How Data Driven Creativity Is Changing Advertising

Creativity used to be a nebulous concept. Traditionally, creative departments spend weeks, sometimes even months, coming up with campaign and ad concepts guided primarily by subjective creative instinct.


The dawn of technology and data science in the ad universe has completely changed the ballgame. Now, marketers are equipped with insights capable of informing every stage of the creative process from planning to execution. It’s no longer a “let’s get this out there and hope for the best” kind of scenario. We now know predictively what is most likely to work and when we should start refreshing ads as they begin to experience fatigue.


Data driven creativity is enabling brands to gather deep insights around their audiences as well as the best channels and ways to reach out to them. Ultimately, time and money are saved by using innovation to make creatives perform better in driving business goals.


A/B Testing

Netflix is a great example of a data driven company that has successfully harnessed the power of data and insights. Every video comes with half a dozen images which are tested with a subset of the user base. The winning images are then used with all of Netflix’s members. By deploying  A/B testing, the company has achieved between 20 to 30 percent increase in video viewing.



In an era where customers value unique tailored experiences, personalization is a must-have marketing strategy. Marketers see an average increase of 20% in sales when using personalized web experiences. Personalized CTAs result in a 42% higher conversion rate than generic CTAs.


Creating audience segments by identifying discernible patterns in behavior from data across all touchpoints is an effective way of personalizing your marketing efforts. Creatives and messages can then be tailored towards each target audience segment to bring about a personalized experience.


Predictive Analysis

Predictive analytics uses data mining, modeling and statistics to forecast consumer behavior or outcomes of marketing efforts.


This allows advertisers to be more precise with their messaging by focusing on pinpointed demographics with a precise message for a precise purpose. With enough adoption of predictive analytics, irrelevant ads will disappear. And as advertising becomes more effective, return on ad investment increases.


During the creative development process, pre-production predictive analysis arms designers with insights on visual compositional elements that work best for each target audience segment even before they start creating. When selecting ads to run, advertisers are given predictive insights into the ad versions that would most likely perform better among all available creatives.


This pretty much takes most of the guesswork out of the creative development process, giving designers and advertisers more control over creating and running ads that work.

Alexis Ng

Digital marketer with a love for the ocean, yoga and constellations. Watches too much TV.

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