Why advertisers are using AI to manage ‘choice overload’ and unlock first-party data

These challenges span from the decline of third-party cookies (even if their end date has once again been pushed off) and new digital privacy laws to the seemingly unstoppable rise of connected TV and overall changes in media consumption habits.

This transformation of the media ecosystem is happening with such speed and complexity that it’s difficult for large brands or holding companies, let alone an independent advertising agency, to navigate. However, if their ad tech partner has the vision to complement their AI-powered tools with technology built for the modern digital advertising landscape, brands, advertisers and agencies alike are more likely to succeed.

Minus cookies, advertisers have more choices, plus more data to ingest and act on

As terms such as “Web3” and “open internet” have been tossed around for the past few years, what’s clear is that the internet and online world are undergoing decentralization. 

This proverbial changing of the online guard signals a move away from a few large tech companies being in control. The most notable sign is the Department of Justice’s antitrust lawsuit against Google. The current and developing open web is more focused on community control, with consumers enjoying an increased say on how marketers use their data and, consequently, who advertises to them. 

For advertisers, this means transitioning away from the often-invasive third-party cookie and toward delivering a better advertising experience.

In the wake of the slowly dying single-device conversion model of cookies and the seemingly unstoppable growth of cookieless channels like CTV and streaming audio, advertisers are all but required to craft full-funnel omnichannel campaigns that deliver the better advertising experience consumers desire. 

Although this gives advertisers almost infinite choices of how and where to invest, it often leads to “choice overload,” ever-complicating the media evolution.

How choice overload is also a gateway to first-party data

As an example of choice overload, in a CTV-only campaign, when a programmatic trader examines the 50,000 applications for CTV, 300,000 available audience segments and 3 CTV video formats, the results present a staggering 45 million campaign options. And that’s just CTV — many modern campaigns require more than one channel. 

On the other side of this equation is data — and lots of it. 

The continued data loss from third-party cookies puts the spotlight on first-party data. First-party data is a golden ticket for advertisers because, as opposed to the relatively less-than-reliable anonymous proxy data collected from third-party cookies, this data is willingly offered by consumers (or collected in a privacy-minded way). 

This more direct data sharing helps teams comply with the latest updates to data privacy laws. It also acknowledges, tacitly or explicitly, that someone is willing to receive marketing from a brand in the future. 

While moving away from cookie data to more accurate first-party data is a positive for the industry, one problem demands attention: how to crunch this data and make it actionable for a better advertising experience, especially given that not every advertiser has the budget for a team of data scientists.

AI is an evolving tool helping advertisers parse 45 million ad choices

If a programmatic trader, for example, had an AI tool that could help them solve for the 45 million ad choices mentioned previously, they could use those AI-powered recommendations to optimize an underperforming campaign or increase the reach of a target audience.

And if there was a simple chat interface that the trader could use to help make sense of a massive amount of first-party data so it’s useful for a campaign — without a data science degree or team — that would be a game changer for many teams. 

Or, during campaign planning, if they had access to some of the latest AI-powered solutions, they could use a tool to find the lowest bid price and, as a result, reduce their customer acquisition costs. That saved budget can then be invested in future campaigns.

Advertisers need to evaluate their ad tech partners to ensure a good fit

While these tools have significant benefits, they’re only as good as their integration into the advertising technology provided by the ad tech partner.

For example, how useful are these AI-powered solutions if the ad tech partner cannot measure a CTV campaign to help their client understand their actual return on ad spend? Or, if they don’t have a solution to use that crunched first-party data for identity resolution and subsequent use in an upcoming campaign, then their ad tech partner may not be the right fit for them.  

And, perhaps most importantly, what if the ad tech partner solely relies on traditional (and dated) third-party cookie advertising strategies?

So, while it might seem obvious that AI-powered tools are only as good as the ad tech partner, advertisers searching for or auditing AI-powered ad tools should also ensure their partner has the vision to see the sea change happening in digital advertising — and the technology to navigate it. 

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