Top 5 Trends Drive Gartner Hype Cycle for Digital Marketing, 2020

September 1, 2020
Contributor: Gloria Omale

The Gartner Hype Cycle highlights digital marketing technologies that have the capability to transform how marketers respond to changing conditions.

Personalization can sometimes feel creepy, and we all know that creepy crosses the line. But what do consumers think about privacy and consent when it comes to their data?

In 2017, Netflix came under fire on Twitter for tweeting that it knew exactly who was watching what and when. While the tweet was intended to be lighthearted and funny, many users said it came across as creepy, kicking off a debate about digital marketing and the use of customer data. Privacy made headlines again in 2018 when news broke that consulting firm Cambridge Analytica had gained access to Facebook user data, compromising the privacy of tens of millions of users.

This incident and many others publicized in the media have caused an uptick in consumer concern about how organizations collect and use customer data to drive personalized engagements. 

“Marketers and their brands have responded by establishing ethical frameworks for how they use customer data,” says Mike McGuire, VP Analyst, Gartner. “Over the next five to 10 years, we’ll see demand for the ethical treatment of customer data intensify as consumer trust decreases.”

Not surprisingly, customer data ethics makes its first appearance on the Gartner Hype Cycle for Digital Marketing, 2020. Among the 21 marketing technologies on the Hype Cycle, it is one of five technologies that are of high importance to marketing leaders. The others are: 

  • Real-time marketing

  • Artificial intelligence (AI) for marketing

  • Personalization engines

  • Location intelligence

Customer data ethics

The need for customer data ethics arises from two factors: 

  • Concentrated market power of a few digital tech giants controlling massive amounts of customer data

  • Consumers’ deep-seated concerns about how their data is collected and used

Focusing on customer data ethics doesn’t mean marketers need to stop collecting data or avoid advanced analytics or use of AI. It is best viewed as a progression that starts with merely being compliant, moves to reducing risks and ends up where trust becomes more than a word used in advertising slogans. 

Customer trust will grow if marketers talk about customer data ethics and demonstrate, in transparent ways, their commitment to be more than legally compliant.

Real-time marketing

Real-time marketing describes an organization’s ability to interpret and respond to opportunities within time frames that provide business advantage by using tools, technologies and processes that capture, monitor, analyze and act on information in real time. Companies that adopt real-time marketing tools and techniques across their larger value chain will outperform competitors in operations and their ability to deliver more rapid, relevant offers to customers. 

Organizations honing skills in real-time marketing are already using rapid response to take share from primary competitors. Large organizations stuck in older, slower ways of doing things due to rigid hierarchies or business processes are particularly vulnerable to competition from agile organizations that use speed to respond faster to customer demands across multiple life cycle stages.

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Review Gartner Hype Cycles for Digital Marketing and Advertising, 2020

AI for marketing

AI for marketing includes systems that change behaviors without being explicitly programmed, and are based on data collected, usage analysis and other observations. The benefit to marketing includes faster, more accurate, and more actionable insight generation and prediction. 

AI techniques are already finding their way into multiple marketing systems. However, AI for marketing presents a long, steep learning curve in which marketers must overcome multiple challenges — including data availability and team skills gaps — before mastering.

Read more: How AI Will Drive Transformative Change in Marketing

Personalization engines

Personalization engines are commonly used by marketing, digital commerce, merchandising and customer experience teams to optimize content and campaigns, commerce experiences and recommendations. They can also be used for interactions across customer touchpoints like call centers, chat and digital kiosks. Brands and retailers newer to personalization should pilot personalization using existing resources (data, talent, technology, content) to prove results and justify budget.

Learn more: Answers to pressing questions on personalization

Location intelligence

Location intelligence for marketing enables marketing leaders to manage and make available correct information about the physical locations under their control to search engines, app publishers, review sites and other social media. Location intelligence also includes technologies that enable marketers to assemble consumers’ location histories (typically via mobile apps) to refine customers’ profiles to deliver more relevant engagements or offers. 

Despite its potential, the promise of location intelligence is hampered by the tension between consumers and brands over how consumers’ location data is used. Gartner recommends that marketers ensure their organization’s data collection policies for customer location comply with appropriate regulation, such as the California Consumer Privacy Act (CCPA) and the EU’s General Data Protection Regulation (GDPR).

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