Acxiom：2023年客戶情報CI評估報告您對客戶的了解程度如何（英文版）（52頁）.pdf

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1、1Customer Intelligence How well do youunderstand yourcustomers?2CONTENTS True Assessment of CI Maturity Pillar 1:Strategy and MindsetPillar 2:Data HealthPillar 3:Analytics and EnablementPillar 4:Operations and SupportImplicationsMethodology and Sample Breakdown03041018273646483FOREWORD well do you u

2、nderstand your customers?It sounds like a simple enough question,but in todays increasingly complex and competitive market,the answer could be the difference between success and failure,profjt and loss.The challenges facing brands are momentous.While consumers still have money to spend,rising prices

3、 mean brands are competing fjercely for a shrinking number of transactions and are having to work harder to move from conversions into relationships.At the same time customer expectations for personalized,meaningful experiences are skyrocketing.Brands need to enable these experiences across a contin

4、ually expanding range of online and offmine channels,all while navigating a changing privacy and identity landscape.The stats are clear.Almost 90%of consumers think the experience a company provides is as important as its product or services.And three-quarters expect brands to understand their uniqu

5、e needs.1The only way to meet these high expectations is by gaining in-depth knowledge of the customer what they want and how they behave through data-driven Customer Intelligence(CI).The pressing need for an effective CI strategy wont be news to the majority of brands.Most already know that using d

6、ata to understand people can help them acquire new prospects,retain existing customers,and grow trusting relationships.But they also know how hard implementing CI across an organization can be.The ongoing expansion of digital channels provides an exciting opportunity to really get to know their cust

7、omers,but it also means wrangling a mass of complexity,fragmentation,and siloed data.The data exhaust generated by a customers digital interactions is massive and continually growing so determining which data points really matter and which can be ignored is a diffjcult task in itself.A proliferation

8、 of technologies designed to make sense of various data types can just add to the challenge if theyre not integrated effectively and used to create a single customer view.The journey to CI maturity is a long and complicated one,and it isnt always easy to determine what point a brand has reached.So,w

9、e commissioned a study from international strategy and research agency MTM to build a detailed view of the market and uncover how brands across the US and the UK are really making use of data-driven intelligence.Rather than just exploring their views on CI,we aimed to dig deeper and discover the qua

10、lity of the data brands are using,as well as what infrastructure is in place to support intelligence.We wanted to fjnd out whether customer insights are actually driving strategic decision making and how they are ultimately translated into action.This report is the result,and it reveals a fascinatin

11、gly nuanced picture of the intelligence landscape.It explores multiple facets of CI maturity and gauges where brands sit in that complex journey.It also explains what they need to do to move forward to a point where they can engage customers on their own terms through personalized,relevant,and respe

12、ctful experiences.In short,where they can use CI to differentiate their brands and gain a competitive advantage.Ill ask the question again.How well do you understand your customers?Its time to fjnd out.Tate Olinghouse Chief Client Offjcer 4A TRUE ASSESSMENT OF CI MATURITY difference highlights a sig

13、nifjcant gap between what businesses think,and what they are actually doing.The customer intelligence gap.In this Acxiom CI maturity assessment,we take a deep dive into the CI maturity journey and explore where organizations currently sit along that path.We give examples of what best-in-class looks

14、like,and provide recommendations toward achieving it.And therell be lessons to learn from the real-life experiences of industry experts currently making their own journey.To stay relevant and maintain competitive advantage,brands need to combine the power of data,analytics,and artifjcial intelligenc

15、e so they can truly understand their customers.”Katia Walsh,Chief Global Strategy and AI Offjcer,Levi Strauss&Co.“A True Assessment of CI Maturity 87%of companies agree that using data and predictive analytics to improve customer experience will be a key source of customer advantage over the next fj

16、ve years26%But only 26%describe using analytics to drive product and service innovationExhibit 1:Companies perception and use of analytics The customer intelligence gap Understanding customers is fundamental to a brands success.After all,when you understand people,the conversations you can have and

17、the experiences you can create for them will always be better.Better conversations and experiences build trust.And people love to buy from brands they trust.Customer intelligence,or CI,is the key to understanding customers,and most businesses know how vital it can be.But just because businesses real

18、ize CI is important,doesnt mean theyre making full use of it.In our recent research focused on customer experience trends,we discovered that although 87%of companies believe using data and predictive analytics to improve customer experience is a key source of competitive advantage,only 26%are curren

19、tly using analytics to drive product and service innovation.25A TRUE ASSESSMENT OF CI MATURITY market in transition To understand CI maturity,we created a framework against which to assess 200 US and UK businesses,using a survey followed up by interviews.The framework has four stages of maturity exp

20、loring,developing,maturing,and differentiating.At a high level,the results look promising,with 86%of organizations sitting within the two middle stages of developing and maturing.But there is still plenty of work to be done for most brands to reach the differentiating stage where they can use CI to

21、drive competitive advantage.The four pillars of CI strategy To gain a more detailed understanding of the situation,we went deeper and scored businesses on the four pillars that must support any effective CI strategy,using the same four maturity stages.These pillars are:Strategy and mindset Is CI emb

22、edded at leadership level,are analytics and commercial strategy aligned,and is the organization committing suffjcient resources?Data healthWhat is the quality in range and depth of data,how it is collected and stored,and how regularly is it updated?Analytics and enablement How sophisticated are the

23、analytics used to drive insights,and are those insights translated into actions?Operations and supportDoes the organization have the infrastructure and operational set-up to deliver market-leading CI?Pockets of insights and analytics specialisms,but not rolled out consistently Some strategic,forward

24、looking work,butmostly report on customerinteractions,rather than predict them Increasing number ofnon-marketing use cases Limited businessintelligence capabilities Some reportage againstcore metrics Mostly marketing scope Deep specialism across business intelligence and advanced analytics Strategic

25、,forward-lookinginsights across wide range of marketing and non-marketing use cases Trusted adviser to seniormanagement CI is a source ofcompetitive advantage Strategic and predictive,with a focus on deliveringbest-in-class marketing,CX and operations Automation enablesresponse to customersignals in

26、 real time Corporate leaderExploringDevelopingMaturingDifferentiating10%48%38%4%Scale%of respondentsCharacteristic6A TRUE ASSESSMENT OF CI MATURITY we examined our results through each of the pillars,we saw a far more nuanced picture.Higher maturity scores across the data health and operations pilla

27、rs suggest many companiesknow they need to collect data and are taking steps to do this.The lower maturity in the other pillars suggest businesses are less clear about what to do with data once they have it.Exhibit 2:Distribution of Levels of Digital Maturity among survey respondents ExploringDevelo

