1、12024Digital Trends23454810161116128131819Executive SummarySection 1 Personalization and customer journey expectations.Why are we still talking about personalization?What personalization means in 2024.Section 2 Unified data and insights are foundational for personalization.Connect your data for seam

2、less,personalized journeys.From compliance to competitive edge.Market leaders exemplify responsible data practices.Section 3 Clear starting points and future goals for generative AI.Generative AIs first use case is content.Internal strategies for adopting generative AI.From pilots to powerhouse.Reco

3、mmendations Exceptional digital CX through personalization,generative AI,and unified data.MethodologyExecutive survey.Consumer survey.Table of contentsAdobe 2024 Digital Trends3Adobe Digital Trends has,over the past 14 years,brought readers up to date with executives views on how their organizations

4、 perform in the face of change.For the first time,we have added an extensive consumer survey to uncover what customers really think about innovations in digital experiences.In this report,well define what personalization means in 2024 and how unified data lays the foundation for organizations not on

5、ly to effectively personalize but also leverage generative AI to its fullest potential.Lastly,well explore the actual impact of generative AI on customer experience(CX)today,and how organizations can deliver on its promise.Key Learnings:Consumer experiences are still not meeting expectations.Consume

6、rs feel companies have the potential to address their needs more closely,but many digital experiences have yet to live up to expectations.Consumers point to the fact that businesses hold enough of their data to provide better products and services but arent making the most of it.Personalization is o

7、ften based on assumptions,not evidence.Organizations often focus on personalizing individual contact points rather than creating what customers wantconsistent,seamless interactions across different channels and throughout the entire customer journey.These assumptions are based on outdated informatio

8、n and habits.Companies still arent connecting the data dots.Unifying data is just one piece of the puzzle to deliver exceptional digital CX,but organizations still struggle to get it right.Once properly implemented,unified data will be the foundation for organizations to build next-generation experi

9、ences,including AI-powered ones.Generative AI strategy needs more attention.The perception is that generative AI will quickly scale a newly efficient business.The reality is that while success is within reach,businesses must improve underlying data to make the most of AI.Market-leading organizations

10、 have done the work on data,goals,and strategy.Market Leaders can accelerate their ability to use generative AI because they are more likely to have sophisticated data strategies.Early Adoptersthose who already have generative AI solutions in placeare six times more likely than those without generat

11、ive AI solutions to have exceptional digital CX.AIs potential is unrealized but achievable.As firms integrate generative AI into their business workflows,its potential for far-reaching business impact is becoming clearer.However,the fact that so many have yet to establish business goals or KPIs show

12、s a lack of focus and means that generative AIs potential is still far from being reached.Executive Summary4Section 1 Personalization and customer journey expectations.Why are we still talking about personalization?Personalization continues to be a top business priorityand organizations still strugg

13、le to get it right.According to this years consumer survey,just 26%of consumers described their digital experience with a brand they have an existing relationship with as“excellent.”About half of the consumers surveyed agree that“the more brands know about me,the better service they can give.”At the

14、 same time,nearly two-thirds express frustration“with brands that know a lot about me but dont take my preferences into account”(Figure 1).Organizations continue to demand more and more data,but consumers are wary,in part because of the limited personalization they have received after sharing their

15、data in the past,along with general privacy concerns.This suggests consumers would rather brands get their core interactions right across website,email,app,and social before expanding to interactions such as automated chat or virtual try-ons.Figure 1:To what extent do you agree with each of the foll

16、owing statements?(Consumer)80%71%67%65%60%49%Its important to me to know if I am talking to a human or a botI expect my experience with brands to be seamless across their website,app,and call centerI would be more open to granting permission to use my data if brands were more transparent about how t

17、hey were using and securing itI am worried about how much data brands hold about meI get frustrated with brands that know a lot about me but dont take my preferences into accountThe more brands know about me,the better service they can give meSample size:6,793 5What personalization means in 2024.In

18、2024,world-class digital experiences require a personalized end-to-end customer journey across all channels,delivered seamlessly and consistently.It is not a series of customized touchpoints.Four-fifths(80%)of consumers consider consistent experiences across different online channels“important”or“cr

19、itical”to meeting their CX expectations,and 70%assign similar ratings to“personalized product recommendations”(Figure 2).However,above all else,consumers want their data used responsibly,with 91%insisting it is either“important”(28%)or“critically important”(63%).Respondents were significantly more l

