Why Automated Technology Should Have Adaptability Built Into Its Design

By Eric Schwartz, US Managing Director at Scibids

The most difficult – and exciting – aspect of digital marketing has always been the amount of data from which marketers can tailor campaigns. And, despite numerous regulations and changes to identity making it increasingly tough for marketers to utilize data, digital marketing has never been more important.

The industry’s reliance on data to create relevant campaigns has led to an explosion of automated technologies to process and analyze the available data more efficiently.

One of the most notable developments in recent years has been the rapid innovation and development within the artificial intelligence (AI) sector. In fact, Gartner has predicted that worldwide AI software revenue will grow 21.3% to reach $62.5 billion this year. So, it’s clear that AI is becoming an integral part of how companies are operating in the digital sphere. But how can businesses ensure that their automated technologies are adapting to the continually changing digital landscape?

Aligning Your Technology With the Times

Modern marketers are facing a raft of challenges including the deprecation of third-party cookies, the need to build first-party data stores, the emergence of channels such as connected TV, the attention economy, and post-pandemic changes to consumer behaviors, among other less-than-comfortable obstacles.

Looking for ways to navigate this complex landscape, many marketers are turning to automated technologies, and more specifically AI.

Modern AI has the power to run more calculations in a single minute than a human could in thousands of years. The ability to analyze data at this scale can provide marketers with highly optimized results, while giving them the flexibility to adapt their strategies in response to whatever hurdles the world may put in their path. However, not all AI-powered solutions are created equally.

Adapting to the Fast-Changing World

Instead of thinking that technologies should be set in stone, any solution implemented must be as adaptable and customizable as a campaign’s messaging and creative, meaning brands are able to tailor their AI tools based on the goals they’re looking to achieve on a campaign-by-campaign basis. Cookie cutter solutions are incapable of adjusting to a brand’s individual needs and, as a result, fail to drive cost efficiencies. But campaigns that run on technologies with adaptability baked in enable marketers to deliver cutting-edge advertising to consumers, regardless of regulations, changes to identity, or shifts in consumer behavior.

Furthermore, many existing solutions were engineered with individual cookies in mind. The next generation of AI tools, and machine learning algorithms, are built to tackle evolving data practices. They can flexibly ingest large amounts of data that relates to advertising contexts and not users, and are capable of providing the answers needed in a world where there is a wealth of data, but an increased need to respect consumers’ personally identifiable information as well.

By taking on a broader, more flexible, privacy-focused approach, AI tools solve many of the problems that the reliance on third-party cookies has caused.

Customizable AI algorithms adapt to unique business needs by adapting its bid models with custom data sources and focusing on metrics such as ROAS or attention. And those algorithms do that while finding patterns that open up consumer-friendly avenues for the brand, shifting advertisers away from any reliance they may still have on third-party data, and the user tracking and profiling that comes with that.

Time to Make a Change

Change is never easy, and many of us have been stuck in our ways for a number of years within the digital space. However, with the sheer number of complexities and challenges currently facing digital marketers, the change has to come now.

There is a lot of work to do to change the way we approach reaching consumers with relevant content. One thing we know for sure is that the over-reliance on third-party cookies, cross-site tracking, and behavioral targeting was never the answer. And a shift to a focus on broader datasets was always going to happen, regardless of regulation or changes to identity practices.

Importantly, and what will come as a relief to digital marketers, the best tools within this next generation of AI won’t be expecting you to entirely overhaul the way you operate, or turn your back on the tech stacks you’ve become accustomed to. Instead, the tools are interoperable, built to complement your existing workflows, and empower your current tech stack to deliver more for your business.

AI technology can deliver greater marketing value, while ensuring that your marketing is future-proofed and more privacy-aligned. It’s time to leave behind the intrusive legacy technology of the past and embrace the here and now of adaptable, privacy-focused automation.

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