In today’s rapidly evolving performance marketing landscape, the debate between self-service execution and dedicated managed support has never been more important. We spoke with Nadim Batista-Kuttab of Xevio, one of the industry’s leading native advertising specialists, to discuss how artificial intelligence (AI) platforms are reshaping what’s possible.
Nadim’s team manages multiple large enterprise accounts, giving them a unique view on where self-service excels, where there are limitations, and why human expertise remains the ultimate competitive advantage. Today, Nadim shares why enterprise brands often struggle with DIY approaches, how agencies use Realize differently than internal teams, and how dedicated expertise consistently delivers stronger outcomes in terms of scale, speed, and long-term profitability.
The High-Budget Dilemma: Why Self-Service Fails Enterprise
Self-service platforms base their models around simplicity — put in a headline, upload a creative image, set a budget, and go from there. For small advertisers or those testing new channels with limited spend, this can be a more cost-effective entry point, but for enterprise-level customers, the limitations of a purely DIY approach quickly become unavoidable.
As Nadim sees it, there’s a disconnect with large advertisers consistently struggling, not because the tools are insufficient, but because the operational complexity of performance advertising makes it impossible to scale without a deep level of expertise.
“I think self-service has never worked for big advertisers,” Nadim explains. “Mainly because there are so many different pieces to a typical campaign that without some sort of internal support, you’re going to have a really hard time navigating policy issues, creating white lists or blacklists for sites, and understanding the trends of the platform, which are changing very quickly.”
This complexity becomes especially challenging for advertisers more familiar with walled garden sites like Meta, Amazon, or Google, where platforms are more automated and far narrower in format constraints. Those environments create a false sense of ease, and advertisers branching out onto the open web often underestimate the depth of manual optimization required for a successful campaign. This assumption can become costly, as contextual inventory, publisher environments, and rapid policy shifts all play into these overarching costs.
Even more importantly, the open web rewards experienced users who know how to leverage audience signals, publisher-level insights, and ongoing trend data. Without this understanding, brands risk misallocating budgets, misinterpreting early data, and assuming that short-term performance spikes represent long-term viability. Nadim notes that, for consistent results, having an account manager is the best option.
The Strategic Advantage of Team Dedication
The biggest differentiator between self-service advertisers and those working with an agency or dedicated in-house team comes down to focus. A strong performance organization doesn’t just know performance advertising, but lives it daily. This singularity in expertise can’t be replicated by brands splitting attention and staff resources across channels.
“We have 50 people here that do nothing but Taboola and the other native and performance channels on a daily basis,” Nadim says. “If you assign one or two people from internal teams to compete, it’ll be very difficult.”
This isn’t a commentary on the skills of your internal talent, but simply an acknowledgement that the sheer volume of learning required to manage and scale these campaigns is immense.
Creative Volume
Performance advertising relies heavily on creative iteration. A larger team naturally produces more testable assets, such as variations in imagery, hooks, or landing page experiences that expand the options for exploration and accelerate the journey to profitability.
With Realize, this scale becomes even more powerful as agencies can run structured creative experiments, feed the algorithm with richer signals, and capitalize on insights from multiple client accounts. A solo marketer, no matter how talented, will always be limited in their volume of experimentation.
Competitive Intelligence
Running dozens of accounts simultaneously generates pattern recognition that no individual brand can replicate. Agencies see emerging trends, publisher shifts, inventory changes, and seasonal behaviors before they ever appear in public documentation. Nadim describes this as a near-instant advantage: Because the team at Xevio is working with the data every day, they can make adjustments in real time.
Efficiency
Every advertiser on the open web eventually pays a “learning tax” through the costs of testing, failing, adapting, and scaling. Agencies, though, have already absorbed that cost across extensive historical datasets. They’ve seen thousands of examples of what works and what doesn’t, they know and understand the pitfalls, and they can interpret early performance data more accurately. All of this translates into less wasted spend. As Nadim puts it, this allows brands to essentially “skip steps” and reach performance goals faster, reducing both total cost of learning and time to profitability.
