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Gartner for Marketers Hype Cycle for Digital Marketing, 2021 Michael McGuire VP Analyst Leah Leachman Senior Principal Analyst 2Gartner for Marketers Follow Us on LinkedIn Become a Client Hype Cycle for Digital Marketing, 2021 Excerpt of a full research note; available for limited use Michael McGuire VP Analyst Leah Leachman Senior Principal Analyst As markets transition to a post-COVID-19 footing, digital marketing leaders are reemphasizing customer acquisition strategies and encountering new restrictions on customer data use and channel engagement. Use this Gartner Hype Cycle methodology to identify technologies to help you manage uneven market conditions. Published 12 July 2021 ID G00748300 3Gartner for Marketers Follow Us on LinkedIn Become a Client Hype Cycle for Digital Marketing, 2021 Excerpt of a full research note; available for limited use Analysis What You Need to Know As parts of the world emerge from the lockdowns and major disruptions resulting from the COVID-19 pandemic, marketers are moving from pure customer retention strategies to new customer acquisition and growth. The past year saw marketing teams accelerating their digital transformations and working to shield their digital marketing initiatives from budget cuts. A full return to normal is not a given. This uncertainty is underscored by the persistent drumbeat of consumer concerns over how marketers use their personal data. Add to that continued concentration of market power in a few mega-walled gardens (Amazon, Apple, Facebook and Google) each has released a bevy of new policies and platforms with some occasional quick revisions and you have an environment best described as fraught. But the past years required moves toward embracing digital commerce and marketing analytics has given marketers a newfound resiliency they lacked prior to COVID-19. Such resiliency puts a spotlight on many maturing technologies and techniques, such as mobile marketing analytics, multichannel marketing hubs and social analytics. Meanwhile technologies with longer times to plateau (e.g., AI for marketing and personalization engines) will likely remain protected in marketing budgets given their long-term importance and incremental value they will deliver over the midterm. 4Gartner for Marketers Follow Us on LinkedIn Become a Client Hype Cycle for Digital Marketing, 2021 Excerpt of a full research note; available for limited use The Hype Cycle In contrast to the focus on customer retention and market penetration strategies in 2020 and early 2021, the balance of this year and next will feature a greater emphasis on new customer acquisition. Such pressure for immediate growth means that while investment in emerging technologies like AI for marketing continues apace, marketers are also grappling with the challenges associated with these powerful yet immature technologies. Consider the following dynamics: Advanced technologies such as AI for marketing promise transformative capabilities such as personalization of advertising and marketing engagements. Marketing platforms such as multichannel marketing hubs (MMHs), customer data platforms and mobile marketing platforms are integrating AI and machine learning (ML) capabilities. The appetite for such tools only continues to grow as 52% of marketers Gartner surveyed in 2021 were using AI and ML, with another 38% in the planning or piloting stages with AI/ML. However, only 17% have deployed AI across all aspects of their marketing technology stacks. Marketers still struggle to operationalize this emerging technology citing complexity and lack of resources (people and technology), and a certain amount of distrust. Among marketers using AI and ML, 73% find it difficult to trust AI and ML with important decisions. Emerging technologies in the early stages of their journey to maturity influence engineering (making its first appearance on the Hype Cycle for Digital Marketing) and customer data ethics are fueled by a fundamental shift in how marketers acquire and exploit customer data. In particular, consumers, consumer industry groups and government regulators have pushed for greater transparency and consumer control over data collection practices. These include some of the largest tech players in the world. Marketers must find their footing in this new reality. COVID-19 forced marketers to double-down on marketing technology to accelerate incomplete digital transformations. As a result, technologies such as event-triggered marketing, mobile wallet marketing and MMHs progressed more quickly toward maturity. Mobile marketing analytics a profile Gartner expected to see mature and graduate off the Hype Cycle will probably extend for at least another year as the marketers grapple with the practical impact of Apples App Tracking Transparency (ATT) framework on mobile advertising dollars and optimizing campaigns with less data. 