Hello, Niki. Let’s start with your journey—can you share a bit about your background and now as CEO at TeqBlaze?
Hello, and thank you for having me! My journey in AdTech began over seven years ago when I started as a project manager at SmartyAds. Unlike many leaders who enter this industry through business development, I came from working closely with tech teams. This gave me a strong foundation in understanding both the technical and business aspects of AdTech.
Over time, I led the transformation of what were initially smaller, independent products – like separate white-label SSP and DSP teams – into a unified business unit. In February 2024, under my leadership, the Enterprise Solutions unit evolved into an independent company, TeqBlaze, and I stepped into the role of CEO.
2024 was a year of real growth for our team. We tackled challenges that pushed us to rethink and enhance our white-label solutions, and it was exciting to see those efforts truly pay off.
In a rapidly changing market, how do you ensure your product roadmap always evolves with technological advancements and is flexible enough to adapt to the challenges in the ad tech ecosystem, especially given the pace of innovations?
In my experience, Staying ahead in ad tech isn’t just about reacting to trends; it’s about being part of the conversation shaping them. Our team’s deep involvement in communities like IAB Tech Lab and Prebid gives us early access to industry developments and, more importantly, a chance to influence them. This proactive approach keeps our roadmap aligned with the future, not just the present.
Equally important is our connection with clients in industries such as DOOH, retail, telecom, and game development. Their insights into their markets help us build technologies that address real-world needs, not just theoretical ones.
Finally, our R&D team constantly researches new directions and emerging use cases.
We keep our roadmap flexible and relevant in an ever-changing ecosystem by staying closely connected to industry trends, listening to clients, and continually exploring new directions.
How can ad tech companies effectively integrate real-time client feedback and market analytics into their product roadmaps?
Integrating real-time client feedback into a product roadmap works best when it’s treated as a continuous, collaborative process. In our case, we collect feedback on two levels: smaller, weekly updates through account managers and more comprehensive input during structured reviews every six months. This approach allows us to address immediate issues while also spotting long-term patterns that shape our development priorities.
What’s crucial is how we handle that feedback. It’s not just a checklist—we involve multiple departments to dig into the details. For example, the service team might use it to improve communication or scale processes, while the technical team might adapt their testing frameworks or refine how features are validated. By connecting the dots between feedback and actions across teams, we make sure no insights are lost and every improvement is meaningful.
The key, I think, is ensuring feedback isn’t just heard but actively shapes how we evolve, from day-to-day operations to strategic decisions.
What role do personalized training and support materials play in improving the adoption of your platform among clients with varying technical expertise?
Training and support materials are essential for ensuring clients can confidently use our platform, no matter their background. In our experience, onboarding needs to be tailored to each client’s level of expertise, and we’ve built two clear paths to handle this.
For clients new to ad tech, we start with the fundamentals—terminology, basic programmatic concepts, and open RTB protocols. Once they grasp these well, we move on to the platform itself, explaining its structure and guiding them through its features step by step.
For clients with experience, we skip the introductory phase and dive straight into how the platform works. The focus here is on using its features to their fullest potential and improving performance through optimization.
This approach ensures that every client gets the guidance they need without feeling lost or overwhelmed, regardless of their starting point. It’s not about overloading them with information but helping them quickly find their footing and see results.
What is the most significant challenge ad tech platforms face regarding client education, and how do you overcome it?
One of the biggest challenges in ad tech is educating clients from industries like retail or DOOH, where standard RTB protocols aren’t widely used. These sectors have their own terminology and systems, which need to be carefully mapped to programmatic concepts to make the connection clear.
This mapping process involves aligning their workflows with how programmatic operates while showing them how the two can work together. It’s not just about teaching the technology but about making it relevant to their specific needs and context.
Efforts like the IAB Tech Lab’s work on RTB protocols for retail are a big step forward, but until these standards are fully adopted, education has to be flexible and tailored to help clients navigate this new space effectively.
How do ad tech platforms achieve a balance between maintaining scalable, high-performance systems and offering deep customization for clients?
