Scaling media spend is often portrayed as a simple matter of increasing budgets once a campaign demonstrates early promise. In reality, meaningful scaling that takes a brand from modest acquisitions to sustainable, high-volume profitability requires a more structured approach that can interpret market signals and have a clear sense of when to increase and when to hold steady.
A disciplined understanding of how performance shifts as budget grows, rooted in data, is essential. We’ve turned to Nadim Batista-Kuttab of Xevio, a performance marketer known for managing some of the highest-spend native advertising programs online, to break down the essentials of budget allocation and scaling across a complex platform, and provide expert insights into how to maximize profitability and avoid wasted spend.
The Mandatory Minimum: Why Your Campaign Needs a Budget Floor
One of the most frequent mistakes advertisers make when entering the native performance space is starting too conservatively. A campaign launched without sufficient budget does not just underperform, it fails to generate the data density that machine learning (ML) systems require in order to optimize most effectively.
Nadim emphasizes that most campaigns, whether focused on lead generation or e-commerce, need at least $300 per day to exit the learning phase of ML and create a stable environment for campaign optimization. This number applies across verticals, placements, and geo locations. A mobile-only iOS campaign needs the same minimum as a large-scale lead gen initiative, because the platform must be able to observe enough impressions, clicks, and conversions to understand signal patterns and target high-intent users.
Campaigns launched below this threshold rarely reach their potential because the algorithm doesn’t receive enough information to distinguish meaningful behavior from noise. At $50 to $100 per day, artificial intelligence (AI) systems often end up competing for low-quality inventory or delivering to inconsistent placement groups. The result is an uneven cost-per-acquisition (CPA) trajectory and a misleading impression of poor channel fit. Nadim stresses that advertisers often evaluate the wrong variable when judging campaign viability: The issue isn’t usually creative or the vertical, but rather the lack of budget required to gather high-quality performance signals.
For performance advertising, especially with the Realize engine powering bidding decisions, this minimum matters even more. Realize evaluates impressions based on predicted engagement, contextual alignment, user behavior patterns, and post-click conversion likelihood. These predictions depend on rapid and reliable feedback loops. When spend is too low, Realize can’t build an accurate performance model, and the campaign risks becoming trapped in a low-quality auction environment. Setting a budget floor ensures that learning accelerates instead of stalling, allowing the campaign to reach a viable optimization state more quickly.
The Scale-Up Indicator: Accelerate Based on CPA, Not Hype
Scaling should never be driven by guesswork, excitement, or pressure to meet quarterly spending goals. Nadim explains that the only reliable indicator that a campaign is ready for increased spend is performance relative to your target CPA. When a campaign begins to approach, or consistently hits that target, it signals that the algorithm understands where to find high-quality users and can replicate that success at a larger budget.
This is why campaign spending around $500 per day and achieving strong performance can often scale to $5,000 per day with minimal disruption. The system already knows what user patterns correlate with conversion and which placements produce the most stable results. Increasing spending is not giving the model a new job, but simply allowing it to execute the same logic at a larger scale. Nadim points out that this phenomenon is especially true on Run of Network, where a campaign is distributed across a network of websites, or the public marketplaces of broad exchange inventory. When a campaign has access to a wider publisher set, the algorithm has enough diversity to expand without running into immediate auction constraints.
Not all situations support fast scale, though. Hyper-targeted campaigns tend to saturate early because they restrict the algorithm’s ability to maneuver. If you’re targeting a very small list of publishers, a single demographic, or a limited geography, increasing spending too quickly forces bids upwards and fragments performance. In these situations, Nadim advises that it’s best to work with your Realize account manager before scaling too aggressively. The team can estimate how much inventory a campaign is capable of absorbing based on current cost-per-clicks (CPCs), click-through rates (CTR), and click-to-message (CTM) levels, along with broader market behavior.
Scaling based on CPA stability keeps the whole process more disciplined. It prevents advertisers from interpreting short-term wins as long-term capability and ensures that scale only happens when the data demonstrates readiness.
The Saturation Plateau: Recognizing Diminishing Returns
No matter how strong a campaign is, every market eventually reaches a point where adding more budget no longer produces proportional returns. Nadim refers to this moment as the saturation plateau. Understanding when this occurs is essential for long-term profitability. The plateau appears when the campaign absorbs most of the available high-quality inventory and cannot expand further without pushing into less efficient placements. When this happens, each incremental dollar begins to produce fewer conversions and CPA may begin to rise.
