level of transparency move beyond just URL reports and into more sophisticated audience and creative performance breakdowns within Performance Max. As advertisers become more comfortable with these insights, the platforms that provide the most transparency will win the biggest share of the budget because they empower the human expert. The future of Microsoft Advertising lies in this synergy, where the “black box” opens up just enough to allow human expertise to fine-tune the high-powered engine of machine learning.