28、pingMaturingDifferentiatingStrategy and MindsetAnalytics and EnablementData HealthOperations and Support10%9%25%22%8%9%10%16%30%44%25%34%52%38%40%28%7A TRUE ASSESSMENT OF CI MATURITY Room for improvement To achieve an even more granular view of how businesses are progressing on their CI journey,we b

29、roke each of the supporting pillars down into multiple categories,and scored each of the brands that took part in our study against those.In the following chapters,well explore these pillars further,and reveal how maturity levels vary across different categories.In the meantime,lets take a look at h

30、ow CI maturity is impacted by business size.Heres a snapshot of some of the promising trends and areas of opportunity that emerged within each pillar.Exhibit 3:Opportunities and areas for concern across our four pillarsStrategy and Mindset56%of businesses agree that their customer insight function i

31、s mainly focused on delivering the companys key commercial objectives3Analytics&Enablement60%of businesses claim to use advanced analytics techniques for CI6Data Health46%of businesses claim to be using a combination of fjrst-,second-,and third-party data5Operations&Support63%of businesses say they

32、have CI Centers of Excellence to share best practices across the business79%of businesses use identity resolution to unite data signals in a single customer view,impacting their ability to deliver meaningful outcomes.3But only22%have real-time,collaborative data platforms that can be accessed by all

33、 teams8But only23%use AI or ML within their advanced analytics capabilities6But only7%say that CI is being actively championed by the CEO or president4But by business size In general,larger businesses are a little further along in their CI journey:86%of the largest businesses($1bn annual revenue)rea

34、ch the maturing or differentiating stage.That said,only 12%of them classify as differentiating,so there is still plenty of work to be done.9So why are larger organizations more mature in CI?This appears,in part,to be a function of the scale of resources at their disposal,which enables them to invest

35、 more heavily in data,as well as specialist technology and skills.Maturity also appears to relate to the scale and complexity of the organization,with multiple business units,products,and services driving the need for greater complexity in insight and analytics functions.There are also simply higher

36、 stakes in terms of revenue,reputation,and profjtability.Finally,greater compliance requirements,particularly in sectors such as fjnance and healthcare,can be a driver of increased sophistication.Organizations in these sectors have historically had to invest in robust data protection measures and pr

37、ocesses to comply with privacy and security regulations.Exhibit 4:Proportion classifying as maturing or differentiating,by revenue A TRUE ASSESSMENT OF CI MATURITY businesses$/1bn revenue32%of businesses$/500-999m revenue24%of businesses$/100-499m revenue9 While its both possible and useful to estab

38、lish overall trends in CI maturity,and to identify general areas where business can improve,its important to remember that every business is unique.Our interviews demonstrate clearly that each organization has its own individual needs and its own barriers to CI maturity that must be overcome.For som

39、e,its the level of spend required to transform legacy infrastructure that makes the capital investment too signifjcant,especially in diffjcult economic circumstances.One Head of Insights at a fjnancial services provider told us:“I came from one of the US leading start-ups.My job is to transform us i

40、nto the kind of data-driven company they are.Theres a desire to make the leap,but also hesitancy,because our legacy CRM is not fjt for purpose and there just isnt the money to make such a big investment.”Playbook:No two companies are the same Elsewhere,we heard that changing mindsets,rather than upd

41、ating technology,represents the biggest blocker to progress:“I am Head of AI/Analytics in a global telecoms business.The biggest challenge has been convincing the senior managers to make decisions using the data and the tools I provide.”Even within organizations,we heard about barriers differing by

42、market,driven by scale,culture,or business model.We also see variations by sector(especially health and fjnance)in terms of the volume and sensitivity of customer data available,and the compliance regulations that apply to it.As such,the picture is not a universal one.CI transformations differ based

43、 on companies starting points,motivations,access to data,barriers to change,and end goals.And this inconsistency becomes abundantly clear as we delve deeper into the four pillars of the CI maturity framework.A TRUE ASSESSMENT OF CI MATURITY 10STRATEGY AND MINDSETPillar 111 PILLAR 1:STRATEGY AND MIND

44、SET does good look like?The following will be true for the 8%of businesses that are at the differentiating stage of the strategy and mindset pillar:Strategic alignment There is a clear vision and plan for how CI can deliver the companys key commercial objectives.Decision makingCI and analytics infor

45、ms the most strategic,organization-wide decisions.Executive sponsorshipCI is actively championed at CEO or president level.Investment priorityCI budget and resources are large enough to enable strategic,innovative,and experimental work.Differentiating8%Developing52%Maturing30%Exploring10%What is it?

46、Within the strategy and mindset pillar,we investigate whether an organization has a clear vision and plan for CI.We assess whether CI is embedded into the leadership of the organization,how well the insight and analytics strategy is aligned with commercial strategy,and whether the organization is co

47、mmitting suffjcient resources.Strategy and mindset is the pillar where organizations show the second lowest maturity,with only 38%scoring as differentiating or maturing.And it is a strong indicator for overall outcomes,with 86%of those who are at the exploring or developing stage of the overall fram

48、ework also exploring or developing in the strategy and mindset pillar.To understand the stage a business has reached in the strategy and mindset pillar,we broke it down into four key categories:strategic alignment,executive sponsorship,decision making,and investment priority.Exhibit 5:Distribution o

49、f scores in the Strategy and Mindset Pillar12 PILLAR 1:STRATEGY AND MINDSET 6:Proportion of businesses exhibiting strategic alignment,executive sponsorship,CI-informed decision-making and prioritized CI budgetsExploringDevelopingMaturingDifferentiatingLow MaturityHigh Maturity40%24%22%14%BudgetAlign

50、ment to commercial objectives25%19%44%12%Active championing 39%52%7%Decision-making42%36%15%7%CI functions are focused on delivering the companys key commercial objectives.Most orgs are maturing they somewhat agree that CI activities and commercial objectives align.Most orgs are maturing CI has seni

51、or champions at C-suite level.Most orgs are developing CI provides insights and recommendations to functions within the business.Most orgs are developing budget is stable or declining and only minimally suffjcient.It might be vulnerable to being cut.CI strategy is detached from the companys commerci

52、al objectives.CI is actively championed by the CEO or president,or by someone reporting directly to them.CI is not actively championed by senior management.CI insight and analytics are embedded into the organizations strategic decision making.CI fulfjlls data requests frombusiness units.CI budget is

53、 suffjcient for strategic,innovative,and experimental work.Budget is set to decline,isvulnerable to being cut,and/oris insuffjcient for desired activities.High Maturity FeaturesLow Maturity FeaturesCI functions have senior sponsorship,but are not yet as successfully embedded into organizations strat

