Nội dung
- Targeting is becoming less about “narrowing down,” and creative is taking over that job
- Why creative must be clearer when AI expands reach
- Creative does not just persuade; it also helps the algorithm learn correctly
- A higher education example: speaking to the right people works better
- What this means for the Vietnamese market
- References
On major ad platforms like Google Ads, Meta, and TikTok, targeting is shifting toward broader reach and greater AI orchestration. That means ad creative is no longer just there to grab attention; it is increasingly acting as a signal that helps systems understand who is most likely to see the message.
For Vietnamese marketers, this shift is especially noteworthy because it directly affects lead quality, conversion costs, and how messages are built as platforms gradually reduce advertisers’ manual control.
Targeting is becoming less about “narrowing down,” and creative is taking over that job
According to MarTech, systems such as Google’s Performance Max, Meta’s Advantage+, and TikTok’s audience expansion mechanisms are giving algorithms more power to find the users most likely to convert. Advertisers therefore have less precise control over “who sees the ad” and instead provide broader inputs, stronger conversion signals, and better creative content.
The notable point is that creative is no longer in a supporting role. Every headline, image, video, or call to action can help the platform infer: who this ad is for, what stage they are at, and how it should respond.
In other words, as audience targeting expands, creative becomes a new layer of “audience confirmation.” This is a fundamental shift in how effective digital advertising is executed.
Why creative must be clearer when AI expands reach
In the old model, many marketers assumed audience settings would filter out unsuitable users, so ad content could remain fairly generic. But when platforms prioritize broader distribution so machine learning has more room to optimize, vague messaging can easily attract low-quality engagement as well.
The usual result is less suitable leads, higher cost per qualified lead, noisier conversion data, and algorithms that struggle to learn the right signals. That is why creative must clarify two things at once: who this product or service is for, and just as importantly, who it is not for.
This is the core point MarTech emphasizes: the goal is not just to get more clicks or views, but to create self-selection. The right people will stop and pay attention; the wrong people will move on. Both help the campaign perform better.
Creative does not just persuade; it also helps the algorithm learn correctly
When creative clearly conveys context, users tend to self-identify whether they belong to the target group. This benefits both sides. Behaviorally, people with real demand are more likely to pay attention and engage strongly. Technically, the platform receives cleaner signals to keep optimizing.
This is especially important in performance campaigns, where marketers often care more about quality than surface metrics. A message that is sharp enough can reduce irrelevant engagement, thereby supporting more sustainable optimization.
As a result, creative is shifting from the role of “bait” to the role of a “smart filter.” That is why marketing teams need to rethink their messaging, visual design, and CTA choices through the lens of qualification, not just persuasion.
A higher education example: speaking to the right people works better
MarTech gives an example from higher education, where marketers are used to multiple layers of filtering such as age, education interests, academic status, or remarketing lists. But as platforms move toward broader targeting, relying only on audience settings is no longer enough to ensure application quality.
Suppose a university is promoting an online master’s program in data analytics. It does not need everyone interested in data analytics; it needs the right group: people with a bachelor’s degree, work experience, and a desire to advance or change careers.
Instead of relying solely on audience settings, the message can be written to clearly identify the target audience. A generic headline like “Advance Your Career with a Data Analytics Degree” may attract many different types of people. By contrast, a headline that emphasizes “for those who already have a bachelor’s degree and are ready to step into leadership roles” will automatically filter out less suitable users and increase the likelihood of conversion from the target group.
The clearer the message, the cleaner the signal, and the easier it is for machine learning to optimize for the right people.
What this means for the Vietnamese market
For Vietnamese businesses, the lesson is not to chase every new AI feature, but to rebuild how creative is approached in the era of broad targeting. As platforms increasingly prioritize automation, marketers need to see ad content as part of the customer classification strategy from the start.
This is especially relevant for industries where lead quality determines business performance, such as education, finance, real estate, healthcare, and B2B services. Instead of writing overly broad messages, businesses should make fit conditions, usage context, and expected outcomes clear in the headline, visual, and CTA.
In short: when AI broadens reach, creative must narrow the message. That is how you maintain scale without sacrificing conversion quality.
Source: MarTech, “AI is making creative the new targeting” (30/06/2026).
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This article focuses on AI in advertising with a perspective for the Vietnamese market.