20、ikely to rate this as critical to meeting their CX expectations than any other option.When asked what consumers value more when interacting with brands,results revealed most prefer communications on their own schedule.Almost two-thirds(60%)said they would prefer to receive an email on top offers ove

21、r a personalized text message(40%).Similarly,consumers preferred recommendations via website and in-app(62%)to tailored emails and texts(38%).Cross comparisons on app versus website,chat versus forms,and other preferences were almost equally split,suggesting there is no one right path for most custo

22、mers (Figure 3).Figure 2:When interacting with brands generally,how important are each of the following to meeting your customer experience expectations?(Consumer)Critically importantSomewhat importantImportantNot at all important26%44%21%9%34%46%15%36%41%16%7%28%44%19%8%63%28%7%Personalized product

23、 recommendations based on my interests and past purchasesConsistent and seamless interactions across different online channels(website,social media,email)Quick and efficient customer support through automated systems like chatbotsTools and features to make my online experience better,like virtual tr

24、y-ons or interactive product demonstrationsAssurance that my personal data is being used responsibly and securely by the brandSample size:6,489Real-time personalization is what our customers expect every single time,every single interaction.We must get that right and do it so youre not coming across

25、 as creepy or trying to sell something the customer doesnt need.Youre coming across as a partner who genuinely cares for their customers and wants the best for them.”Parthiv Sheth Vice President of Marketing,AT&T 6Figure 3:When choosing between different brands to do business with,which of the follo

26、wing are more important to you?(Consumer)62%38%56%44%49%51%49%51%49%51%60%40%Marketing emails and texts with offers tailored for meText messages with offers personalized for meRecommendations based on my profile,e.g.age and genderA well-designed appOnline chat with a virtual assistantOnline chat wit

27、h an agentGreat product recommendations in-app or on the websiteEmails with top offers of the dayRecommendations based on recent purchasesA comprehensive websiteA form for questions and inquiriesA number to callSample size:6,793Drilling further into the data,we uncovered preferences by consumer age

28、groups,revealing some interesting generational differences.For example,most consumers under 45 prefer online chat to calling or completing a form,while most consumers over 65 prefer websites to apps(Figure 4).Brands need to realize that,as some segments“age out,”the preferences of todays younger con

29、sumers will then become the dominant expectation.Only consumer segmentation with detailed insight behind it is going to get businesses closer to meeting expectations.For instance,consumers valued tailored messages that are timely and relevant among their top three priorities in personalization(Figur

30、e 5).At the same time,only 20%of consumers valued being addressed by name.Having their information and preferences recognized when reaching out for support or customer services is more important(23%),as is being recognized when they log in on different devices(25%).Figure 4:When choosing between dif

31、ferent brands to do business with,which of the following are more important to you?(Consumer)b)Online chat with a virtual assistant versus a form for questionsc)A well-designed app versus a comprehensive website60%56%58%51%51%64%36%49%42%44%40%18-2425-3435-4445-5455-6465 and older49%A well-designed

32、appA comprehensive website61%39%62%38%61%39%51%49%58%42%69%31%18-2425-3435-4445-5455-6465 and olderOnline chat with a virtual assistantA form for questions and inquiriesSample size:6,793a)Online chat with agent versus a number to call18-2425-3435-4445-5455-6465 and olderOnline chat with an agentA nu

33、mber to call43%57%60%58%52%57%64%40%42%48%43%36%7There is evidence brands need to pay closer attention to what consumers are telling them.While 40%of practitioners align with consumers in prioritizing recommendations,they also prioritize addressing customers by name(40%,Figure 6),which as weve seen

34、was significantly less a priority for consumers(20%,Figure 5).Positively,practitioners routinely use data and analytics to predict consumer needs by segment(47%),which indicates they are able to take different approaches to communication preferences.By interpreting buying behaviors and browsing habi

35、ts,practitioners can focus on their audiences true needs and preferences with the goal of enhancing the customer journey rather than chasing after every data point.Figure 5:Personalization that consumers value the most from brands(top 3).(Consumer)Sends timely reminders by text or email about produc

36、ts or services I might be interested inRecognizes me on all my devices when I log onto its website or appAddresses me by name in all digital communicationsSends messages and offers that feel tailored to meGives recommendations based on my latest browsing history and/or purchasesRecognizes and respon

