We’re nearly a month into 2024 and it’s clear that two of the major issues of last year are set to continue as white hot themes for this year – cookies and AI, both of which provide clear opportunities for advertisers to improve our practices.

And in the ongoing journey towards more accurate attribution and a human marketing experience, it could be that the decline of cookies and the rise of AI takes us significantly closer to where we want to be.

However, before we get too carried away with the exciting possibilities these shifting technologies present, it’s worth remembering that key requirements for advertising success that have not changed: reachbranding, and ease of finding and buying remain fundamental to success, regardless of whether you’re using cutting-edge tech or a three-decade-old feature that’s on its way out.

Reach real humans, not bots; Meta example

Seemingly the easiest of metrics to measure, reach is in fact a truly nuanced advertising requirement, because successful ads reach real human audiences – whereas measuring ‘users’ usually leads to a figure inflated and polluted by bots.

Arguably just as important is reaching interested individuals, because an ad seen by a million apathetic people is going to be less effective than one seen by a fraction of that number if the latter audience are made up of people whose interest is piqued by what they see.

This is why determining the actual reach of many channels has long proven so challenging, even in the digital environment, where different tech and methods – including cookies – are used to provide reach reporting.

Simply put, not all reach is equal, and a deep understanding of each advertising medium and channel is necessary to assess actual reach. Happily, we are seeing increased awareness of this challenge, giving rise to new research and metrics – in particular, the metric of attention.

On top of this, continuously evolving technical skills are required to identify good channels and make effective buys within each channel.

For example, objective and placement optimisation within Meta has become an intricate and important artform, with many combinations of available inventory having a major impact on the reach and human reach that your campaign receives. Often the default or recommended settings are not what will yield the best results – take ‘Meta Reach’ campaigns, which can drive more incremental conversions than when using a ‘Conversions’ objective.

Of course, this is not a challenge unique to social platforms, as AI continues to expand the total amount of inventory and impressions available to be monetised. This means you need trusted partners to ensure true reach, as well as ownership of your tech platforms to monitor shifts in consumption and inventory.

Fixing flawed last-touch attribution – without cookies

At the same time, cookie-based attribution remains in wide use, even as Google has pledged to phase them out of Chrome in the second half of 2024.

Our industry is still intent on linking an individual sale or conversion back to a specific digital campaign or ad, largely through last-touch attribution – an inherently flawed practice which made Google branded search and the inflatable tube man at the car yard the most effective media channels on the planet.

In good news, the advancement of machine learning has made advanced measurement practices – such as Market Mix Modelling – much more accessible. We are growing a far more nuanced appreciation of the importance of the journey to purchase, rather than just giving all the credit to the last step before reaching the destination.

Machine learning has also served to underline the ongoing value of incrementality; of ensuring your organic sales are attributed as such, rather than incorrectly chalked up as a win for a campaign that may not have been as effective as you credit it.

And far from being reliant on third-party cookies, incremental value can be measured more accurately by stripping things back. Baselines can be established in comparing timeframes, media mixes or markets and constructing tests to measure genuine incrementality.

This means there is no need to panic about the death of third-party cookies, which have served a purpose but have also always been an inherently flawed method of attributing sales.

Bringing brand and performance together

Excitingly, the above changes can create new opportunities for marketing and creative teams, with the shift in measurement away from digital attribution helping the brand and performance camps to hopefully become less siloed.

Yes, there are still ways to target an identified or in-market audience, and digital can provide the means to reach your audience in the right context.

But the techniques that led to the delineation of marketing skill sets, channels and budgets into two distinct disciplines have changed dramatically – even when it comes to search.

As we all know, consumers don’t think in campaign terms or about which stage of the buying funnel they are in. But with AI’s continued growth and cookies set to end up in the trash, marketers have increased opportunities to better appreciate and understand what steps on the journey to purchase have the most weight, even if the person making the purchase never stops to think about it.

Ironically, the age of AI may give rise to a more human form of advertising.

Rather than chasing the sugar hit of an ad-level conversion, marketers of all disciplines can seek the lasting impression that associates the brand with the desired product-use cases or buying contexts.

In 2024 one tool, AI, will continue to proliferate and present both new opportunities and challenges in reaching this goal, while another long-relied upon tool, cookies, will finally give ways to more sustainable targeting and measurement practices.

Article originally published on Mi3.