Data Meets Creativity: A New Approach to Content Creation
How successful campaigns bring creative, media, and data together perfectly.

“The creatives weren’t good!” is the phrase you’re most likely to hear shouted after your advertising campaign just tanked. Either that, or “the media plan really sucked…”
Unfortunately, these subjective and notoriously unfruitful debates usually turn into a finger-pointing duel between creative, media, and occasionally legal for those 3 paragraphs that ate up half your assets.
But, the point is this: behind any successful advertising campaign are two forces coming together in perfect harmony—creative and media. And if either of these fall short, so does your campaign. Now, as much as ever, there is a need to break down creative and media siloes for more streamlined advertising experiences.
This comes at a time when brands are asking for more from their agency partners, and a surge in ‘integrated pitches’ which predicate on the demand for simplification: driving efficiency as well as effectiveness by bringing content, media, data and production together in a seamless funnel, with technology holding it all together.
It’s the golden age for data-led creatives.
AI and the new creative data set
AI isn’t just a means to break siloes or drive efficiency, it also has its own unique role.
One of the main advantages of LLMs (Large Language Models) is their unique ability to process and understand unfathomable amounts of data. This, in tandem with an unrivalled capacity to automate mundane manual tasks, is how marketers are transforming campaign quality and output.
Infusing campaigns with data-driven insights, powered by AI, makes a strong foundation for upstream content ideation. This is why many creative teams now use platforms—such as SmartAssets’ creative analytics—to gauge which creative elements from advertising campaigns are most impactful, and then bake this knowledge into conceptualisation.
Creative analytics can now be fed with data from granular asset tags and myriad performance data that would otherwise be unmanageable by human-led teams. By assimilating these large data sets, creative effectiveness platforms are now able to: pinpoint the sweet spot for effective content, help teams to craft data-backed AI prompts, or even QA whether scaled assets are media-ready.
Moreover, media teams can also leverage insights to ensure platform adherence, regulatory compliance, brand guidelines, or any other rule-based parameters defined by brands or agency-side teams are applied.
Creative optimisation even offers prescriptive recommendations that outline which edits would help achieve higher ROAS (return on ad spend).
The 101 to AI data-driven insights
Advertising has always been about striking a balance between creativity and media. But, whereas media has been relatively data-led, creativity has largely been guided by intuition, experience and taste-making.
The advent of new technologies has, however, shaken things up, given that more and more brands are bringing creative data sets into the fold. And they’re right to. Enabled by AI, the unique splicing of creative and media data is one of the most powerful modern tools in the advertising arsenal, allowing marketers to make more outcome-focussed and better informed decisions in myriad ways:
1) Audience intelligence
Ineffective targeting can be a serial drainer of media spend, and AI analytics have been paramount to tackling this by effectively matching creative attributes to a relevant audience. Looking past the standard platform algorithms such as user interests, AI creates more nuanced profiles using first-party data to inform brands on what their consumer segments prefer in terms of: emotional resonance, product balance, scenery, humanisation, colours, etc.
Leveraging these insights for the creation of downstream assets yields big savings for production teams—effectively refining and reducing the number of quality assets that are needed.
2) Predictive recommendations
In the same vein as audience intelligence, predictive recommendations are an effective way to optimise assets preflight. This means leveraging a broad scope of creative scoring—platform, brand and best practices—to enhance campaign performance, and make sure that your ads are hitting the mark.
Using historical data from previous assets, SmartAssets’ creative analytics tool measures the impact of granular creative elements and uses these to inform their impact on campaign performance. This could include recommendations to reduce the number of products included in a specific ad, mention the brand sooner, make the CTA more prominent, or to humanise the assets.
3) Attention mapping:
Trained on thousands of data sets and real-life simulations, AI-powered attention mapping is a useful tool that enables marketers to identify how salient their messaging is, without having to test it in a lab.
While ensuring your message successfully lands and grabs the attention of your target audience, visual tracking also analyses brand prominence and makes sure that the other campaign elements aren't overshadowing brand visibility. One global luxury brand recently saw an uplift of 121% by implementing SmartAssets’ recommendations to increase the CTA size and limit how many products were displayed in assets.
4) Quality assurance
Creating consistent ads is a challenge for teams of all sizes—but AI takes the grunt work out of manual asset-checking. Using computer vision to scan through thousands of assets in record time eliminates the risk of manual error.
This is most effective at scale: global campaigns across several languages, varying products, taglines, and different regulatory compliance laws. Using a combo of rule-based logic and AI, brands can now easily control asset quality, and ensure their brand guidelines are consistently enforced on all advertising platforms.
If you’d like to find out more about how SmartAssets can help you improve your advertising, feel free to book a demo.
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