37、ds to my most recent purchases or browsing history in their communicationsSends me offers and messages that seem to fit my age,gender,and lifestyleRecognizes my information and preferences when Im making a return or reaching out for support or customer serviceShows ads on social media that are relev

38、ant to my interests and needsSample size:6,55631%30%28%25%24%23%20%19%16%Figure 6:The ways that practitioners say they routinely personalize digital content for customers.47%40%40%36%27%25%23%We use data and analytics to predict customer needs by segmentWe use data and algorithms to personalize the

39、website experienceWe use generative AI to personalizeimages,infographics,or video contentWe make recommendations based on previous purchase and browsing behaviorOffers are updated in real time to reflect most recent browsing and purchase behaviorCustomers are addressed by nameWe use generative AI to

40、 craft emails,messages,and other copySample size:3,1978Indeed,the link between strong data practices and routine personalization efforts is demonstrated in our research.As illustrated in Figure 7,practitioners rating their customer data system(CDS)as“highly effective”are more likely to routinely per

41、sonalize across channelswith recommendations,in real time,using generative AI crafted contentcompared to those rating their CDS as“moderately/ineffective.”Section 2 Unified data and insights are foundational for personalization.Connect your data for seamless,personalized journeys.Data sophistication

42、 is vital to effective personalization.Without the data capabilities to make intelligent product recommendations or route the customer to the most effective customer service journey,digital touchpoints cannot fulfill their promise.Take the chatbot experience,for example.Chatbots are dependent on int

43、elligent data and mostly used for service or to help the customer self-direct their purchasing journey.Yet,they are also the most likely to disappoint.About half of consumers(49%)rate their experiences with chatbots as either“very poor,”“poor,”or just plain“adequate.”Figure 7:Aspects of digital cont

44、ent that practitioners say they are routinely personalizing versus the effectiveness of their organizations customer data systems.Sample size:1,700Highly EffectiveModerately/Ineffective65%54%54%53%60%41%47%27%41%23%40%29%We use data and analytics to predict customer needs by segmentWe use data and a

45、lgorithms to personalize the website experienceWe make recommendations based on previous purchase and browsing behaviorOffers are updated in real time to reflect most recent browsing behaviorWe use generative AI to personalize images,infographics,or video contentWe use generative AI to craft emails,

46、messages and other copyHenkel AG&Co.,the German multinational chemical and consumer goods company,has enhanced its operations with the new digital platform RAQN,powered by Adobe Experience Platform.This technology is transforming how the company manages its 30+brands,enabling tailored experiences ac

47、ross channels.With cloud-based tools for content,customer data,and assets,Henkel has streamlined 300 web domains,facilitating personalized engagement for B2B,B2C,and B2B2C interactions.Learn More CASE STUDY9When asked what improvements a brand could make to provide a better digital experience,consum

48、ers named improving customer service transfers(52%)or making self-service support easier(44%)as the top two.To achieve this,a smooth flow of data between departments and systems is critical.An organizations data-related capability also correlates with market performance.Figure 8 shows that Market Le

49、aders(those who outperformed their sector peers in 2023)are more likely to rate their data-related capabilities as“best-in-class or“above average”across all five measures of functionality versus Market Followers(those who merely kept pace or underperformed their sector in 2023).Many organizations re

50、cognize that their data strategies are still very much“in development.”This is echoed by practitioners,who rated their customer data systems as merely“average”to“ineffective”in providing consistent data across all touchpoints(52%)and enabling a holistic customer view(57%).More than half of senior ex

51、ecutives(55%)identified“customer data management”as the top technology area they prioritize for investment in 2024.Such tools theyve prioritized on unifying data into a single source of truth that can be accessedsubject to the right permissionsfor a number of purposes,including data security and com

52、pliance,customer service,marketing,and product development.Increasingly,analysts suggest the most popular format for unifying data is the customer data platform,or CDP.*These data platforms unify,segment,and activate data for all the necessary systems and stakeholders required,giving the organizatio

53、n a single source of truth for customer data to help create seamless,personalized journeys.Figure 8:Senior executives rating their data-related capabilities as“best in class”or“above average.”Market Leaders vs.Market Followers Market LeadersMarket Followers75%45%75%48%71%42%43%46%71%72%Sample size:1

