30-second summary:

  • Consumers increasingly place their trust in known entities — family, friends, institutions and familiar brands. This shift is undermining investments in influencer marketing.
  • Marketers and advertisers are using artificial emotional intelligence (AEI) technologies to gather insights on users’ reactions to products and services.
  • Only 22% of marketers say they have in-depth insight into known customer values, but CMOs identify marketing and customer analytics as the capability most vital to supporting their marketing strategy.
  • 80% of marketers will abandon personalization efforts by 2025, due to lack of ROI.
  • Personalization now comprises 14% of the marketing budget, yet more than one in four marketers cite technology as a key obstacle to personalization.

Several key marketing trends will veer into a new direction in the next few years, according to a recent set of predictions from research firm Gartner.

The “Predicts 2020: Marketers, They’re Just Not That Into You” report [accessible only by clients] is the latest is a series of predictions Gartner makes based on “where things might be going,” Research VP Jennifer Polk told ClickZ, as a kind of “finger in the wind.”

Influencers, AEI and personalization

All of the predictions challenge current thinking:

  • Influencer marketing will become transformed by the trust that consumers, institutions and brands prefer to place in known entities. By 2023, Gartner predicts, budgets for influencer marketing “will decrease by a third as consumers continue to lose trust in brands and entities they don’t personally know.” Marketers should instead “be choosy about influencers,” the research firm advises, and select influencers who “authentically represent the brand’s core values.”
  • Artificial emotional intelligence, or AEI, technologies – driven by audio, computer vision, sensors and phonetic/text analysis — will more widely impact users’ reactions to products and services. By 2023, Gartner predicts, Amazon, Google (Read more...) the other walled gardens will incorporate AEI-detected emotions in the ways they target advertising.
  • And, perhaps most challenging, Gartner predicts that, by 2015, “80 percent of marketers who have invested in personalization will abandon their efforts due to lack of ROI, the perils of customer data management or both.”

That last prediction flies in the face of such assessments as the Association of National Advertisers (ANA)’s selection last week of “personalization” as its marketing word of the year.

Expectations versus cost

In its announcement, ANA provided verbatim comments from some of its members voting for that word. An example: “Personalization is what customers expect. Every current and prospective customer expects that your brand knows them and can deliver what they want.”

The other comments similarly touted marketers’ need and consumers’ desire for personalization. But, Polk said, Gartner’s Magic Quadrant report on the topic has found that 49 percent of marketers buy personalization for ecommerce, where specific purchases can indicate a clear ROI for such expenditures of time and money.

The other 51 percent of personalization expenditure, however, is oriented toward more nebulous results, like customer experience or marketing in general. Instead of personalized offers or recommendations whose results can be shown as purchases, the offerings are personalized content, emails or other methods that are more difficult to measure.

The difficulty in securing reliable ROI for about half of all personalization budgeting, Polk said, is further complicated by the increasing cost of acquiring and managing all the data, from many different sources, that accumulates in a customer data platform or other data-profiling system. These profiles are then used to determine, or infer, what the customer wants.

‘One-to-one marketing’

She noted that the declared end goal of all this data and expenditure is what is called “one-to-one marketing,” a nebulous concept that seeks to provide a unique content and marketing experience for each individual on the planet.

Gartner’s main point is that this goal, with the increasing expenditures and the vague return for at least half of all marketers, cannot be sustained. Additionally, consumers are increasingly wary of making available more personal data, the kind that could help with additional personalization.


The specific figure — 80 percent of marketers will abandon personalization — is an approximation, Polk said, adding that the main point is that personalization needs to be redefined away from one-to-one marketing.

When asked if consumer-generated preference filters could develop as a less expensive, bottom-up filter for personalization, Polk said that kind of development is currently in its infant stages, and it’s not clear if it will be widely adopted.

Preference filters could, for instance, be set by Consumer A to indicate she is interested in buying a new minivan and a new pair of women’s sneakers, so that advertisers could direct related offers and content.

A consumer-driven filter?

Such a filter could reside, for instance, in a consent string that consumers are already generating, such as in the Interactive Advertising Bureau’s framework for privacy consent management, and thus be readily transmitted to the entire advertising and marketing ecosystem.

A consumer-indicated personalization filter could send the trend line for personalization in a different direction, where costs to acquire and manage all that personalization data are largely replaced by consumers specifying what they’re interested in buying or reading, thus pre-qualifying them for those pitches and potentially raising the ROI.

In any case, Polk predicts, marketers are going to see a “flight to quality” in personalization efforts, where more emphasis is put on personalization investment that has tangible results. This might mean, she suggested, more of an orientation toward segment-based personalization instead of the goal of one-to-one, or it might result in other redefinitions, as marketers more realistically address the issues of measurability and scalability.

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