What Gartner’s 2024 digital ad hype cycle shows about marketing innovation and adoption

By Marty Swant  •  August 21, 2024  •

Ivy Liu

“Marketers are looking to increase or stretch fewer dollars over more expensive mediums and more expensive tools,” said Gartner marketing analyst Mike Froggatt, who co-authored the report. “With marketing tech providers, it’s pretty safe to say they’re not going to be reducing their costs — especially as they started to create AI and other tools that … require a ton of processing power. That’s not cheap.”

The biggest movers include TV advertising, identity resolution, and customer data platforms, which made its debut on the hype cycle. However, Gartner removed promotional NFTs from this year’s list, since according to the report, the topic has “quietly exited the stage as an advertising opportunity” following a “spectacular collapse” of NFT trading platforms.

Along with other terms familiar to marketers, new arrivals on the hype cycle include AI-related categories like generative AI for marketing alongside other topics like emotion AI for marketing and influence AI, and visualization AI. Influence AI automates digital experiences to help marketers to shape consumer choices more effectively based on user intents and motivations. Emotion AI analyzes and responds to users’ emotional states with tailored experiences based on body language, voice, and other inputs.

“Generative AI continues its surge forward, heading into the Trough of Disillusionment,” said fellow Gartner marketing analyst Nicole Greene. “The increased hype over the last year lead has led to misplaced expectations of what the tech can deliver. The true potential of genAI will be revealed when combined with other AI techniques.”

The report also accounted for Google’s latest plans to not deprecate third-party cookies like it had planned. Froggatt noted that the news will impact almost every profile included in the report including generative AI. Some of the sections that received edits as a result were retail media networks, consent and preference management, data clean rooms, programmatic segment-based advertising and personification.

Gartner isn’t the only firm to update forecasts as a result of Google’s news. Earlier this month, Boston Consulting Firm noted a majority of markets said changes to third-party cookies posed a risk to at least 20% of data used for targeted marketing. Last month, Forrester said 61% of markers surveyed for its 2024 report had already expressed skepticism in Google’s plans even before its announcement.

Here’s a look at five technologies on Gartner’s 2024 hype cycle:

Generative AI for Marketing 

• Promise: Generative AI advancement and adoption have progressed immensely in the past year and now has an estimated target market penetration of between 20% and 50%. Drivers include improved foundation models, an increased impact on marketing creativity and productivity, more enterprise adoption, enhanced deepfake detection, and increased competition for pricing and safety. 
• Challenge: Rapid adoption has also led to greater scrutiny of the technology’s ethical and societal implications, ranging from AI disinformation and fraud to social unrest and licensing issues. Those concerns and others are leading many marketers to still approach the tech with caution despite early results — not to mention other challenges with training, output consistency and bias. Despite advancements, Gartner found most companies are still in the exploratory phase, with content creation efficiency instead of fully shifting to AI-generated ads at scale.
• Outlook: Marketing execs need to navigate the trough of hype cycles by prioritizing use cases where generative AI is a good fit, Greene said. Chief marketing officers and others also need to account for budgets, data governance, time and employee training. She added that areas like Influence AI and emotion AI for marketing are also aided by first-party data.

Customer Data Platforms (CDPs) 

• Promise: Making its debut on the 2024 hype cycle are customer data platforms (CDPs), which still remain two to five years out from reaching a plateau. Key drivers include more CDP connectivity across marketing suites, organizations’ increased reliance on centralized data, and a higher focus on privacy and regulatory compliance. 
• Challenge: Key challenges include varying operating costs, overlapping martech features, integration complexities and a higher level of technical skills.
• Outlook: CDPs could play in helping companies fine-tune AI models and grounding data to improve answer accuracy. 

Retail Media Networks (RMNs)

• Promise: As retail media networks expand, drivers include online sales outpacing in-store retail, increased investment in performance, data signal loss, concerns about walled gardens — from brands and retailers alike. Others include increased retailer use of loyalty apps, mobile in-store scanning and higher presence of digital screens in stores.

• Challenge: Despite all the rage around RMNs, the technology is starting its descent into Gartner’s “trough of disillusionment” amid a growing gap between promises and reality. Fragmentation, inconsistent standards, pricing issues, ad spending pressure and overall confusion are all creating new challenges after early rushes to build and adopt. There are also growing pains as teams merge across traditional and emerging channels to adapt to and adopt RMNs.

• Outlook: Advertiser relationships with RMNs and vendors still have a lot of work to do. Some brands are feeling more pressure to double-pay through advertising with both RMNs and online platforms to drive traffic to the RMNs. “Last year, it was getting it done, [adopting] as many retail media networks as can be, maximizing sales for the cheapest [advertisers] we can get,” Froggatt said. “It was about finding that point of diminishing returns for every individual retail media network. This year, we’re getting a little bit more into the weeds of management.”

Data Clean Rooms

• Promise: These are also approaching their peak of inflated expectations, driven by more data deprecation, more focus on first party data, more measurement and the drive for more privacy compliance. 

• Challenge: There are still issues like device ID gaps, regulatory uncertainties — especially with state laws demanding different levels of privacy — and uncertainty around cost estimates.

• Outlook: Gartner is looping clean rooms in with a broader category of “data collaboration tools,” which help with identity resolution, consent preferences and optimization. One example is the increased focus on improving reach and frequency of campaigns across online platforms and connected TVs.

Programmatic Segment-Based Advertising (PSBA)

• Promise: A rising technology on the hype cycle, PSBA is still ascendant on the hype cycle. The tech aims to improve accuracy and accountability in cookieless environments by targeting clusters of users instead of individual people. Other tech like contextual targeting and verification services fall under a broader category of programmatic segment-based advertising. 

• Challenge: Although PSBA aims to improve privacy, there’s still a risk that segment IDs could become attached to people when combined with other data. There’s also still little understanding of the benefits and risks of segment ID traffic in open bidstreams, which have varying pricing and privacy practices.

• Outlook: With market penetration falling between 1% to 5%, PSBA is still lower on the innovation curve, especially when considering browser usage and Google’s Privacy Sandbox developments. Marketers can improve their effectiveness with PSBA by supporting pre-bid and open-source standards, according to Gartner, which also noted walled garden environments should still be considered. Agencies and data science teams can also help with modeling the potential outcomes alongside the use of data clean rooms. 

https://digiday.com/?p=553092