54、,243Real-time data capture and consolidationInsight generation and predictive analysisOmnichannel content personalizationCustomer journey orchestrationMeasuring CX impact and ROIUnderstanding customers is a challenge for consumer packaged goods companies(CPGs)because they rarely sell directly to the

55、 customer.As a result,they have to make the most of the data they can acquire.Coca-Cola does this by bringing together its regional CDPs to create a single view that gives real-time insights into global customers.In just the first phase of deploying Adobe Real-Time Customer Data Platform and Adobe J

56、ourney Optimizer,Coca-Cola brought together 98 million customer profiles from more than 100 countries,with plans for billions of profiles in the future,allowing the company to target consumers by drink preference,lifestyle,location,and more.Learn More CASE STUDY*Forrester,The Customer Data Platforms

57、 For B2C Landscape,Q1 2024,202410From compliance to competitive edge.Confidence in data compliance underpins organizations willingness to explore new technology solutions and digital strategies to keep innovating.Technology will inevitably encourage that exploratory thinking,and data will fuel that

58、technology.To make the most of the data and technology equation,organizations must be confident they are protecting both themselves and their customers data.Perhaps surprisingly,despite their concerns over data privacy,consumers are broadly comfortable with brands using AI,particularly if it would l

59、ead to brands making better recommendations and improving communications(Figure 9).However,consumers do still have some concerns.Around one-third are uncomfortable giving customer service employees access to their data(34%),which could impact organizations efforts to improve automated self-service,a

60、 noted priority for brands and consumers.Moving forward,brands will need to be diligent in adopting more transparency around data policies.That means providing clear consent options and explaining how and where data is used,particularly when it comes to AI.Organizations recognize this is easier said

61、 than done.More than half(57%)of practitioners say ensuring quality and customer trust in AI-generated content will be a top challenge in 2024,while 38%of organizations with generative AI solutions in place also agree that“building trust by embedding responsible data and AI practices”will have a big

62、 impact on their businesses.Figure 9:How comfortable are you with the brands you deal with using AI for each of the following purposes?(Consumer)Making better suggestions for products and services I might be interested inMaking better recommendations in-appImproving relevance of emails and marketing

63、 messages they send to meMaking chatbots more helpfulGiving customer service employees access to my purchase history without having to go through security checksUsing AI-generated images to make marketing messages more engaging32%34%23%17%17%16%41%38%42%47%47%48%27%28%35%36%36%37%Sample size:6,532No

64、t comfortableFairly comfortableVery comfortable11Market leaders exemplify responsible data practices.When it comes to using customer data to power new technology like generative AI,Market Leaders are pulling ahead of Market Followers in terms of having effective customer data systems to ensure data

65、privacy,develop content responsibly,and meet security standards and brand requirements.In fact,Leaders are twice as likely to agree their progress in guaranteeing data privacy and security standards is already done(37%vs.17%).Conversely,41%of Followers say they have either“not started/have no plans

66、to start”or are just at the“planning stage,”compared to only 19%of Leaders(Figure 10).When using generative AI for content creation and distribution,Market Leaders are ahead of Market Followers in ensuring brand safety and legal compliance(78%vs.63%).There is an even bigger gap between Market Leader

67、s and Followers when it comes to having the data needed to develop AI content responsibly(75%vs.50%)(Figure 11).By getting their data house in order first,Market Leaders are laying the critical groundwork to leverage generative AI capabilities for content creation,customer support,and more in a secu

68、re,responsible manner.Figure 10:Senior executives rating their progress in“Ensuring data privacy and security standards as they pertain to AI.”Market Leaders vs.Market Followers Already done/fine tuningWork in progressPlanningYet to start/no plans37%44%13%6%17%41%26%15%Market LeadersMarketFollowersS

69、ample size:1,196Figure 11:Practitioners agreement with statements related to their plans to use generative AI for content creation and distribution.Market Leaders vs.Market Followers Market LeadersMarket FollowersWe have the tools to create high-quality AI contentWe are confident customers will be h

70、appy to engage with AI contentWell be able to ensure brand safety and legal complianceWe have the right organizational culture to work on cross-functional AI initiativesOur organization sees clear benefits in using AI for content creationWe have the data we need to develop AI content73%75%78%75%80%6

