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Written by Christopher Van Mossevelde
Head of Content at Funnel, Chris has 20+ years of experience in marketing and communications.
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Reviewed by Julian Modiano
Co-founder and CEO at Acuto, a company that builds data and automation solutions tailored to agencies
How can you gather and use creative data to optimize your ad creatives? This isn't just about making your ads look good; it's about making them work hard to drive engagement and increase ROI.
Julian Modiano is the CEO of Acuto, a company specializing in creating customized data and automation solutions for marketing agencies. In a recent discussion with Funnel, he explained how to use creative data to optimize ads and make a creative team truly data-driven.
Julian Modiano, founder and CEO of Acuto
Introduction to creative data
Let’s first address what “creative data” means to us? Creative data encompasses all the measurable elements of your ads — from colors, labels, objects and entities to the text within the images.
It's in your ad creatives' DNA, providing insights beyond basic performance metrics. But how do you actually begin to harness this wealth of information?
Gathering data into BigQuery
The journey begins with gathering all your creative data into one place, and for Acuto, that place is BigQuery. Acuto does this really easily by using Funnel, a marketing intelligence platform. BigQuery is the backbone of Acuto’s data-driven strategy, allowing them to efficiently store, query, and manage vast datasets.
“By centralizing our data, we set the stage for sophisticated analysis and optimization strategies,” said Julian.
Processing with the Google Vision API
With their data in BigQuery, the next step is to send all their ad images for processing with the Google Vision API.
“This powerful tool allows us to dissect our creatives at an atomic level, extracting crucial elements such as colors, labels, objects, entities, and text,” explained Julian.
For instance, in a project for an automotive-focused agency, Acuto discovered that ads featuring images exclusively focused on cars consistently outperformed those incorporating unrelated elements.
This revelation, while seemingly intuitive, challenged conventional assumptions and underscored the importance of data-driven decision-making in creative strategy.
“It's like giving our ads a thorough MRI, revealing insights invisible to the naked eye,” said Julian.
Joining Creative and Performance Data
Once the Acuto team has all its creative data, it combines it with its performance data. This marriage of creativity and analytics allows them to see not just what their ads look like but also how they perform in the wild.
It's here that Acuto starts to answer more meaningful questions about its creatives at scale. For example, they can gain answer to the following questions:
- Which colors resonate most with our audience?
- Are certain objects more engaging than others?
Analyzing and generating recommendations
With a comprehensive dataset, Acuto’s analysis can be more thorough.
“We use various tools and techniques to sift through the data, looking for patterns and correlations that can inform our future ad campaigns,” said Julian
He explains that this process generates actionable recommendations, guiding them on which elements to emphasize in their next batch of creatives.
Predictive performance modeling
But they don't stop there. Before they launch new creatives, they run them through a predictive tool that evaluates their likely performance based on their historical data. This step is crucial. It acts as a safety net, ensuring that their ads have the best chance of success before they even go live.
Making the creative team data-driven
All these steps transform how the creative team works.
“By intertwining data analytics with the creative process, we're not just guessing what might work; we're making informed decisions based on empirical evidence. This approach doesn't stifle creativity; it supercharges it, providing a solid foundation to innovate,” said Julian.
Optimizing your ad creatives with creative data isn't just a good practice; it's necessary in today's competitive digital landscape.
By following the steps mentioned above — which involve gathering data in BigQuery, processing it with the Google Vision API, analyzing performance, and generating recommendations — you'll be able to create ads that are not just ads but data-driven works of art that your audience will love and that will deliver unmatched results.
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Written by Christopher Van Mossevelde
Head of Content at Funnel, Chris has 20+ years of experience in marketing and communications.
-
Reviewed by Julian Modiano
Co-founder and CEO at Acuto, a company that builds data and automation solutions tailored to agencies