Anastasia Braitsik brings a wealth of knowledge in data analytics and digital strategy to our discussion today, specifically regarding the seismic shifts in the Google Ads ecosystem. As Google pivots away from impression-based planning, her expertise is vital for brands trying to navigate a landscape that increasingly prioritizes immediate performance over traditional brand visibility. We are exploring the practical implications of Performance Planner’s recent updates and how media buyers can maintain a holistic strategy in an automation-heavy world.
Performance Planner recently stopped supporting Display and Video campaigns along with impression share metrics. How does this change your workflow for upper-funnel strategy, and what specific steps should teams take to forecast awareness budgets now that these native tools are restricted?
The removal of Display and Video support from Performance Planner, which took effect just last month, forces a significant pivot in how we approach the top of the funnel. Previously, we could lean on native forecasting to visualize how a budget increase might impact our reach, but now we must rely on historical data and manual modeling to fill that void. My team is now spending more time in the Reach Planner and combining those insights with performance data from Demand Gen and Search campaigns to estimate visibility. It’s a bit of a sensory shock for planners who are used to having all their projections in one clean interface, as they now have to stitch together a narrative using disparate data points. To bridge the gap, teams should prioritize building custom forecasting spreadsheets that account for the seasonality of Display and Video, ensuring that awareness doesn’t become an afterthought simply because it’s harder to track.
Google is prioritizing conversion-driven campaign types like Search and Performance Max over impression-based planning. What are the practical trade-offs when using performance-centric tools for brand-heavy objectives, and how are you measuring success without absolute top impression share data?
The most immediate trade-off is the loss of granular control over where a brand appears, as tools like Performance Max and Search are designed to hunt for conversions regardless of the aesthetic or atmospheric context of the placement. When you lose access to metrics like absolute top impression share within the planner, you lose the primary pulse check on brand dominance and “mental availability” in the market. We are pivoting our success metrics toward “branded search lift” and conversion volume specifically from Demand Gen, which still retains some native support. It feels like navigating a ship without a compass when you can no longer view or edit existing plans that relied on those top-of-page metrics. We have to become more comfortable with “blended” success, where we look at how these performance-driven campaigns influence the total ecosystem rather than just looking for a specific percentage of the top spot.
Advertisers can no longer access or edit existing plans that rely on impression-based metrics or video content. What alternative forecasting methods do you recommend for maintaining continuity, and how can teams bridge the gap between automated performance data and manual brand planning?
It is a frustrating reality that any existing plans incorporating Display, Video, or impression share metrics are now effectively locked away and inaccessible. To maintain continuity, I recommend that teams immediately audit their past performance reports from the last twelve months to establish their own internal benchmarks for impression-to-conversion ratios. We are currently utilizing a hybrid approach where we use the Performance Planner for supported types like Shopping, App, and Local campaigns, while manually layering on awareness projections based on those historical averages. There is a certain weight to this manual work, but it prevents the “black box” of automation from completely swallowing the strategic intent of a brand. Bridging this gap requires a disciplined documentation process so that the tribal knowledge of how Video fuels the bottom funnel isn’t lost in the shift toward pure performance tools.
This shift toward automation and Demand Gen suggests a heavier focus on bottom-funnel outcomes. How can advertisers prevent their awareness strategies from being sidelined, and what specific metrics should they present to stakeholders to justify budget for non-conversion-driven channels?
To prevent awareness from being sidelined, we have to change the language we use with stakeholders, moving away from “impressions” and toward “demand signals.” When presenting to a board, I no longer just talk about how many people saw an ad; I talk about the correlation between Display spend and the decrease in Customer Acquisition Cost (CAC) for our Search and Performance Max campaigns. Even though Google is doubling down on conversion outcomes, we must demonstrate that Demand Gen and Video act as the fuel for those high-performing engines. I suggest presenting a “Halo Effect” report that shows how volume in non-conversion channels directly precedes spikes in Shopping and Local campaign actions. If we don’t fight to keep these channels funded, the performance-driven well will eventually run dry as we stop reaching new audiences who aren’t yet ready to click “buy.”
What is your forecast for the future of Google Ads planning tools?
I believe we are entering an era where the concept of “manual planning” within Google’s native environment will almost entirely disappear in favor of predictive, AI-driven suggestions. We will likely see a full integration where the tool doesn’t ask us for a budget, but rather asks for a target outcome and then distributes funds across Search, Shopping, and Demand Gen automatically. This means that the role of the media planner will shift from a “calculator” to a “curator,” where our value lies in feeding the machine the right creative assets and business objectives. We should expect to see even more metrics related to “user intent” and “predicted value” replace traditional visibility stats like impression share. It’s a future that is incredibly efficient for conversion-focused brands, but one that requires us to be much more intentional about protecting the long-term health of brand equity.
