Marketing executives looking for the next big thing in tech have at least 28 options, according to Gartner’s latest Hype Cycle for Digital Marketing and Advertising, which illustrates how technologies mature from shiny objects to widespread industry adoption—if they don’t die out first.
Artificial intelligence for marketing is at the peak of inflated expectations, while customer data platforms (CDPs) and real-time marketing are near peak in Gartner’s projections, which means expectations for these technologies are the highest they’ll ever be. Nevertheless, along with blockchain for advertising, Gartner said these four technologies have the ability to transform how marketers do their jobs and deliver meaningful customer experiences.
The Hype Cycle starts with what Gartner calls the Innovation Trigger, which is where technology emerges from labs and quickly rises to the Peak of Inflated Expectations. From there, the cycle drops nearly as fast into the Trough of Disillusionment, which is about where Gartner placed tech like multitouch attribution, native advertising and personalization engines.
That’s not to say this is bad tech, but rather as customers start to use the tools, there will inevitably be bugs and other challenges like incompatibility with existing platforms, said Mike McGuire, a vice president analyst in Gartner’s marketing practice.
“I would argue the space between the peak and trough is about marketers learning to trust [the technology],” McGuire added.
Then, as platforms fix bugs and make other adjustments, there is a slow and steady rise on the Slope of Enlightenment, which is where Gartner placed influencer and advocacy marketing, multichannel marketing hubs, social analytics, ad verification and mobile marketing analytics.
Finally, after they graduate out of the hype cycle, the technology is productive and stable, and everybody uses it, McGuire said. Examples include tried-and-true tactics like email marketing. (Of course, not everything makes it this far.)
He said marketers should use the hype cycle to guide their investments in marketing technology, as well as new talent.
Here’s what Gartner had to say about a few of the most promising technologies still on the roller coaster:
AI for Marketing
McGuire noted as AI for marketers has matured, offerings have expanded to include IBM Watson, Adobe Sensei and Salesforce Einstein, which have generated a lot of media coverage and are now the source of frenzied speculation that runs the gamut from marketers worrying AI will take their jobs to hoping it will solve every problem they’ve ever had.
“Both ends of the spectrum are wrong,” he said.
In 2018, another Gartner survey found 11% of marketing technology executives said AI is the technology that will have the most impact on the industry in the next five years. And, over the next 20 years, Gartner said AI will drive “pervasive shifts across the marketing technology ecosystem, effectively transforming the marketing practice.”
Customer Data Platforms (CDP)
According to McGuire, a CDP unifies all customer data from all sources so marketers can model and optimize for given customer segments. But there’s still a disconnect between how marketers say they use CDPs and how vendors advertise their CDP capabilities—as well as what a CDP is, exactly. Half of the marketers surveyed who have deployed a CDP told Gartner it’s their CRM system. As a result, Gartner said CDPs’ movement through the hype cycle has slowed.
Blockchain in Marketing
Gartner said blockchain for advertising holds tremendous promise, but must first overcome significant challenges with scalability, performance and adoption. Dozens of companies have used experimental blockchain platforms for advertising, but none have been able to demonstrate ongoing viability.
Despite skepticism, Gartner said the technology is gaining momentum through support from organizations like the Interactive Advertising Bureau and work from companies such as IBM, Comcast and Amazon, which are collaborating on both the buy and sell sides of media.
McGuire said this technology sits at the very beginning of the cycle, so it’s not yet mature, but it has great potential in targeted applications like smart contracts that would allow all parties involved in a given transaction to see which stakeholder is responsible for which actions, as well as the timeline and terms.