54、egic decision making 13 PILLAR 1:STRATEGY AND MINDSET alignmentThe pandemic compressed fjve years of growth in digital channels and ecommerce into a few months.10At the same time,third-party cookie deprecation,evolving privacy regulations,and rising customer expectations are combining to cause a ste

55、p change in what is needed from CI,and in the demand for a fjrst-party data strategy.Businesses understand the signifjcance of these changes.In fact,almost all the companies we interviewed talk about understanding and meeting customer needs in their mission statements.Despite this,only 12%of these c

56、ompanies strongly agree that their CI function is focused on delivering the companys key commercial objectives.Even though a further 44%did somewhat agree,this indicates that,for the remaining 44%,CI strategy is largely detached from commercial objectives.3Exhibit 7:Key trends impacting insights and

57、 analytics strategyPrivacy regulationPandemic accelerates digitalCore focusSecondary focusNot a focusof advertisers see compliance with privacy regulations as a core or secondary focus.11Internet sales as a%of retail sales have settled at a new normal post-pandemic.1266%Personalizationof consumers a

58、re more likely to buy from a brand that treats them as an individual.1394%57%37%6%Feb 2020Jan 2021Oct 202219.1%37.8%26%14 PILLAR 1:STRATEGY AND MINDSET whats going on?The key challenge for these businesses appears to be the required shift to using fjrst-party data,as many lack the people,skills,and

59、processes to make this change.Moving forward,these businesses can learn from those that are more advanced in the strategy and mindset pillar.The more mature organizations demonstrate collaboration between analytics,engineering,and marketing teams to develop a clear view of what data and insight is n

60、eeded to reach certain goals and resolve specifjc problems.They establish test-and-learn processes,so they can pilot activities and continuously improve their strategy.As one CMO in an ecommerce business explained:“When Apple made their ATT changewe reorientated to having a 1-2-1 direct relationship

61、 with the customer.Now our loyalty sales penetration is about 70%of our sales.”Executive sponsorship The presence of executive sponsorship,and the level of engagement between this sponsor and the insight function,are two critical drivers of a successful CI strategy.The executive sponsors role is to

62、embed a culture of objective,data-driven decision making at senior levels across the organization.They need to build coalitions across a business,perhaps pushing for greater integration across teams or driving investment.And theyre also there to raise the bar for insight teams,ensuring their work yi

63、elds high impact for the business.The businesses that took part in this research display a variety of approaches to executive sponsorship.Some are establishing new,dedicated executive positions such as a chief data offjcer(CDO)to embed sponsorship in the board.Others are locating insight and analyti

64、cs teams under central strategy teams or under the CMO.Our survey results reveal a mixed picture of executive sponsorship.Only 7%of businesses describe CI as being actively championed at the CEO or president level.However,a more reassuring 52%describe it as being actively championed by someone repor

65、ting into this level.4In general,ensuring CI is actively championed by senior management is an area for development.When a BCG study into best practices for CI asked whether consumer insight teams“consistently answer the question so what?about the data they provide,”73%of consumer insight staff said

66、 yes.But only 34%of their line managers agreed.14People who have championed my team the Customer Intelligence team include the COO,the CFO,and the CEO.This is a Board-level conversation these days.”Head of Insight,Insurance Provider“15PILLAR 1:STRATEGY AND MINDSET makingCI insights and analytics sho

67、uld be embedded into an organizations strategic decision making.But the majority of the businesses interviewed have some way to go to achieve this goal.Most currently use CI to fulfjll data requests from other areas of the organization and provide insights to specifjc functions within the business r

68、ather than to drive core decision making.Our interviews highlight multiple examples where,even though data and insights are available,they are excluded from business decision making.Investment priority The insight teams that took part in the study are relatively positive about the budget made availa

69、ble to them.In fact,a strong 22%of businesses scored within the differentiating category for investment priority.Just over 50%see their budget as stable,and 41%describe it as growing indicating CI remains a strategic priority despite the challenging economic circumstances.15 Only 17%describe their b

70、udget as insuffjcient,and a further 45%describe it as minimally suffjcient.16But there are important caveats to this positive story.Only 38%describe their budgets as suffjcient to enable strategic and experimental work.16 And intervieweessuggest budget alone is not an indication of maturity.Many foc

71、us instead on the importance of tracking ROI for CI initiatives,with CI functions often performing well on observable metrics such as customer loyalty and growth rates.Several heads of analytics and AI told us budgetary pressures exist across the whole business,but they see themselves as value drive

72、rs rather than cost centers.Tracking these metrics will help shift overall business mindset so CI is seen as a revenue driver.Although the data suggests most budgets are stable or rising,we did talk to several leaders,especially heads of traditional customer insight functions,who are contending with

73、 reduced budgets in light of economic headwinds.Even where budgets are seen as suffjcient,there is increased focus on delivering“more for less”in the face of economic uncertainty.One exec told us:Our focus now is on the projects that have the most impact,where we can prove we deliver value via cost

74、savings or enhanced sales.Some of the longer-term projects might have to wait.”“1616PILLAR 1:STRATEGY AND MINDSET spendon platforms and toolsIn an effort to cut spending,they are reviewing the value-add of outsourced customer data infrastructure and developing guidelines for approaching vendor relat

75、ionships.“I need to review all the spend on any platform resources,be it secondary research portals,infrastructure Were building preferred supplier lists,negotiating general approaches to contracting outside partners.”Playbook:More for lessThe Senior Director of Customer Insight at a leading payment

76、s solution provider told us:“One of the biggest issues to manage over the next year is how I internalize a reduction in my budget while still providing the same or an even better level of insight more for less.”Their company is applying a two-pronged approach to deal with these demands:2.ExploringDI

77、Y solutionsThe team is bringing as much work as possible in-house,using DIY platforms and internal analytics teams where they know what questions they want to ask.“That way we dont need anyone outside to write a questionnaire or do the analysis.Were using the platform ourselves,to code,fjeld,and ana

78、lyze now.If you think about it,when we already know what we want to ask,why hire an outside agency to do all of that?We know the questions,we know what we want to get out of it,we can just put it in ourselves and get it done and its very effjcient.”Cloud the great equalizerBoth of these approaches a

79、re enabled by the availability of cloud-based,plug-and-play tools for data and analytics.The speed,scalability,and fmexibility of the cloud makes understanding the customer simpler and cheaper,and this low barrier to entry encourages exploration and innovation,particularly around artifjcial intellig

