There are numerous examples of high profile brands experimenting with artificial intelligence (AI) in creative ways. For example, Lexus recently worked with IBM Watson to release the first AI scripted advertisement.
AI is ultimately here to improve people’s lives both at work and at home, yet many organizations are still timid about investing in the technology. Here are some strong cases for investing in AI for advertising today:
Achieving True Scale and Engagement
Marketers are investing in AI to deliver advertising that is relevant, contextual and hyper-personalized to individual consumer preferences. Automation is an important component of driving this capability.
Adam Powers, CEO at Tribal Worldwide, shared at Mobile World Congress 2019 how they use AI in advertising to create contextual experiences for users: “Offer an experience where the application of AI is an invisible factor—emotional engagement and conversion focus. Magic can happen in the details, the small things and looking at the practical application of AI. For example, a client in Indonesia uses machine learning to forecast fashion trends by feeding in various data points, and image uploading to forecast in which part of the region certain products will sell.”
“Brands need to try to keep up with changing consumer behavior,” added Neil Stubbings, CRO at IV.AI. “It’s the age of availability. A brand should be available on any platform that the customer is, and that’s the challenge and the opportunity for brands to transact with consumers…people are looking for things that feel more native.”
Customer Journeys: In Real Time
The linear sales funnel is a thing of the past, and marketers are turning to AI to optimize ad campaigns mid-cycle at scale. James Hilton, Global CEO of M&C Saatchi Performance, said: “We acquire retained customers for world leading brands. We are a performance agency, so we use ML and AI to get the right customers at the right price, and get the right yield for clients.” Having seen first-hand the tremendous impact of ML and AI technology on clients’ campaigns, I can vouch for that.
Finding Ad Fraud Warning Signs
From our experience, one of the most important use cases in the digital advertising space is the potential to fight ad fraud. Marketers are already exploring how to use user data and ML to solve challenges around attribution, like finding patterns early, that can lead to fraudulent sales.
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Jay Benach, Strategy Lead at White Ops, a cybersecurity company specializing in bots for advertising, ecommerce, social and more, said that when they started their business in 2013, they were detecting malware with minimal data, and then telling advertisers when they discovered bots. Advertisers were rightfully frustrated and asked the firm to stop the bots before they hit the platform, not after it has already occurred.
In response, many adtech companies fighting fraud have developed ML-based solutions to identify and stop fraud before it happens. To illustrate the extent of this persisting issue, only a few months ago, the FBI shut down ad fraud “botnet” that was running through the entire ecosystem and defrauding advertisers for years.
Given the pervasiveness and the aggressive nature of how new types of fraud attacks emerge and infest the ecosystem, ad fraud will continue to be an area where technology development is focused and moving quickly. Advertisers will want to look at the potential of AI and ML for mitigating this fraud going forward.
AI and machine learning bring a lot of possibilities for the advertising industry, and ultimately, for the consumer experience. Advertisers should already be thinking about how they build the right teams to leverage this technology effectively—whether it’s investing in data scientists, or training creative teams to interpret and analyze data. Ultimately, collaboration across cross-functional teams from creative to IT will be crucial in driving AI adoption effectively in advertising.