In digital advertising, reaching the right consumer is no longer just about scale—it’s about precision, privacy, and performance. For years, the industry has debated two dominant approaches: contextual targeting, which aligns ads with the content being consumed, and behavioural targeting, which relies on signals from users’ past actions and interests.
Yet with tightening privacy regulations, the phasing out of third-party cookies, and shifting consumer expectations, marketers today face a new question: which approach delivers better ROI in a privacy-first era?
To explore this, MARKETECH APAC spoke with industry experts Germaine Hendrik, head of marketing APAC at Quantcast, and Rishi Bedi, managing director APAC at Ogury, who shared their insights on how advertisers can navigate this evolving landscape.
Defining the line: content vs. consumer
At its simplest, Germaine explains, the difference comes down to what you target versus who you target.
“At its core, contextual targeting focuses on the relevance of the page or content being consumed at that moment. Behavioural targeting, on the other hand, looks to other insights or signals, such as a user’s past interactions, interests, and intent. Basically, contextual targets what’s on the page. Behavioural targets are those who are viewing it,” she said.
For Rishi, the distinction also reflects the industry’s ongoing tug-of-war between relevance and privacy.
“Behavioural targeting depends on tracking individuals over time by collecting data on actions, preferences, and habits to deliver personalised ads. Contextual targeting, in contrast, serves ads based on the content being consumed, aligning messaging with page topics rather than user behaviour,” he explained.
He adds that Ogury’s approach, which they call “personified advertising”, looks to bridge both worlds—using anonymised audience insights and contextual signals to reach personas, not individuals, in privacy-safe environments.
Where each approach excels
Both leaders agree that effectiveness often depends on the campaign objective and vertical.
Germaine noted that behavioural targeting shines for performance-driven industries like financial services, e-commerce, travel, and subscription-based services, where past intent data can drive conversions at the right moment. Contextual, on the other hand, is stronger in brand-building campaigns for sectors like FMCG, lifestyle, and entertainment, or in markets where behavioural data is limited.
Rishi echoed this but pointed out that contextual becomes especially valuable in privacy-sensitive industries such as pharma, finance, or tech. “As privacy becomes non-negotiable, the real opportunity lies in evolving beyond this binary. Personified advertising represents that next step in delivering relevance through anonymised audience intelligence and contextual signals, not personal data,” he said.
Still, Germaine emphasised that in today’s advertising ecosystem—shaped by privacy regulation, browser changes, and shifting consumer expectations—the most effective strategies will blend both approaches: using contextual targeting as a privacy-resilient foundation, with behaviour-based insights layered on for predictive accuracy.
Measuring ROI: brand lift vs conversions
The two approaches also diverge when it comes to measurement.
“For behavioural campaigns, I normally look at Cost Per Acquisition (CPA), Return on Ad Spend (ROAS), or lifetime value,” said Germaine. “For contextual campaigns, success often leans toward brand metrics—such as uplift in awareness, ad recall, or brand favourability, alongside other engagement metrics.”
She added that within Quantcast, they use the Quantcast Platform internally to test both tactics and refine strategies for their own marketing goals. “With AI, we can now link contextual exposure directly to conversions—closing the gap between awareness and action.”
Rishi noted a similar distinction: “Behavioural campaigns often focus on lower-funnel KPIs such as clicks, conversions, or CPA. In contextual campaigns, success means reaching the right consumer, at the right time, on the right channel, in the right environment, without relying on personal data.”
He explained that at Ogury, they take this a step further by leveraging zero-party data gathered through always-on, un-incentivised surveys. These insights provide direct understanding of user preferences, purchase intent, demographics, and more—allowing them to build consented audience profiles and deliver precise, scalable targeting while keeping privacy at the core.
Ultimately, both leaders agree the industry is shifting toward outcome-based measurement—moving away from identity-based tracking and toward assessing whether campaigns truly deliver meaningful business impact.
The AI effect: closing the gap
AI and machine learning have emerged as critical tools in improving contextual relevance and performance.
According to Germaine, AI has “transformed contextual targeting from basic keyword matching to understanding the full meaning of content and how people interact with it, using real-time data to hone in on achieving results.”
Quantcast’s own Ara® AI, she added, processes billions of browsing events to link content with conversion likelihood—helping advertisers deliver relevant ads without personal identifiers.
Rishi also highlighted AI’s role in contextual intelligence: “Today, AI can analyse the full semantic meaning of a page, detect sentiment, and assess brand safety in real time, ensuring ads appear in the most contextually relevant and respectful environments.”
He explained that by combining this with anonymised audience insights, contextual campaigns can now rival—and in many cases surpass—the precision once exclusive to cookie-based strategies.
Balancing privacy with performance
For both leaders, the path forward is not about choosing one strategy over the other but about combining them in ways that are privacy-compliant and performance-driven.
Germaine advised marketers to “treat privacy not as a limitation but as an innovation driver. The most future-ready strategies combine privacy-compliant behavioural insights with sophisticated contextual signals to ensure relevance without compromising trust.”
Rishi agreed, emphasising the need to diversify data inputs. “A more effective approach is to combine first-party data with zero-party insights to create richer audience understanding while respecting privacy. This allows marketers to deliver more precise, scalable, and privacy-conscious campaigns that connect with the right people at the right moments,” he said.
Building on this, Germaine also encouraged marketers to invest in AI-powered solutions that can work effectively with first-party data and real-time signals. And most importantly, she stressed the need to adopt a test-and-learn mindset:
“Test, learn, and stay agile—the winners will adapt as fast as the landscape changes.”
Context + behaviour = future resilience
As the advertising landscape shifts beyond cookies and IDs, one thing is clear: ROI today comes not from leaning on one tactic but from integrating contextual intelligence with privacy-safe audience insights.
Contextual targeting delivers trust and compliance; behavioural data brings predictive accuracy. Together—with AI as the bridge—they allow marketers to maintain reach, relevance, and measurable impact without compromising consumer privacy.
In a market where both regulation and consumer expectations evolve daily, the most resilient strategies will be those that blend context and behaviour to strike the right balance between performance and trust.