71、2%63%49%50%75%47%52%Sample size:1,58912Section 3 Clear starting points and future goals for generative AI.Generative AI presents many ways to improve CX and drive business transformation.However,our survey shows that most organizations havent yet connected generative AI to larger transformation or C

72、X goals.Only about one-quarter of senior executives have done so,but encouragingly,45%are working toward it(Figure 12).Around two-thirds of senior executives are optimistic that generative AI will deliver significant or major business transformation across the board,from data analytics and customer

73、service to webpage optimization,email marketing,and content workflows(Figure 13).However,given that less than one-quarter have a roadmap and only one-quarter have identified KPIs(Figure 12),theres a risk that their generative AI deployments may not live up to expectations without more strategic over

74、sight.Figure 12:Senior executives readiness for generative AI across specific organizational areas.Already done/fine tuningWork in progressPlanningYet to start/no plans24%45%20%11%Aligning a comprehensive AI roadmap with broader business goals25%44%21%10%Conducting skill-building programs centered o

75、n AI25%44%21%10%Identifying KPIs to assess AI impactSample size:2,175Qualcomm,a multinational company with expertise in telecom and semiconductors,has developed an integrated approach to engaging its business customers.They connected customer data across channels and experiences so marketers may per

76、sonalize at every point of the journey for complex B2B needs.Whether a journey begins at a website and ends in a trade show,or whether the customer is from the automotive or mobile sectors,Qualcomm can use AI and advanced data sharing capabilities to tailor real-time personalization to each lead.Lea

77、rn More CASE STUDY13Generative AIs first use case is content.Its time to marry executives aspirations with pragmatic business cases and consumer needs.Practitioners who have either already adopted or are in the process of implementing generative AI capabilities were asked to identify the areas where

78、 their organizations will use it in digital marketing and experience management.The top answer is content.Both automating content creation and personalizing content are top use cases(Figure 14).Figure 13:Senior executives assessment of the degree that generative AI will transform their organizations

79、 current operations.11%26%37%23%23%40%28%8%26%38%25%9%27%39%24%9%26%36%24%12%28%38%23%10%28%38%22%11%26%40%22%10%Data analytics and management(e.g.,handling,reporting)Customer service operations(e.g.,support channels,engagement methods)Email marketingContent workflows(e.g.,creation,editing,distribut

80、ion,archiving)Insights gathering and sharing(e.g.,market research,customer feedback)Sales processes(e.g.,tactics,CRM usage)Webpage creation/optimizationCustomer journey management21-No significant change345-Major transformationSample size:2,084Figure 14:Top areas where practitioners who have either

81、adopted or are implementing generative AI capabilities plan to use it in digital and marketing experience management.Sample size:1,05141%41%39%36%32%30%28%27%Automating parts of content creation such as creative,articles,social posts,landing pagesOptimizing campaign performance through testing and a

82、nalysisAutomating email and SMS campaignsResizing and adapting content for different platforms and devicesPersonalizing content based on customer interests and preferencesImproving content tagging and data qualityOffering automated chatbot or messaging supportAutomating audience segmentation and tar

83、geting14To accelerate their customer experience initiatives,practitioners are prioritizing effective use of generative AI in organizing,streamlining,and improving creative production efficiency(41%,Figure 15).But 38%also recognize its potential to help customers self-servea key consumer request from

84、 our surveyand to understand more about their customers journeys(38%).On the other hand,consumers said that beyond data security,their key needs are seamless customer service(Figure 2)and efficient customer support via chatbots.For example,77%of consumers said,“quick and efficient customer support t

85、hrough automated systems like chatbots is important or critical,”and 51%would rather chat online with an agent than call(Figure 3).It follows that organizations should focus their efforts on improving the chatbot experience,however,the foundational workunifying customer datamust first be in place fo

86、r automated tools like chatbots to accurately customize interactions.Organizations generative AI objectives must ultimately be set to solve both internal business goals and customer pain points.While it may take significant time and resources to fully achieve those aims,its possible to enjoy some fa

87、ster success that can put the business on the path to greater efficiency and lay the foundations for deeper investment going forward.Based on the survey results from practitioners,streamlining content workflows(41%,Figure 15)and personalizing content(41%,Figure 14)emerge as pragmatic starting points

88、 for many.This approach yields tangible financial benefits for businesses in a relatively short period and minimizes disruption to their existing infrastructure.Figure 15:Practitioners intentions to deploy generative AI in 2024 for accelerating and enhancing marketing and customer experience initiat