80、ence(AI)and machine learning(ML).The democratization of CI toolsets in the cloud means businesses can test out familiar solutions,with pre-built integrations,to gain access to data,generate insight,and take action.“Our analytics and data science team is thinking a lot about automation as we reduce b

81、udgets.Its about standardizing how we do things from taking data in to producing output.Its complexity reduction.”Senior Director of Customer Insight,leading payments solution provider17Align CI activities with the companys key commercial objectives and track ROI against these objectives.Focus on us

82、e cases with the potentialto unlock value.Track ROI against these use cases,using indicators that relate to revenueand company performance,whichalso shift CI from being seen merelyas a cost center.Embed executive sponsorship at board level,to instill a culture of trust in the data and ensure the ana

83、lytics team remains close to commercial priorities.Ensure CI is an integral part of strategic decision making,not just fulfjlling requests from individual business units.Build a roadmap with quarter-by-quarter strategic activities.For companies in their maturityjourney,this will involveunderstanding

84、 what data they haveand what data is needed to deliveragainst specifjc use cases.Allocate suffjcient CI budgets to support a culture of innovation and experimentation.Strategic alignment Executive sponsorship Decision makingInvestment priorityPILLAR 1:STRATEGY AND MINDSET Key take- HEALTHPillar 219

85、PILLAR 2:DATA HEALTH does good look like?The following will be true for the 9%of businesses that are at the differentiating stage of the data health pillar:Differentiating9%Developing38%Maturing44%Exploring9%Access to data Collects data from a wide range of fjrst-,second-,and third-party sources,upd

86、ates that data frequently,and has a clear plan to derive value from it.Single customer viewIntegrates this data and uses advanced identity resolution to provide a coherent view of its customers that is accessible across the business.Value exchangeDelivers value to its customers in return for the fjr

87、st-party data collected.Data partnershipsMaintains a range of partnerships withother participants in the data economy to harness the power of second-party data.What is it?Within the data health pillar,we determine how accurate and reliable customer data is.We assess the quality in range and depth of

88、 data,but also how it is collected and stored,and how regularly it is updated.Organizations that took part in our research perform most strongly against this pillar.It has the lowest incidence of exploring responses(9%)and the highest combined maturing or differentiating count(53%).This may refmect

89、how regulatory change is forcing businesses to re-assess their data strategies.To understand the stage a business has reached in the data health pillar,we broke it down into four key categories:access to data,single customer view,value exchange,and data partnerships.Exhibit 8:Distribution of Scores

90、in the Data Health pillar 20 PILLAR 2:DATA HEALTH MaturityHigh Maturity20%42%16%22%Single customer viewTypes and sources of data8%46%28%18%Frequency of updates60%30%10%Data storage25%53%21%A comprehensive set of external and internal data with a constant supply of new sources to support experimentat

91、ion.Most orgs are developing-they work with a range of conventional fjrst-and third-party data.Most orgs are developing they update data as frequently as weekly or monthly.Most orgs are maturing they employ an enterprise data management platform with a single or complete customer view for marketing.

92、Most orgs are maturing they agree to some extent that they maintain a cross-channel,single customer view.Basic,fjrst-party data only.Customer data is updated in real time.Customer data is not updated,or is updated only(semi)annually.Enterprise data management platform employed-data is made accessibl

93、e for company-wide application.Data exists in silos.Organizations maintain a single customer view,integrated across all data channels.No single customer view across all channels.High Maturity FeaturesLow Maturity FeaturesExploringDevelopingMaturingDifferentiatingExhibit 9:Proportion of businesses us

94、ing a suffjcient range of data types and sourcesThe majority of organizations have their enterprise data platform and single customer view in place although there is still work to do to ensure breadth,depth,and currency of their data21 PILLAR 2:DATA HEALTHCapturing data without a clear strategy for

95、how to use itAt fjrst sight,businesses appear advanced in the range and depth of data they collect.An impressive claim to have built a comprehensive set of fjrst-,second-,and third-party data,and 18%describe a constant supply of new sources as teams experiment with data types and techniques.5However

96、,interviews suggest brands often capture a wide range of data in the belief that collection itself translates to value but without a clear strategy for what to do with it.Unnecessary data collection burdens both the business and the customer.It increases the costs of technology,personnel,and managem

97、ent,and raises data management and compliance risks.And this burden is pointless if businesses lack a basic understanding of how to use that data to generate value.Whats more,the people data businesses have is often out of date.40%told us they update customer data daily to ensure it is accurate and

98、current,while 61%say they only do so weekly or even less frequently.This problem is more pronounced among smaller companies,where only 29%update daily.1746%“Too many businesses in the healthcare sector are collecting consumer data without a clear plan for how they will use it.This is a major privacy

99、 and security concern for consumers.”CDO,major healthcare company22 No single customer viewIn addition to the challenges of wasteful data collection,What is identity?To understand people better and reach the differentiating stage of the data health pillar,businesses must be able to identify customer

100、s in the moment,no matter where they are connecting,and learn from every interaction.This requires a robust enterprise identity solution,including a fjrst-party identity graph supported by third-party referential graphs,to gain a single,consistent customer view that can be used across the organizati

101、on.of businesses describe their data as existing mainly or completely in silos across the company.18While the remainder claim to have an enterprise data management platform,these platforms often contain multiple personas for each customer because they dont have the ability to link identifjers such a

102、s email addresses,cookies,device IDs,mailing addresses,social media handles,and more.Onlyof respondents strongly agree their company performs identity resolution,tying together these user IDs to build a single master portrait,enabling marketers to get a single customer view across all channels.39%26

103、%PILLAR 2:DATA HEALTHExhibit 10:Businesses carrying out identity resolution and maintaining a clear view of customer journey.“We carry out identity resolution”3Enterprise identityA single,connected identity solution across a businesss entire enterprise,available to any department(e.g.marketing,opera

104、tions)in order to enable a complete and consistent customer view and understanding.First-party identity graphReferential identity graphA private graph,unique to a business,linking fjrst-party data and third-party insights with customer identifjers to enable consistent cross-channel experiences.A thi

105、rd-party reference graph providing non-intuitive connections that arent evident in a businesss fjrst-party data.9%35%56%Strongly agreeSomewhat agreeNot in Value exchangeFirst-party customer data sits at the heart of any data strategy.This should be the case regardless of the third-party cookie situa

106、tion,but cookie deprecation is accentuating the need for fjrst-party insights.And any fjrst-party data strategy should be supported by a clear value exchange between customer and business.At its simplest,this value exchange is underpinned by a brand being ethical with customer data and respecting th

