Bold, beautiful, and fantastical, Davinci Production’s unauthorized Dior ad is just the latest captivating showcase of how far artificial intelligence has come.
By and large, most industry players have reached the point where AI’s ability to whip up such stunning visuals is seen as an “amplifier of human creativity,” not a threat. But while the man versus machine debate is (mostly) settled, that doesn’t mean there isn’t any conflict about where we go from here.
While marketers embrace generative tools for efficiency, 80% worry about ensuring smart content aligns with regulations and brand image. Agencies argue campaign quality depends heavily on brands providing clean, compliant data. Regardless of responsibility, the future of advanced tools hinges on the quality of the data driving creativity.
You get what you give: input is everything
The best illustration so far of how much foundational data impacts smart technology in a creative context comes from Heinz. As part of a tongue-in-cheek campaign, the food giant shared what DALL-E created when asked to draw ketchup: multiple images featuring immediately recognisable elements of its packaging that clearly illustrated the pervasiveness of classic Heinz branding and the huge influence training data has on generative production.
Although most marketers have started to recognise this direct correlation between AI output and data input, a high proportion have limited access to the right fuel. According to multi-sector studies, data proficiency still needs to improve, with employees spending 30% of their week on unproductive data tasks, while only half of in-house data experts are confident that their workforce knows where to look for crucial reports, datasets, and insights.
These figures suggest many firms continue to struggle with well-worn basic data management issues that leave marketers – and their agencies – without the solid data foundation needed to successfully harness AI.
Suffering with silos: poor data unification
While causes of inefficient data coordination vary, silos remain the most frequent offender. There is still a widespread tendency to collect and store data in isolated buckets that are often made all the more challenging by lingering reliance on manual processing — as underscored by the fact four in ten cross-industry employees cite structuring, preparing and manipulating information among their top data difficulties.
Therefore, a sizable number of organizations are working with fragmented and inconsistent data that requires time-consuming wrangling and is often subject to human error. The obvious problem this poses is a lack of the comprehensive data to inform sound decisions. At the AI-assisted marketing level, faulty data has a high potential to jeopardise creative efforts; resulting in irrelevant ads that miss their mark for target audiences and brand goals and misguided strategic moves based on skewed analysis.
Of course, there are no quick fixes to tackle these complications. But businesses can reach greater data maturity and efficacy by reconfiguring their orchestration methods.
With a streamlined system that persistently delivers consolidated data, marketers will be equipped to extract key performance and consumer insights that steer refined and precise AI-enhanced activity. Yet, it’s important to note that unification won’t eradicate every issue. To keep data reliable and usable, marketers need better ways of ensuring ongoing quality.
Abiding by stricter quality standards
As highlighted by Gartner, boosting data quality isn’t a one-time action; it’s an endless mission. Per Gartner’s dedicated guide, regular profiling — A.K.A auditing — of data flowing from each source is critical to spot issues and take corrective steps. So too are dashboards providing easy access to reports that facilitate robust at-a-glance reviews of current quality and identification of longer-term patterns.
Establishing standardised data procedures will curb the likelihood of duplicates, mistakes, and out-of-date details creeping in at vital points during the data lifecycle, from initial entry to transformation and activation through gen AI creative and analytical tools, on top of ensuring data use meets increasing data regulations.
Marketers have an essential role in deciding where we go from here. To drive in-house and agency-managed efforts forward, they will need to realise that the art of intelligent creative lies with mixing the right data palette and working on concocting a high-quality mix.
About the Author
Mark Debenham is VP of Growth Marketing & Operations at Adverity. Centralized Data Management for the Modern Marketer. Adverity is the integrated data platform for connecting, managing, and using your data at scale. The platform enables businesses to blend disparate datasets such as sales, marketing, and advertising, to create a single source of truth over business performance. Through automated connectivity to hundreds of data sources and destinations, unrivaled data transformation options, and AI-powered data governance features, Adverity makes it easy to scale and automate your data operations and have trust in your data.