89、ives.41%38%38%36%31%Streamlining creative workflows and asset productionOptimizing customer journeys by integrating new data sourcesEnhancing self-service portals for better customer experienceUpdating content in real time to stay relevantImproving campaign iteration with continuous testingSample si

90、ze:2,627Its not as simple as just hooking up to the internet and putting whatever comes back in front of customers.It has to be thoughtfully done.But I absolutely think generative AI can help us in ecommerce,marketing,and software development.Theres a lot of opportunity,but its a marathon,not a spri

91、nt.”Jordan Broggi Senior Vice President&President Online,Home Depot15When we asked senior executives about the primary methods they are employing to enhance workflow efficiency and reduce costs in 2024,52%identified“automating manual tasks through the use of content AI and chatbots”as their top sele

92、ction.Automating manual tasks can deliver substantial cost savings when inputting standardized information into a generative AI tool.Examples include adapting existing content for different audiences,products,and regions,or idea generation or concepting for skilled employees to finalize creative ass

93、ets(Figure 16).Figure 16 also shows where there is an opportunity for organizations looking for a competitive advantage to take the lead.Interestingly,50%of practitioners currently admit implementation for auto-updated content,such as price information,isnt in the plan until 2025,if at all.Yet,using

94、 generative AI to perform this task is one of the more reliable and straightforward use cases.Internal strategies for adopting generative AI.We categorized practitioners into two main groups based on their responses:those who are currently using generative AI,referred to as Early Adopters(Figure 17)

95、,and those who indicated Figure 16:Current and expected use of generative AI in content production and workflows.(Practitioners view)32%19%22%27%31%20%25%23%34%21%23%23%29%20%30%21%27%22%32%18%Idea creation and concepting for skilled employees to finalizeGenerative inputs for content components to h

96、elp complete an employee-designed assetAdapting existing content for different audiences,products,regionsAuto-updating live content,(e.g.,prices,product specs)End-to-end production,from inception to executionIn use todayBy end of 20242025 or laterNo current plansSample size:2,553Figure 17:Rate of ad

97、option of generative AI in content production and workflows versus practitioners perceptions of their digital experience.Note:Respondents were asked to state when they planned to use generative AI in different areas of content production.Using their responses to this question,we grouped them into th

98、ree segments:Currently use(Early Adopters),later in 2024(Fast Followers),and 2025 and beyond(Late Movers).Weve focused on comparisons between Early Adopters and Late Movers for the analysis.Our digital CX is exceptional and can surprise and delight the customerOur digital customer experience meets c

99、ustomers needsOur digital customer experience sometimes lags our customers needsOur digital experience consistently falls below customer needs36%52%8%6%41%38%Early AdoptersLate MoversSample size:2,55116implementation by“2025”or expressed“no current plans,”referred to as Late Movers.Early Adopters ar

100、e six times more likely than Late Movers to report that their digital experience is exceptional,demonstrating that generative AI adoption is correlated with brands delivering superior CX.Successful businesses boast another characteristic that allows them to maximize the benefits of this technologyth

101、eir corporate culture.As illustrated in Figure 18,organizations currently using AI solutions are three and a half times more likely than organizations with no formal strategy to agree they have a culture fit to work on cross-functional AI initiatives (88%versus 25%).What does that look like?Companie

102、s have identified their top priority as providing advanced AI skills to key team members(48%,Figure 19).Of course,eventually all staff within an organization could be interacting with AI to a greater or lesser extent.Understandably,an almost equal priority is ensuring all employees have a basic unde

103、rstanding of AI(46%).It might seem concerning that just 38%cited creating interdisciplinary teams as important.Weve already seen that effective generative AI implementation involves input from business leaders,marketers,customer service operatives,data analysts,strategists,and more.AI implementation

104、 cannot be stuck in silos.With 24%of senior executives either done with or fine tuning their AI roadmap around broader business goals and 45%still in progress(Figure 12),interdisciplinary teams will be essential to delivering on the promise of generative AI.However,there are positive signals that or

105、ganizations are moving in the right direction.From pilots to powerhouse.Without clear goals,integrated teams,or leadership support,its no surprise that most organizations are still in the pilot phase with generative AI.For example,less than half of practitioners(45%,Figure 16)currently use or plan t