107、e customers preferences around how that data is used.Beyond that,businesses should use customer data to add value by offering more relevant,meaningful experiences.The goal should be to create experiences that are so relevant and respectful,customers feel like everything is happening on their terms.B

108、ut although almost all businesses acknowledge the importance of personalization,less than a quarter strongly agree they use customer data to create personalized experiences,and less than 10%strongly agree they tailor marketing content based on the point in the customer journey.3PILLAR 2:DATA HEALTH8

109、5%Agree the ad industryneeds to do better than the bare minimum to embrace a privacy-fjrst age.198%Maintain a clear view of where individual customers are in their journey with the company and are able to tailor marketing based on this view.323%Use customer data to create personalized experiences fo

110、r their customers.3Exhibit 11:Businesses agree they need to do better than the bare minimum but are still in the early stages of developing the value CMO of a leading American clothing company explains how getting the fjrst-party data value exchange right is particularly important for engaging young

111、er audiences.“Younger customer bases,theyre not put off by us sending the most relevant message in the most relevant channel at the right times.If we get any of this wrong,our customers will fmick by us.”The companys sophisticated consumer insight model uses real-time data from online and offmine ch

112、annels to keep up with the changing demands of a young audience.“Our best customers are toggling between in-person stores and digital channels all the time.We have to be increasingly sophisticated from a customer marketing standpoint,trying to get the next best,personalized offer.Thats a ground chan

113、ge in my industry,and Gen Z expect it more than anyone else.”Playbook:Value exchange for Gen ZData from the companys loyalty program is also a key input now that privacy changes make customer data harder to gather:“Trying to work with the best data and also holding up your end of the bargain with th

114、e customer in terms of his or her privacy,thats what weve been focused on.”“Were trying to create experiences that help our customers to make the best apparel decisions for their needs.Its not a grab for evil,or a one-sided we win,the customer doesnt.We want the customer to win,and we do that by ser

115、ving them the most relevant products and experiences always.That is how we develop our app,our email program,our SMS program,our paid media strategy.Its all about how we help them.”And customers are receiving this approach well.People are excited by us anticipating their needs,that were not sending

116、a spray-and-pray message,were sending a more bespoke message to you.When we lean into personalized offers,we see incremental results.”CMO,leading American clothing company“PILLAR 2:DATA HEALTH25 Data partnershipsIn addition to fjrst-party data,gained through a transparent and fair value exchange,bus

117、inesses can use data from other sources to get to know their customers better.Nearly half(46%)of businesses describe maintaining partnerships in the data economy for a range of purposes,from predictive analytics and personalization of marketing to generating revenue through data collaboration.Just u

118、nder one-fjfth(18%)describe experimenting with new data types and techniques such as real-time,unstructured data.5External data is critical to harnessing the power of AI and predictive analytics,as it enables companies to bring together a variety of data sets,search for patterns,then use the insight

119、s they fjnd to drive their predictive models.As one exec told us:“We have enriched our internal data repository with a great deal of external data anything from weather to social media trends,epidemiological models to oil prices.When you marry data sources that have never met in the past,its incredi

120、ble what you can fjnd.Then we apply ML to come up with recommendations for optimal pricing,promotions,inventory management.”PILLAR 2:DATA HEALTHAs cookie deprecation and regulatory changes impact data accessibility,marketers are turning to second-party data,gained through data partnerships,to help w

121、ith market research,audience segmentation,and the personalization of marketing.Data clean rooms are increasingly popular as a means for two or more parties to share data in a safe and privacy-complaint space.They can be used to:-Enhance relevance by creating custom audiencesfrom fjrst-party data and

122、 partner data to enable engaging messaging.-Build closed-loop measurement by bringingtogether fjrst-party data and one-to-many publishers exposure data for true omnichannel attribution.-Conduct a gap analysis with a partner that hasa similar customer base to understand the potentialto collaborate,dr

123、iving greater engagement andrevenue for both parties.-Support loyalty programs and make them moremeaningful by working with adjacent partners,resulting in greater customer retention andmore revenue.Finally,many companies are using data partnerships as a revenue-generating opportunity.By working with

124、 data-marketplace and aggregation platforms that specialize in building relationships with hundreds of data sources What is a data clean room?“Data clean rooms are privacy-conscious,data collaboration spaces.In a data clean room,brands and their trusted partners can share and combine data to create

125、new insights that benefjt all parties more relevant advertising for people,better growth for brands and their partners.They open up opportunities in co-marketing,audience building,monetization,and marketing measurement without asking brands to actually share their customers personally identifjable i

126、nformation.”Read more about Data Clean Rooms here“for example,consumer,real-estate,or company data a company can ethically share,trade,and supplement their own data.We work with vendors who have broader data-sets,because our fjrst-party data isnt enough to target our marketing.”Director of Customer

127、Insight,leading US Financial Services Key take-outsPILLAR 2:DATA HEALTH(including fjrst-,second-,and third-party data sources):Consider all types and sources,but makesure there is a clear use case for whateveryou collect Update regularly Supplement external data with partnershipswhere necessaryEnsur

128、e you have a clear value exchange with your customers for the data you collect from them:Offer customers choice over optingin or out of communications Use the data to tailor your communications and improve customer experience(e.g.,via personalized content)Consolidate your data on an enterprise data

129、management platform,and make it accessible to all teams who need it:Conduct identity resolution to ensure youfjnd,clean,match,merge,and relate all the disparate signals Data partnershipsValue exchangeAccess to data and single customer AND ENABLEMENT Pillar 328 PILLAR 3:ANALYTICS AND ENABLEMENT does

130、good look like?The following will be true for the 10%of businesses that are at the differentiating stage of the analytics and enablement pillar:Business intelligence Using conventional analytics to deliver insights that inform marketing and broader decision making.Advanced analyticsUsing advanced an

131、alytics techniques to drive strategic planning across the business.This includes personalization at scale as well as optimization of offers,messaging,and media mix.Customer journey viewHas a clear view of where individual customers are in their journey that is used to inform personalized marketing.A

132、ctivationUsing insights to drive a wide range of strategic and forward-looking use cases,not just in marketing but across all aspects of the enterprise,from product development and supply chain operation to customer service.Differentiating10%Developing40%Maturing25%Exploring25%What is it?Within the

133、analytics and enablement pillar,we assess the sophistication of the analytics used to drive insights and the degree to which those insights are then translated into actions across the business.It is the weakest performing of the four pillars,with two-thirds of businesses falling into the exploring o

134、r developing stages.In general,the picture that emerges is of businesses that are capturing data but not yet driving insights from it,or actioning insights to make decisions in marketing,product,supply chain,or other functions.To understand the stage a business has reached in the analytics and enabl