5Gartner for Marketers Follow Us on LinkedIn Become a Client Hype Cycle for Digital Marketing, 2021 Excerpt of a full research note; available for limited use Hype Cycle for Digital Marketing, 2021 Source: Gartner (July 2021) 2021 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner and Hype Cycle are registered trademarks of Gartner, Inc. and its affiliates in the U.S. Expectations Innovation Trigger Peak of Inf.shortlated Expectations Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Time As of July 2021 Plateau will be reached: 2 to 5 years 5 to 10 yearsless than 2 years obsolete before plateaumore than 10 years Expectations Inf.shortluence Engineering Customer Data Ethics Visual Search for Marketing Customer Journey Analytics Real-time Marketing Consent and Preference Management Personif.shortication Conversational Marketing Shoppable Media Customer Data Platform AI for Marketing Multitouch Attribution Identity Resolution Location Intelligence for Marketing ABM Platforms Inf.shortluencer and Advocacy Marketing Mobile Wallet Marketing Personalization Engines Event-Triggered Marketing Mobile Marketing Analytics Social Analytics Multichannel Marketing Hubs 6Gartner for Marketers Follow Us on LinkedIn Become a Client Hype Cycle for Digital Marketing, 2021 Excerpt of a full research note; available for limited use The Priority Matrix The overall trends in this years Hype Cycle noted in the previous section are reflected in the Priority Matrix below. With marketers showing a preference for martech stacks based on integrated suites (instead of an amalgam of best-of- breed providers), MMHs are moving toward the Plateau of Productivity Meanwhile, mobile marketing analytics expected to graduate off the Hype Cycle this year remains on the Slope of Enlightenment due to Apples deprecation of its Identifier for Advertisers (IDFA) and the introduction of ATT. These moves potentially eliminate a significant amount of app-behavior data and cause marketers to continuously reevaluate how to leverage supporting technology. Ultimately, with the increased visibility among consumers of how their data is used, marketers must rethink their marketing strategies. Given consumer concern about marketers exploitation of their data and the adoption of machine learning in marketing automation, marketers need to be conscious of the ethical implications of their engagement strategies. These developments pushed customer data ethics toward the Peak of Inated Expectations, showing that marketers must prioritize articulating and demonstrating an ethical framework that guides use of customer data. Similarly, inuence engineering enters this years Hype Cycle for the rst time as marketers pursue more strategic, market- shaping growth goals and look to get more out of their AI investments. The disruption of in-store shopping brought by COVID-19 propelled mobile wallet marketing and shoppable media along their Hype Cycle journeys. 7Gartner for Marketers Follow Us on LinkedIn Become a Client Hype Cycle for Digital Marketing, 2021 Excerpt of a full research note; available for limited use Table 1: Priority Matrix for Digital Marketing, 2021 Source: Gartner (July 2021) Benefit Years to Mainstream Adoption Less Than 2 Years 2 5 Years 5 10 Years More Than 10 Years Transformational AI for Marketing Influence Engineering Real-Time Marketing High Multichannel Marketing Hubs ABM Platforms Customer Journey Analytics Event-Triggered Marketing Identity Resolution Mobile Marketing Analytics Shoppable Media Visual Search for Marketing Customer Data Ethics Personalization Engines Personification Moderate Influencer and Advocacy Marketing Social Analytics Consent and Preference Management Conversational Marketing Customer Data Platform Location Intelligence for Marketing Mobile Wallet Marketing Multitouch Attribution Low 8Gartner for Marketers Follow Us on LinkedIn Become a Client Hype Cycle for Digital Marketing, 2021 Excerpt of a full research note; available for limited use Influence Engineering Analysis By: Andrew Frank Benefit Rating: Transformational Market Penetration: Less than 1% of target audience Maturity: Embryonic Definition Inuence engineering (IE) refers to the production of algorithms designed to automate elements of digital experience that guide user choices at scale by learning and applying techniques of behavioral science. Why This Is Important The abundance of data sources and machine learning capabilities enables new systems of inuence. Though still largely theoretical, breakthroughs in areas such as emotion detection and language generation show clear potential to automate inuential aspects of communication. Examples have shown how AI can amplify bias and other harmful effects, yet benecial goals may accelerate positive social change. This suggests a need for new forms of governance to oversee IE research and deployments. Business Impact Alongside protable growth, businesses face growing