106、o use generative AI in end-to-end content production by the end of 2024 because Figure 18:Organizations agreement(agree or strongly agree)to having an organizational culture to work on cross-functional AI initiatives by level of generative AI adoption.25%59%72%78%88%No formal adoption strategyConduc

107、ting enterprise-wide assessment of if/where to deployIdentifying use cases and evaluating vendorsImplementing initial solutions,including pilot projectsHave solutions in place and evaluating effectivenessSample size:Agree(2,323)and Strongly Agree(596)Figure 19:Senior executives top priorities for pr

108、eparing for generative AI in 2024.Advanced AI skills training for key staffDeveloping and implementing AI governance frameworksBasic AI understanding for all employeesModifying existing workflows for AI Creating policies for ethical AI use and data securityCreating interdisciplinary teams for AI 48%

109、46%45%44%41%38%Sample size 2,10617this would require a degree of systems and workflow integration to work smoothly.As stated earlier,we shouldnt be worried that only 38%of senior executives felt creating interdisciplinary teams was a top priority.Put in the context of Figure 20,it turns out that 70%

110、of senior executives are establishing cross-functional teams for rapid AI project rollout by the end of this year,with 70%also reorganizing their teams and functions.With these two elements in place,those organizations will be in a strong position to move from pilots to long-term generative AI-drive

111、n strategies.Indeed,senior executives at organizations with generative AI solutions already in place(Mainstreamers)show a path toward broader rollouts more so than those at organizations just starting to implement initial solutions(Piloters).Leadership.Organizationally,Mainstreamers are making strid

112、es compared to Piloters,with the former more than twice as likely to introduce AI leadership roles by the middle of 2024(44%vs.32%).They are also reorganizing team functions at a similar rate(40%vs.29%).Data.Responsible data use is imperative for organizations and consumers.Mainstreamers are twice a

113、s likely as Piloters to state that they have ensured privacy and security standards pertaining to AI are in place or are fine tuning them (47%vs.25%).Roadmap.Mainstreaming organizations are more than twice as likely as Piloters to agree they have“done or are fine-tuning”a comprehensive AI roadmap(42

114、%vs.22%),showing they have a structured and goal-oriented rather than piecemeal approach.KPIs.Mainstream organizations are twice as likely as Piloters to claim“best in class”CX measurement(34%vs.21%).This foundational work means that further down in the business,Mainstreamers in organizations using

115、generative AI in 2024 are much better placed than Piloters to drive growth in adapting content(45%versus 29%),to use generative AI for ideation(49%versus 32%),and to update content in real time(45%versus 28%).Overall,there is still an opportunity for more progress with generative AI.Over three-quart

116、ers of senior executives(76%)are still working on,planning,or have not yet started aligning it to broader business goals,and 75%are in a similar position when it comes to identifying KPIs that will show its impact.Both will be necessary if generative AI is to fulfill its potential and deliver tangib

117、le returns on investment.Figure 20:The timeline senior executives anticipate changes to their organizational structure to support the adoption of generative AI.8%22%37%32%7%22%32%38%9%23%32%36%7%23%31%39%7%23%30%40%Seeking external help to develop strategyUpskilling and hiring new staff in marketing

118、 and CXIntroduction of AI leadership rolesEstablishing cross-functional teams for rapid AI project rolloutReorganizing teams and functions to accommodate the use of AIMiddle of 2024End of 20242025 or laterDont anticipate this shiftSample size:2,142RecommendationsExceptional digital CX through person

119、alization,generative AI,and unified data.To deliver on the needs of customers today across their buyers journey and to capitalize on the opportunities afforded by generative AI,organizations should focus on the following key recommendations distilled from this years Digital Trends research:Understan

120、d your customers and dont make assumptions about personalization.Build a better understanding of how and where customers want to experience personalization and how touchpoints should connect across their journey.Then use that understanding to“right-size”digital experiences based on their preferences

121、.Unify your data and use it to deliver what your customers expect.Data must be unified in a robust system and ready to support emerging CX innovations.Only then can you gain more accurate insight into consumer needs and effectively personalize across journeys.Customers are looking for brands to impr

122、ove tailored messages and timely reminders,give relevant recommendations,and recognize them across channels.Reinforce data governance.Consumers want reassurance that their data is being used appropriately and securely,especially in the hands of generative AI.And internal teams want reassurance they