135、ement pillar,we broke it down into four key categories:business intelligence,advanced analytics,customer journey view,and activation.Exhibit 12:Distribution of scores in the Analytics and Enablement pillar 29 Most orgs are developing they do not agree with certainty that they maintain customer journ

136、ey views.PILLAR 3:ANALYTICS AND ENABLEMENT MaturityHigh MaturityAnalytical capabilities14%10%26%37%23%customer journey-based view to personalize marketing and customer experiences49%37%Breadth of activation9%59%4%4%Capability to conduct advanced analytics and use AI/ML.Only basic data analytics capa

137、bilities.Clear view of where individual customers are in the journey,to inform marketing personalization.No customer journey-based view,and so cannot personalize marketing based on customer interactions.Customer insight powers the enterprise(including product,customer service and operations function

138、s).CI is used mainly for marketing campaign optimization.High Maturity FeaturesLow Maturity FeaturesMost orgs are maturing they practice advanced analytics but do not employ ML or AI.Most orgs are maturing they use CI for both marketing and non-marketing use cases.28%Exhibit 13:Proportion of busines

139、ses exhibiting mature data analytics and activation capabilities Over 2/3 of organizations do not maintain a reliable customer journey based view to inform their marketing,and less than a third use AI in their advanced analyticsExploringDevelopingMaturingDifferentiating30 Business intelligenceof bus

140、inesses describe their capabilities as being focused on basic or enhanced conventional analytics sometimes referred to as business intelligence.6These business intelligence capabilities are mostly centered around analyzing and reporting against what has happened,rather than predicting what will happ

141、en.20This includes the ability to plan,measure,and optimize marketing campaigns,and the generation and analysis of classic business metrics such as NPS and customer lifetime value.PILLAR 3:ANALYTICS AND ENABLEMENT 40%37%mainly use this business intelligence for reporting performance and marketing ca

142、mpaign optimization.Two-thirds use it mainly for strategic purposes.21For more information about marketing analytics and enablement,please see the Acxiom-sponsored Winterberry Group report,From Data to Insight:The Outlook for Marketing Analytics.This report provides insights into how businesses are

143、using marketing analytics today,and how they are maturing in their use of Advanced analyticsThe research reveals a growing focus on advanced analytics techniques,such as using ML to generate insights and make predictions by spotting patterns in data sets.These techniques are growing in importance du

144、e to(among other things)the increasing volume of data available,enhanced processing power,and the capacity to reveal trends in data to inform marketing and other business decisions(including personalization at scale).Predictive models help companies gauge the probable value of the different occasion

145、s when a customer or potential customer comes into contact with their brand and its messages,which in turn enables ROI optimization.One retail executive for an American apparel company describes its impact on their campaign optimization:“We are turning more and more of our media strategy over to the

146、 machines.Attributions based on predictive models help us optimize ROI in our campaigns and product offers.We can serve the right creative to the right person at the right time and win in terms of incremental revenue and margins.”Over half(60%)of businesses claim to use these advanced analytics tech

147、niques,although it may be that respondents are using a broad defjnition of the term,to include basic modeling and reporting,as only a quarter list ML in their capabilities.640%Use only basic or enhanced conventional analyticsConventional analytics37%Have advanced analytics capabilities,with no AI/ML

148、Advanced analytics with no AI/ML23%Have advanced analytics capabilities,including the use of AI/MLAdvanced analytics with AI/MLExhibit 14:Levels of business analytics capabilities6PILLAR 3:ANALYTICS AND ENABLEMENT PILLAR 3:ANALYTICS AND ENABLEMENT Customer journey view Customer journey view is a wea

149、k area of the analytics and enablement pillar.The majority of businesses do not have this view,and therefore cannot target marketing based on customer interactions.Achieving a customer journey view is a problem at even the largest businesses.Activation Businesses with mature CI functions are increas

150、ingly using their insight and analytics capabilities to drive decision making across the whole enterprise including product design,supply chain management,and logistics.A positive 59%of companies score within the maturing category for business-wide application,indicating they are using CI for both m

151、arketing and non-marketing use cases.22We found one example of a retail business developing algorithms to determine where it would be most effjcient to ship products from,based on their customer distribution and purchase patterns.These insights give the business a better handle on store inventory,re

152、duce shipping costs,and maximize effjciency to improve customer experience.The Customer Support department of another business analyzes call length,resolution,and customer satisfaction data to assess team productivity and pinpoint problems.They then deploy training solutions and hiring strategies to

153、 address them.Exhibit 15:Proportion of respondents with a clear customer journey view.“We maintain a clear view of where individual customers are in the journey with us,and are able to target their marketing based on this view.”3We spoke to the Head of Insight at a technology business that generates

154、$200bn in revenue annually,who told us that this process was just beginning.“Im working on customer journey mapping in one market,pulling together all the different data points we have.Hopefully we can roll it out elsewhere once weve done that.People are excited about it Ive dedicated a quarter of m

155、y workload at the moment to this.”8%Strongly agree44%Somewhat agree48%Not in PILLAR 3:ANALYTICS AND ENABLEMENT of CI data can happen at all stages of the customer journey and product lifecycle,as well as at operational levelExhibit 16:Activation of CI across the businessPersonalized marketing Identi

156、fy untapped ideal markets Develop journey-based individualmarketing strategies,segmented by goals(reaching new customers and retaining existing ones)Product development and design Test or predict demand for newproduct/service designs or features prior to production Inventory Identify patterns in dem

157、and whichinform decisions made regardinginventory(e.g.product deprecation,or when in the year products are released)Internal operations Detect talent shortages and implementhiring or development programsSupply chain Strive for real-time,demand-responsiveprocurement of supplies Assess supplier perfor

158、mance usingcustomer feedbackCustomer experience Tailor customer service offerings Improve effjciency of interaction(reduce wait times,solve issues more quickly e.g.via chatbots)Pricing strategy Test price elasticity of demandfor product/service offerings,and tailor pricing offerings based on segment

159、ation of customers Maximize conversion and reduce churnLogistics and distribution Maximize effjciency of shipping andstorage based on customer location and demand data3434 PILLAR 3:ANALYTICS AND ENABLEMENT Prediction:#1The ability to predict how impactful metrics,such as levels of consumer demand fo

160、r key products,and propensity to pay,will evolve.For example,post-lockdown,when stores reopened,most clothing retailers rolled out mass discounts to clear stock.But predictive models allowed Katia and her team to see this differently:“Because we knew that customers after COVID showed pent-up demand,

