Generative artificial intelligence (GenAI) has set the marketing world aflame. Tools like DALL·E and Adobe Firefly have demonstrated the potential of AI to produce engaging creative from limited resources. Looking beyond that, what can it offer in terms of media efficiency for brand and retail marketers?
The ability of GenAI tools to remix and iterate on a prompt in seconds means that marketers are empowered to fashion different versions of the same creative almost instantly. Would a different backdrop show off the product better, or would a change to the context in which it's presented better appeal to a different shopper? With GenAI those changes can be made and tweaked to perfection in a fraction of the time it used to take.
For resource-strapped marketers in an increasingly tough retail industry, that ability is a blessing. Advertising creative drives almost half (49 percent) of incremental sales, according to a study by Nielsen, and is the most critical driver of advertising effectiveness as a result. That hasn't changed since 2017, suggesting that effective creative is a consistently important part of digital toolkits.
But what is "effective" in one context, or for one demographic, may not be so for others. With GenAI’s ability to turn new creative around quickly, there are many more opportunities to find that optimum creative for any circumstance or audience — without increasing resources to do so.
But that's far from the end of GenAI’s offering for retail marketers.
Doing the Legwork
AI-derived creative is turbocharged by other implementations of generative AI. When teamed with its ability to track changes in datasets at scale, GenAI can optimize creative output to ensure that the ad creative lands with the right audiences at precisely the right time.
AI tools can identify patterns and trends that drive optimal audience engagement with a particular sort of creative. That in turn enables marketers to deliver optimal return on investment for advertising (ROAS) by marrying that tailored ad creative with an AI-powered deployment strategy.
Retail marketers are often in a good position to use data, both from previously deployed marketing campaigns and opted-in customer interactions. Smart AI tools can train themselves on these rich data insights to understand what counts as normal audience behavior vs. what’s not. That takes the legwork out of marketers’ workload, while adhering to privacy rules that protect consumers. Rather than having creative personnel poring over audience habits that can change quicker than the task at hand, GenAI can take the strain while freeing marketers up to look at the bigger strategic picture in real time.
Creative Measurement
Applications of AI can bring all the creative performance data together, providing a holistic overview of every aspect, including costs, clicks, and longer-term measures like lifetime value.
In the fast-paced world of retail marketing, that can provide tangible benefits for brands and retailers looking to speak to consumers ahead of — and in more engaging ways than — their competitors. As personalization and the importance of returning customers climb retail marketers’ priority lists, those measurements provide a road map to using tailored creative in the most effective manner.
The combination of the myriad assets that can be created through GenAI and the real-time measurement of their effectiveness ensures that retail marketers can scale their offering in ways that are not too resource-intensive. For an industry that's too often stretched thin and focused on manual measurement of effectiveness at the expense of efficient speed to market, it's a game-changing addition to marketers’ toolkits — and one that reprioritizes creativity.
Sue Azari is e-commerce lead, EMEA and LATAM at AppsFlyer, where she brings her deep knowledge of the sector to advise companies on their mobile marketing strategies.
Related story: How Will Generative AI Disrupt Retail Marketing?
Sue Azari, E-Commerce Industry Lead at AppsFlyer
Sue Azari is eCommerce lead, EMEA & LATAM at AppsFlyer, where she brings her deep knowledge of the sector to advise companies on their mobile marketing strategies. She has more than 10 years’ experience scaling retail apps, having worked at a number of high-growth brands, including The Very Group, Net-A-Porter, and Beauty Pie. Outside of work, Sue spends her time practising yoga, cold water swimming, kayaking and travelling to new cities.