123、can use data to inform their strategies without inadvertently breaching that trust.Strong data compliance policies can be built on the back of robust data systems to instill that trust and pave the way for progress.Content is a solid starting point.Start your generative AI journey by optimizing and

124、scaling content.From there,work to build more complex use cases.Automating customer support tasks,such as chatbot experiences,are attractive to brands but require sophisticated data systems.Break down cross-functional siloes.Integrate systems,cross-functional teams,and workflows that will allow you

125、to embed generative AI as an integral part of your business operations.Align generative AI to overall business goals.The promise of generative AI wont be realized with a piecemeal approach.Organizations need to set realistic generative AI goals that are aligned with real business priorities and inve

126、stment to drive effective transformation and achieve sustained growth.1819Methodology Executive survey The executive survey was fielded in January and February 2024 to Econsultancy,Adobe lists,and external panels.Launched on January 1,2024,the survey closed on February 19,2024,with 8,600 qualified r

127、espondents.76%of all respondents are client-side marketers.The remaining 24%comprises agency executives,consultancies,and marketing technology/services vendors.This report presents insights from client-side marketers.37%of client-side respondents are senior director level or above,and 63%are practit

128、ioners(made up of junior executives,managers,and director-level respondents).Throughout the report,we compare these two groups.As defined by the target market,the client-side sample is split between B2B(32%),B2C(23%),and those addressing both markets equally(45%).The client-side sample is global,wit

129、h Europe providing the largest share of respondents(42%),followed by North America(32%)and the Asia-Pacific region(22%).The survey was translated into eight languages.Every business sector is represented,with most client-side responses coming from technology(21%),manufacturing and engineering(14%),r

130、etail and ecommerce(14%),financial services(13%),and media and entertainment(7%).Executive Market Leaders,Challengers,and Followers This study draws comparisons between Market Leader and Market Follower organizations.These are defined based on practitioners and senior executives responses to a surve

131、y question relating to their 2023 company performance versus sector competitors.Focusing on these insights allows us to explore issues that most differentiate commercially successful from unsuccessful organizations.Market Leaders are senior executives and practitioners who agreed they“significantly

132、outperformed”their sector (21%of all respondents).Market Challengers are senior executives and practitioners who agreed they had“slightly outperformed”their sector (35%of all respondents).While they are not called out specifically in this report,their responses are included in all the respondents fi

133、gures.Market Followers are senior executives and practitioners who agreed they had“kept pace”with their sector or “slightly or significantly underperformed”their sector (44%of all respondents).Customer Data SystemsModerately/Ineffective and Highly Effective Respondents were asked to rate aspects of

134、their customer data system on a scale of 15,with 5 being the most effective.Areas rated included:Provides consistent data across all customer touchpoints Enables rapid insights for personalization Produces actionable insights that give us a competitive edge Provides a holistic view of the customer M

135、aintains rigorous data privacy and security Using their responses to this question,we grouped them into three segments:Highly Effective,Effective,and Moderately/Ineffective.We only compared Highly Effective and Moderately/Ineffective executive groups for the analysis.Generative AI adoptionMainstream

136、ers and Piloters Respondents were asked to state their organizations status regarding the adoption of generative AI.Using their responses to this question,we grouped them into two segments:Mainstreamersthose who have solutions in place and are evaluating effectiveness.Pilotersthose who are implement

137、ing initial solutions,including pilot projects.Generative AI usage for workflow content productionEarly Adopters and Late Movers Respondents were asked to state when they planned to use generative AI in different areas of content production(Figure 17).Using their responses to this question,we groupe

138、d them into three segments:Early Adopters,Fast Followers,and Late Movers.Consumer Survey Between February 1,2024 and February 13,2024,we surveyed 6,800 consumers who engaged with brands online within the past three months.In addition to an even gender split,the country and age breakdowns included th

139、e following:49%were men and 51%were women.12%were aged 1824,17%were from the age bands of 2534,3544,and 4554,respectively,20%were from 5564,and 13%were from 6574.Respondents were sourced from across 13 countries across three regions.A majority of respondents came from US,UK,France,and Germany.20 MMXXIII Econsultancy/Adobe Adobe and the Adobe logo are either registered trademarks or trademarks of Adobe in the United States and/or other countries.