161、we did not discount.”Personalization:#3Tailoring your offering(product,service,or interaction)to consumers based on their identity and behaviors,and any relevant context.Katia describes how benefjts,including special offers,might work for shoppers and fans who subscribe to exclusive services:“A musi

162、c fan would get concert tickets,someone into fashion would get early access to a new collection,someone into sustainability would be offered sessions in a tailor shop to repair items that they already have.”Precision:#2The ability to maximize performance against profjt,sustainability,and creativity

163、by pinpointing optimal objectives.This might apply when setting prices or managing inventory levels.Katia explains:“In the apparel retail industry,companies like Nike,Levis,PVH,VF,and Abercrombie&Fitch combine manufacturing and retail.There is a desperate need for precision for that industry.But tha

164、ts not unique to an industry.There is also precision medicine,precision agriculture,and more.”Proactivity:#4Anticipating changes in(and opportunities for stimulating)demand and then using this knowledge to retain or attract customers and spend.This includes driving sales by preemptively stimulating

165、interest and engagement via targeted communications with potential consumer groups.Playbook:The Four Ps,a retail POVThe retail industry is increasingly integrating AI and predictive analytics into business strategies and ways of working.Katia Walsh,Chief Global Strategy and AI Offjcer at Levi Straus

166、sand Co.,is at the forefront of these changes.Katia has been with Levis since 2019,with a focus on blending Levis values with innovative technological capabilities to drive change and increase revenue.She describes the vision against which they are seeking to deliver as the four Ps prediction,precis

167、ion,personalization,and PILLAR 3:ANALYTICS AND ENABLEMENT Key take-outsLook for opportunities to shift from retrospective reporting on what has happened to predictive analytics where value-add can be driven.Bring customer intelligence to the forefront of your strategic conversations:Reorientate the

168、conversations soreports on customer behavior are delivered ahead of fjnancials.Develop a feedback loop todemonstrate what was learned fromcustomer data,how it might impactbusiness outcomes,and how to acton it.Adopt a customer journey view that enables your business to tailor customer interactions ba

169、sed on their position on the path to purchase.Explore CI use cases beyond the marketing function,perhaps in product,logistics,or internal operations.Integrate these teams so that whereCI contributes it can inform forwardthinking(e.g.“What is the product that our customers want?”)Business intelligenc

170、e Advanced analytics Customer journey view ActivationKey take- AND SUPPORTPillar 437 PILLAR 4:OPERATIONS AND SUPPORT does good look like?The following will be true for the 16%of businesses that are at the differentiating stage of the operations and support pillar:Tech-stack Up-to-date stack includin

171、g cloud-based CRM and CDP to enable real-time,collaborative access to data across the business.AutomationWorkfmow automated,from data gathering and ingestion to analysis and activation,to drive cost effectiveness and enable personalization at scale.Skills and capabilitiesMultidisciplinary team(s)of

172、data scientists and engineers,developers,analysts,and strategists with a strong commercial and product/service strategy focus.Center of excellenceInsight and analytics capabilities structured to ensure best practice,standardization,and quality control through all business units.Differentiating16%Dev

173、eloping28%Maturing34%Exploring22%What is it?Within the operations and support pillar,we determine whether organizations have the infrastructure and operational setup for market-leading CI.Organizations show similar levels of maturity in operations and support as they do in data health,with half scor

174、ing as differentiating or maturing.Responses were most varied in this pillar,with relatively high proportions of exploring(22%)responses,but also more maturing responses (34%)than most other pillars.To understand the stage a business has reached in the operations and support pillar,we broke it down

175、into four key categories:tech stack,automation,skills and capabilities,and center of excellence.Exhibit 17:Distribution of scores in the Operations and Support pillar 38 MaturityHigh MaturityAutomation26%32%20%22%Use of cloud44%39%13%Sophisticated,real-time,collaborative platform(s)that stakeholders

176、 across the business can accessManual integration and activation of customer data and analyticsEverything is stored in the cloudEverything is stored in internal data center(s)there is no use of cloudHigh Maturity FeaturesLow Maturity FeaturesExploringDevelopingMaturingDifferentiatingMost orgs are de

177、veloping they have a hybrid model with limited use of cloudMost orgs are developing analytical output is largely ad hoc and batch processedPILLAR 4:OPERATIONS AND SUPPORT Most orgs(48%)somewhat agree that they use a customer data platform to combine and manage customer dataExhibit 18:Proportion of b

178、usinesses employing sophisticated technology stacks to support customer intelligence functions Companies are making progress toward cloud migration,and the automation of their customer intelligence workfmow39 PILLAR 4:OPERATIONS AND SUPPORT The most sophisticated insight leaders are prioritizing the

179、 use of automation and AI across multiple workfmows.This might be integrating internal and external systems for billing and reporting,or automating standard,repetitive tasks such as data collection or basic campaign setup.This is often accomplished using the automation solutions already built into p

180、latforms,particularly for campaign optimization and audience reach.Implemented correctly,automation allows businesses to engage customers at scale with relevant,personalized experiences,and to offer seamless omnichannel journeys,as well as responsive customer support around the clock.There is also p

181、otential to drive cost-effective delivery of ever more complicated marketing solutions.Our interview data suggests companies are making more progress in the early stages of the workfmow,most notably in the automated collection and ingestion of data,than they are in the later stages of insight genera

182、tion and action.That said,there is considerable variation by use case.Advertising platforms in particular have sophisticated tools for all stages of the campaign workfmow,from set-up and targeting to measurement and reporting.Similarly,businesses are at various stages of maturity in the shift from o

183、n-site to the cloud.Interviewees understand the power of the cloud,and describe cloud adoption as a critical factor in an organizations digital transformation strategy,which can help them innovate faster,scale tech capacity,secure data,and reduce environmental impact.However,half(48%)of businesses d

184、escribe data as still being stored wholly or mostly in their own data centers,and only 13%have fully transitioned to the cloud.23Theres so much heavy lifting to be done with a new technology,to have it fjt into our existing systems.That transition period,the cost but also the time and manpower invol

185、ved is the issue.”Director of Customer Insight,large US department store“22%Tech stackBusinesses are investing heavily to transition from legacy technologies to systems and platforms that are fjt for purpose in a world of advanced analytics,personalization,and automation.But many have a long way to

186、go.A worrying 26%still have solutions that require customer data to be integrated manually(think spreadsheets)and activated through stand-alone systems such as campaign platforms.A further third(32%)do have a platform to integrate data and analytics as needed,but this is largely ad hoc and batch pro

187、cessed.describe real-time,collaborative platforms that provide access for teams across the organization,and enable customer data to be captured,stored,analyzed,and acted on in real time.8Only40 19:Opportunities for automation across the CI pipelinePILLAR 4:OPERATIONS AND SUPPORT Strategy defjnedData

