In 2022, the marketing industry is being forced to develop a new mindset that recognizes and respects consumer concerns about data privacy and the planet.
Earlier this summer, Scibids co-founder and president Remi Lémonnier coined a new term, “virtuous advertising,” to describe the future for marketers. But what is it? And why is Artificial Intelligence (AI) playing such a big role in making Virtuous Advertising the new normal?
Virtuous Advertising recognizes that marketing organizations are under increasing pressure due to the increasing economic, environmental and regulatory pressures surrounding digital marketing. At the heart of the Virtuous Advertising concept is respect for resources. In other words, be efficient by using only the resources that are absolutely necessary.
In the context of digital marketing, this means removing as much “waste” from your advertising campaigns, and the best way to do this is to not serve digital ads to people who are unlikely to convert. AI helps Virtuous Advertising by constantly adapting to avoid irrelevant targets and redistributing budgets in real time for leaner campaigns.
Open the door to AI
According to a recent survey of modern brand marketers, many question whether their marketing stack is delivering the right scale and performance. Adding to this enormous challenge, today’s decision makers are faced with a variety of challenges, including increased privacy regulation, a lack of human expertise, the environmental impact of digital marketing, a fragmented technology landscape, and a volatile macroeconomic climate. dealing with external issues.
How do you bring these multiple considerations into your marketing tech stack while delivering business growth and strong ROI for your advertisers? Designed to address the challenges facing digital marketing , well-engineered AI provides a path forward.
One thing to consider here is the type of AI used. Ready-made algorithms for ad decisions provide standard lift for all users. In contrast, advanced and sophisticated AI provides customizable algorithms that can be optimized for differentiated results while leveraging and augmenting your own data sets.. Advertisers use their own data to create advanced optimizations that build a unique competitive advantage in their campaigns.
How is AI being used today?
It is estimated that around 40% of programmatic ad spend in the UK is currently using algorithmic decision-making or artificial intelligence. Agencies generally use algorithms/AI systems more than brands, and interestingly, agencies and brands often deploy AI for a variety of reasons. While increased revenue is driving agencies to use AI, brands are motivated by the potential for privacy-compliant targeting.
Overall, increased operational efficiency, convenience, and revenue are the most commonly cited factors driving the use of algorithmic decision-making and AI in digital marketing, with scale and campaign optimization being less prominent. It’s a factor. “Complexity” is often cited as a major barrier to further use of AI-enabled tools.
When considering using AI within an organization, it is important to consider how effective traders can be through automation. Designed to use all available data to calculate the optimal media price, AI outperforms human guesswork. This improves the quality of insights available to professionals and provides a clear path to scale efficiencies across more media opportunities. People can do their jobs more effectively if they have the right tools for the job, instead of feeling betrayed by the technology they use.
AI in context
In today’s privacy-driven environment, marketers can no longer rely on cross-site tracking or personal identifiers to make advertising decisions. However, if you get contextual signal results, a UK marketing her professional reports that these work just as well as traditional identifiers.
Despite these promising results, a small number of brand marketers are currently using all contextual signals (log-level data) included in bid requests. Intelligent use of AI can make this freely available, log-level data actionable for privacy-friendly media purchases.
While there are many commercial metrics that advertisers must focus on, marketers should prioritize insights from data sets such as sales data and warehouse inventory level data. We encourage you to focus on these datasets and partner with companies that can ingest that data and codify it into AI to generate performance metrics that can optimize your media buying.
Advertisers without advanced data science and engineering capabilities should plan to leverage AI to incorporate business metrics into the buying process. For more sophisticated buyers, AI can be used to tailor media buying strategies to specific business outcomes.
If the industry as a whole cite a lack of expertise as a major challenge, every manager should equip their teams with the tools they need to make sure their work is meaningful, insightful, and accountable. Must provide. AI is not meant to automate most of what industry professionals do. Instead, it is a very important and very powerful tool to help build a responsible and “virtuous” future for the digital marketing industry.