The Power of Proximity: Shaping the Platform’s Future
Perhaps the most overlooked advantage of a dedicated account partner is their access, not only to data but to the platform itself. Managed service teams and scaled agencies like Xevio operate with a direct line to Taboola’s internal teams, allowing them to resolve issues, request insights, and help shape the platform’s development roadmap.
“As a company, we have several direct lines to Taboola itself,” Nadim confirms. “We can suggest products directly to the product teams at Taboola, which essentially helps us shape the direction Taboola is taking toward what we need as one of the bigger spenders on the platform.”
Policy Resolution
Ad rejections and policy flags are inevitable on any performance platform, but on the open web, where publisher diversity is significantly higher, policy issues can decelerate momentum quickly. Agencies can bypass the standard queues and work directly with policy teams to resolve issues within minutes, rather than days. This keeps campaigns more stable, maintains learning continuity within the algorithm, and prevents disruptions to Realize’s optimization process.
Product Input
Because agencies represent some of the platform’s most advanced advertisers, their feedback influences product development. Whether it’s advocating for new targeting capabilities, refining bidding models, or providing suggested enhancements to Realize’s predictive intelligence, agencies play an active role in steering the evolution of advertising products. This is a significant advantage over self-service users working on the platform.
Early Access
Agencies and managed account partners frequently receive early access to beta products, audience models, ad formats, or new inventory sources. These advantages can translate into meaningful campaign gains, particularly during competitive cycles or peak seasonal periods. For enterprise brands, this early access can make the difference between scaling profitability and falling behind competitors who leverage new tools faster.
AI as an Accelerator: Blending Generative Tools with Human Expertise
AI has already transformed nearly every aspect of performance marketing, from creative ideation to landing page production and data analysis. But Nadim is clear that while AI benefits marketers with its ability to improve workflows, it does not replace the strategic, human-driven thinking required to interpret data, understand user psychology, and build comprehensive value streams. “Our recommendation right now, especially on the content side, is to use AI as an accelerator, not as a replacement,” he says.
Creative Generation
Generative image models and automated thumbnails significantly reduce the need for extensive design resources, as with a few prompts, advertisers can generate dozens of variations ready for testing on Realize. This democratization of the creative process opens new possibilities for scaling. However, AI will never replace the strategic thinking behind what should be tested. The best results come from when humans are guiding the design, ensuring that headlines, visuals, and concepts align with the brand goals.
The Content Fallacy
AI can produce content quickly, but what it produces should always be considered the draft, not the finished piece. “Just because an AI tool can write you a landing page in 10 seconds does not mean that landing page will perform remotely as well as a page that has a couple of hours of several people’s time put into it, to really fine-tune those edges and make it perform better,” Nadim says. Human teams are still essential for tweaking nuance, providing emotional resonance and brand cohesion, and understanding conversion psychology.
The Full Value Stream
The performance of advertising campaigns is never determined by a single asset: Success requires synchronicity across the entire chain from click to content, to product and purchase. AI can assist with ideation and drafting, but aligning all components in the advertising puzzle still requires human expertise. As Nadim puts it: “The hard part is really just getting the entire value stream right.” This is precisely where dedicated teams outperform individuals, regardless of the tools available.
Key Takeaways
In complex performance environments like the open web, success is defined by the ability to use tools like Realize with expertise, precision, and understanding of how these tools function to make the best strategic recommendations. While self-service platforms create low-friction pathways for advertisers getting started, they’re not built for enterprise-level budgets or more complicated revenue models. The risk of going it alone increases with spend, as policy errors become costlier, creative limitations become more restrictive, and the inability to test, interpret, and adjust quickly can drain budgets long before campaigns reach their full potential.
The human edge remains the ultimate differentiator for enterprise brands. Dedicated account managers, specialized agencies, and deeply experienced advertising teams bring a level of strategic focus that’s difficult for internal teams to match. They offer creative volume, real-time competitive insights, and the ability to navigate performance fluctuations with confidence in little time. This means that the learning curve is typically shortened, protecting budgets from inefficiencies, and always optimizing towards a stronger return on investment (ROI).
For advertisers looking to unlock the potential of the open web, attempting to scale with large budgets through self-service alone is no longer the answer. Instead, tools like Realize reward strategic testing and high-quality data inputs thanks to engaged experts who have a deep understanding of the platform.