Balancing scalability and customization in ad tech is never straightforward, but the most practical solution we’ve found is to keep each client’s platform entirely separate. For us, that means deploying every client on their own infrastructure, with dedicated servers. This ensures no technical overlap between clients and allows us to tailor the platform to their specific needs.
The truth is, optimization has to be individual. Each client approaches things like QPS limits, pricing strategies, and the number of supply and demand sources differently. By isolating their systems, we can focus on adjustments that fit their unique setup, rather than forcing a one-size-fits-all approach.
It’s not without its challenges, but this method gives us the flexibility to prioritize both performance and customization without compromising on either.
When dealing with large-scale bid requests, what are the most effective strategies for optimizing data load handling in ad tech platforms?
Managing large-scale bid requests is challenging because incoming traffic isn’t something we can fully control—it comes from external systems. That’s why we always emphasize the importance of communication with supply partners. Clients need to work with their suppliers to ensure the traffic they’re receiving is relevant and filtered, rather than allowing everything to flow through unchecked.
At the same time, relying solely on agreements isn’t enough. Within our platform, we’ve developed robust filtering logic to handle incoming traffic efficiently. These filters help prioritize relevant requests while reducing unnecessary load. Additionally, traffic shapping algorithms and tools ensure the system adapts dynamically to changes in volume, maintaining stability even under heavy demand.
How can AI-driven contextual targeting maintain the delicate balance between user privacy and advertising precision, especially in light of evolving privacy regulations like GDPR and CCPA?
I think the key to AI-driven contextual targeting is that it doesn’t need personal data to work effectively. Instead, it analyzes the content the user is engaging with in real-time. This means we can deliver highly relevant ads without ever touching sensitive information.
In my view, the balance comes from how AI adapts. It keeps ads precise by focusing on context—what’s happening in the moment—while respecting the strict boundaries set by regulations like GDPR and CCPA. For me, this approach isn’t just about compliance; it’s about proving that great advertising doesn’t have to compromise privacy.
With the phase-out of third-party cookies, what role do you see for AI in enabling DSPs to enhance ad relevancy, and how can they leverage this technology to increase campaign ROI?
With the phase-out of third-party cookies, AI steps in as a critical tool for DSPs to maintain and even enhance ad relevancy. Instead of relying on user-level tracking, AI can analyze and synthesize real-time signals—contextual relevance, device patterns, location trends, and historical performance—to identify the best placement opportunities.
The real strength of AI here is its predictive capability. By using advanced models to anticipate user intent and campaign outcomes, DSPs can dynamically adjust bidding strategies and optimize creatives on the fly. This means ad decisions are driven by actionable insights, not static data. In my view, AI isn’t just a workaround for the loss of cookies; it’s a way to elevate targeting precision while driving measurable ROI improvements in a privacy-compliant framework.
What advice would you give to companies just starting in this space, especially in terms of building a strong foundation for innovation while staying adaptable to market shifts and regulatory changes?
Honestly, I’d say think twice before jumping into AdTech right now. It’s an incredibly dense and competitive market. New companies in this space are rare for a reason—it’s tough to stand out unless you have a truly validated, fresh, and innovative idea.
If you’re considering it, make sure your concept isn’t just a slight tweak of what’s already out there. In my experience, what works are groundbreaking ad formats or something that genuinely disrupts and grabs attention. The reality is, almost everything is already being offered by hundreds of companies in every possible variation. So, unless you’re confident you’ve got that next big thing, it’s worth rethinking the approach or pivoting to a niche that’s still underserved.
Advice from the author : Before jumping into AdTech, ask yourself: Is your idea a game-changer, or just another version of what’s already out there?
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Anastasia-Nikita Bansal, CEO at TeqBlaze
Niki has over 7 years of experience in AdTech. She started at SmartyAds, managing SSP WLS projects, and soon led White Label solutions and SmartHub. In 2024, she transformed these solutions into TeqBlaze, an independent company, where she now serves as CEO. Niki is dedicated to developing advanced programmatic tools that solve real-world challenges for clients across industries. TeqBlaze specializes in creating customizable white-label programmatic platforms, including DSP, SSP, and Ad Exchange solutions, empowering businesses to launch and scale independent ad tech ecosystems. LinkedIn.