This plateau is not a sign of campaign failure, though: It’s a natural state of growth in markets with finite impression pools. In the United States, which has one of the largest and most diverse publisher ecosystems in the world, Nadim notes that saturation often occurs somewhere between $20,000 and $30,000 per day. Larger European markets like Germany show similar behavior, but smaller markets like Spain or France may see saturation earlier, sometimes around $5,000 to $10,000 per day, simply because the available audience size does not support deeper scale.
Once the plateau becomes visible, the best response is to stabilize rather than push harder. Reducing budget slightly can help restore equilibrium, allowing the campaign to settle into its Maximum Efficient Daily Spend (MEDS), which is the highest spend level at which CPA stability and conversion volume remains optimal. After stabilizing, advertisers can focus instead on creative rotation, funnel refinement, and post-click optimization. These improvements can unlock additional scaling opportunities, since small boosts in CTR or conversion rate often result in disproportionately large performance gains at higher spend levels.
Experienced media buyers understand that scale is not linear: It accelerates early, slows as markets absorb budget, and eventually reaches a sustainable plateau. Recognizing this pattern prevents wasted spend and supports long-term growth.
Bidding for Growth: Max Conversions vs. Target CPA
The bidding strategy you use must align with the phase that your performance marketing campaign is currently in. Whether you’re scaling or stabilizing, advertisers must understand what the campaign’s current goal is, to best align placements and strategy with this overall outcome.
Max Conversion (Scaling Phase)
In the early and mid stages of scaling, advertisers need the algorithm to explore more aggressively, test new placements, and uncover patterns that lead to more efficient conversions. Nadim explains that max conversion bidding is the strategy best suited for this phase, because it gives the system freedom to discover opportunity pockets without artificially limiting CPA. With max conversions as the goal, Realize can assess impression value dynamically, allocating spend to the placements that demonstrate the highest likelihood of producing conversions at scale.
This flexibility is crucial during growth. You should opt for a performance advertising platform which supports vast open-web inventory, and max conversions ensure that the model can rapidly evaluate which contexts and user behaviors correlate with conversion intent. Nadim notes that Realize has become sophisticated enough to eliminate the need for manual bid adjustments across individual sites, replacing thousands of micro-decisions with real-time intelligence. During scale, max conversions accelerate learning and ensure that campaigns build a strong performance foundation before any strict cost controls are introduced.
Target CPA (Stabilization Phase)
Once a campaign reaches its saturation plateau and the MEDS becomes clear, the priority should shift from exploration to consistency. At this stage, target CPA becomes the preferred strategy because it reinforces predictable performance. Target CPA tells the algorithm to maintain the CPA stability, even if it means restricting further exploration. Because the system already understands where conversions are coming from, this constraint helps lock in profitability and ensures the campaign operates efficiently at higher volumes.
For many advertisers, switching to target CPA too early is a common mistake. Nadim stresses that target CPA should only be activated once the campaign has already reached stable performance at higher spend levels. When applied prematurely, target CPA limits the system before it fully understands the advertising environment, slowing learning and causing the campaign to stagnate.
The Only Manual Rule: The “Parachute” Safety Net
Although Realize eliminates the need for most manual intervention, Nadim supports using one specific rule: the “parachute” safety net. This rule caps spend when CPA rises dramatically above your normal range. It isn’t meant for optimization, but rather prevents runaway spending during unexpected issues, such as broken tracking, malfunctioning lead forms, or landing page outages.
If CPA suddenly triples after a certain spend threshold, the parachute rule pauses the campaign until you can diagnose the issue. It’s the only manual safeguard that Nadim consistently recommends because it catches operational failures, rather than actively influencing your optimization strategy.
Key Takeaways
Scaling native advertising is not a matter of intuition or aggressive budget. Instead, it’s a measured, data-driven progression that unfolds in defined stages. Nadim’s approach makes it clear that campaigns must begin with sufficient budget to accelerate learning, scaling only when CPA performance proves that the model is ready and can stabilize once the saturation plateau is reached.
Growth is fastest when the algorithm has room to explore and is the most sustainable when it transitions to disciplined controls at the right moment. Max conversions drive intelligent expansion, while target CPA secures long-term stability, with the parachute safety net ensuring operational reliability when unexpected issues arise.
Ultimately, scaling is both a science and a partnership. Even the most experienced advertisers will encounter differences in scale potential across markets, verticals, and inventory conditions. Because those dynamics vary significantly by geography, the most effective step is to consult your Taboola account manager when you’re thinking about scaling budget, testing a new country, or evaluating a campaign’s ceiling. They can help interpret the true scale potential of any market, provide predictive insight into inventory depth, and guide you toward the most profitable path forward as your campaigns grow.
