45% Of U.S., U.K. Advertisers Have Used Same Ad Approach For Past 5 Years

Accenture earlier this year released research in partnership with Pinterest that analyzed the state of the advertising market, its upcoming challenges and how prepared advertisers are to face them.

The research found that that 74% of advertiser budgets have been impacted by the economic downturn, and 47% of advertisers say they have grappled with rising campaign costs.

Around half of advertisers have seen privacy changes such as the drop-off in legacy third-party identifiers, with a negative impact on campaigns. About the same number expect upcoming privacy changes and challenges to reduce campaign effectiveness.

But even more surprising is that 45% of U.S. and U.K. advertisers have been using the same approach to advertising for the last five years, and 71% of this group don’t plan to change their strategy in the next year. That leaves 32% who will continue to use outdated advertising strategies.



“Advertisers are reluctant to change their strategies across audience targeting, platform selection, measurement, attribution, creative -- you name it -- likely because there is a lot of friction in change and the status quo has worked for most advertisers in a world with cookies,” says Nikki Mendonça, managing director at Accenture. “This reflects an if-it’s-not-broken-don’t-fix-it mentality, but with big generative AI investments, we could see a near future where advertiser strategies get quickly rewritten.”

The data also found that globally, advertisers on Pinterest using strategies that do not rely on third-party identifiers, like interest and keyword targeting, run no risk to their return on ad spend or conversion rates when compared with retargeting alone.

And when using the most granular interest-based targeting, advertisers globally saw 45% higher ROAS than advertisers that were leveraging retargeting alone across a 30-day attribution window.

What findings surprised Mendonca the most?

“Even though a cookieless world has been in discussion for the past three years, we were surprised to find that over half of advertisers didn't have a good enough handle on their data for intelligent audience targeting or measurement,” Mendonca said. “It isn’t surprising, however, that advertisers said their organizations did not align on ROI, ROAS, or full-funnel outcomes as top objectives or factors to consider when choosing what platforms to run on.”

Without the proper attribution models in place, it is impossible to measure a key performance indicator (KPI) like return on ad spend (ROAS).

Mendonca believes that a first-party data architecture, fueled by AI-powered measurement and optimization tools, is the backbone of any good marketing program.

Many advertisers don’t have this foundation or talent to fuel this type of program -- and this should be addressed first before tackling any other issues.

Marketing is at a critical inflection point, with more data, advanced machine learning, and artificial intelligence technologies available. But it's crucial to see how marketers harness that data and technology to fuel intelligent, personalized, and connected customer experiences, Mendonca said, pointing to findings from the study.

“Generative AI is a hot topic for marketing -- across content generation, optimization, personalization, and synthesizing large datasets to drive insights, but it’s not the end-all-be-all for optimizing an entire marketing program,” Mendonca said. “For example -- generative AI won’t provide the backend data infrastructure needed to harness first party data for better targeting and attribution.”

She added that GAI is not about replacing humans — it’s about giving them the tools they need to be as creative, strategic and impactful as possible, and to eliminate or cut back on time-consuming, tedious tasks.

There are a few key elements that Accenture thinks GAI will transform for marketing programs:

  • Making better-informed decisions with enhanced intelligence rooted in data and insights, while eliminating guesswork and reducing errors
  • Unlocking creativity by automating slow, labor-intensive tasks that typically take up bandwidth that could otherwise be used for creative output
  • Delivering highly personalized experiences throughout the customer lifecycle
  • Meeting increasing demands to produce more content in shorter time frames

GAI will be transformational not just in marketing, but across the entire customer journey and marketing, sales, service continuum, and more. GAI being able to predict the next-best-action for pushing customers through the sales cycle, or building intelligent customer service GAI chatbots at scale.


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