demands to deliver on environmental and social goals, responsibly and transparently. The success of transformative initiatives needed to address these demands depends on market adoption. As IE techniques mature, their power to shape opinions and choices will increase to the benet or detriment of these transformations. The long-term health of enterprises is thus impacted by their ability to wield these tools effectively in benecial ways. Drivers Evidence of AIs power in marketing: Investments and breakthroughs in AI from global platform providers (such as Google, Apple, Facebook and Amazon) and martech vendors (such as Adobe, Salesforce and Oracle) remove barriers to AI adoption in marketing. The emergence of technologies such as deepfakes and chatbots illustrate AIs ability to synthesize lifelike experiences. Academic work conrms the applicability of machine learning in experiments on inuence. Use of AI is strongly associated with marketing automation, recommendations and personalized digital experience, all high-priority initiatives in marketing, commerce and communication. 9Gartner for Marketers Follow Us on LinkedIn Become a Client Hype Cycle for Digital Marketing, 2021 Excerpt of a full research note; available for limited use Commercial goals: Pressure is mounting on marketing organizations to deliver better results with lower costs and the loss of key data sources such as browser cookies. The shift of consumer behavior toward digital channels for work and commerce creates more opportunity for automated experience elements. Social goals: Pressure is also mounting on corporations to explicitly address societal impacts, as expressed in investors environmental, social and corporate governance (ESG) ratings by nudging consumer choices toward more sustainable and equitable lifestyles. Social fractures create widespread desire to nd common ground and unify digital society in ways beyond the capabilities and scope of regulation. Obstacles Widespread popular condemnation of manipulative technologies is evident, for example, in the recent backlash against Spotifys patent on vocal emotion detection and in popular exposs such as “The Social Dilemma” and “The Great Hack.” The deprecation of popular personal data collection mechanisms such as browser cookies and mobile device IDs that provide behavioral datasets used to train personalization algorithms creates the need to establish new sources of training data. continued on next page Government action is increasing, including: restrictions on use of personal data and unexplained proling; oversight of AIs role in propagating bias and discrimination. There is a lack of established approaches or tools. The market is characterized by divergent approaches and conflicting claims as investors and entrepreneurs seek to exploit a building wave of hype. General skepticism is common, as the actual potential of these technologies remains speculative and many experts question assumptions of viability. User Recommendations Establish or locate the governance structure within your organization where the opportunities for IE are best investigated. Discover use cases and debate the goals and extent of potential commitments. Assure broad, cross-functional representation and ethics committee participation. Assure that statements of purpose are translated into measurable goals used to train machine learning algorithms involved in IE. Recruit friendly user test groups for research and experimental projects. Be transparent about goals and technologies. Be aware when research activities require advance informed consent. 10Gartner for Marketers Follow Us on LinkedIn Become a Client Hype Cycle for Digital Marketing, 2021 Excerpt of a full research note; available for limited use Embed longer-term business metrics in operational dashboards and monitoring processes used to measure and motivate performance. Make opinion sampling and goodwill measurement regular features of your organizations health check. Build your organizations knowledge center for IE, and include organizational learning, assessment of competitors and platform providers activities. 11Gartner for Marketers Follow Us on LinkedIn Become a Client Hype Cycle for Digital Marketing, 2021 Excerpt of a full research note; available for limited use Customer Data Ethics Analysis By: Andrew Frank, Michael McGuire Benefit Rating: High Market Penetration: 1% to 5% of target audience Maturity: Emerging Definition Customer data ethics aligns business practices with moral and ethical policies that reflect a companys avowed values. The need for a customer data ethics platform arises from the often unintended social and environmental consequences of using customer data with the singular goal of maximizing profits. Why This Is Important Adoption of machine learning techniques in marketing automation and personalization is on the rise. So is


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