188、 unifjcationData collectionAutomationData governance application and privacy impact assessments conducted for data useData analyzed for patterns of likehood to churnSuggested actions(based on greatest ROI)defjnedUse case identifjed(personalize offers)KPIs agreed(reduce churn rate)Internal and extern

189、al data collectedData ingestedData merged between sourcesData mapped and matchedInsights visualized and shared with businessEngagement approach with customer adjustedInsight generationActionUse ML to identify churn risks and feed through to relevant team in real timeAutomate segmentation into differ

190、ent categories of churn risk in real timeAutomatically deliver offers based on which churn risk segment the user falls into(e.g.reduction in subscription cost for next 6 months)Ingest data into CRM or CDP platformAutomate blending of 1P,2P,and 3P data sets,where permissableConduct identity resolutio

191、nAutomate collection from multiple sources e.g.:Transaction data Customer center data 2P data41 Skills and capabilitiesModern CI requires cross-functional,multi-disciplinary teams.Almost three-quartersof businesses already employ a team with a diverse set of roles,ranging from data scientists and en

192、gineers,to developers,analysts,and strategists.There is high demand for specialists in predictive analytics and ML,and for insights professionals with a strong commercial focus.Half(49%)of businesses who are maturing or differentiating in the overall maturity framework describe their CI teams as hav

193、ing a strong product and business focus,compared to 4%of those who are exploring or developing.24A chronic shortage of talent in key areas means organizations are reliant on outsourcing,at least until they have built up capabilities internally via(often long-winded)recruitment or talent development

194、processes.In addition,some businesses outsource intentionally.The Head of Insight at one of the worlds major payment providers told us they prefer outsourcing,as it provides them with fmexibility and access to the best specialist skills.Despite these benefjts,most businesses(78%)favor a hybrid appro

195、ach between inhousing and outsourcing,allowing them to reduce costs and ensure alignment with business units.Many interviewees believe this model makes it easier to align workfmows to business units,and guarantee the speed and quality of data analysis,as well as reducing cost.2572%PILLAR 4:OPERATION

196、S AND SUPPORT 42 MaturityHigh MaturityTeam structure:center of excellence20%17%38%25%Skills and capabilities26%48%24%The consumer insight team is a center of excellence,working closely with various lines of the business(e.g.,product,marketing teams)The consumer insights function is an analytics team

197、 located within another team(e.g.,marketing fjnance)CI activities are undertaken by multidisciplinary team(s)with a strong commercial and product/service strategy focusThere is no consumer insight capabilityHigh Maturity FeaturesLow Maturity FeaturesExploringDevelopingMaturingDifferentiatingMost org

198、s are maturing their CI capability sits in multidisciplinary team(s)Most orgs are maturing their CI teams are centers of excellence,sharing best practicePILLAR 4:OPERATIONS AND SUPPORT Exhibit 20:Proportion of businesses with multidisciplinary CI functions,and examination of their structureThe major

199、ity of companies employ multi-disciplinary CI teams with a strong commercial and product focus,operating in centers of excellence43 The businesses that took part in our study employ a variety of structural approaches to delivering customer insight and analytics.7 These include:Decentralized models 2

200、0%of organizations say they operate decentralized insight and analytics teams within other teams or lines of business such as marketing.In many cases these teams grew organically.Centralized teams 17%say they have a stand-alone CI team,with its own management,and a further 63%have developed centers

201、of excellence,with a remit to share best practice across different areas of the business.Some companies treat CI and data analytics as separate functions and have different teams and potentially even a distinct Center of Excellence for each.Each model has perceived strengths and weaknesses.Decentral

202、ized models often grow organically within business units.On the plus side,they have a tight focus on the needs of that team.On the downside,organic growth in multiple teams can result in inconsistent method and quality,and duplication of effort and spend,for example with multiple technology solution

203、s.A centralized model can help with standardization and quality control but requires careful management to ensure the team remains focused on the needs of the wider business.Some adopt a hub and spokes approach where a lean center of excellence disseminates learning to CI professionals on the ground

204、.This central team might have responsibility for the technology,and own key performance data such as a central tracker,record of NPS,or other performance measurements.“Our customer intelligence lab functions as a Center of Excellence for the rest of the business.Otherwise we operate in silos.”Head o

205、f Insight,Technology CorporationPILLAR 4:OPERATIONS AND SUPPORT 4444 PILLAR 4:OPERATIONS AND SUPPORT Playbook:Building a Center of ExcellenceWe spoke to two business leaders who are implementing centers of excellence one for customer insight and one for analytics and AI.Both managers agree that the

206、center of excellence model is hard to get right but also that it offers the highest rewards if done well.The Head of Customer Insight at a major fjntech fjrm describes their team:“Weve been bouncing around for the last fjve years,from the fjnance team to the product team.Now we are a shared service,

207、reporting to the VP of strategy.”This new structure appears to work,in part because the team reports to a person at the commercial heart of the business:“Our VP of strategy plays a similar role to that of a chief commercial offjcer.For the fjrst time,we are focused on whatever the business sees as m

208、ost strategically important.We are engaged at the start of the product development lifecycle to help the company understand customer needs.”They go on to describe how they seek to maintain close links with teams across the business:“There are still multiple teams across the business who sit on custo

209、mer data and insight from social listening teams inside communications to specialist user experience teams inside the product team.Our role is to build established rhythms for our engagement with these teams regular meetings and a shared pipeline of work that we can all see and infmuence.This is our

210、 chance to standardize approach and output,reduce complexity,and provide a clear drumbeat of insight across the business.”A Chief Data Offjcer at a major healthcare company also describes being involved in the development of three different data and analytics centers of excellence over the past deca

211、de.The fjrst two failed because they were too isolated,and because the time to value was too long.When the center of excellence required money from business units to sustain development beyond the initial 24 months of funding,the units saw it as a cost center and refused to fund.The CDO told us:“My

212、focus now is on building capabilities that deliver value for the lines of business from day one.My team is populated by a mix of data scientists(mostly new arrivals)and members of the business units to build the strongest links possible.”We treat our work like a balanced investment portfolio.Some of

213、 it needs to show immediate returns,to prove our value to the business,but we also need longer term projects which behave like the equity markets and return sizable value over time.”Head of Data Science“ Key take-outsPILLAR 4:OPERATIONS AND SUPPORT Key take-outsImplement cloud-based,collaborative pl

214、atforms that enable customer insight to be accessed across the organization.A data platform should allowreal-time,collaborative access to customer data and should sit at the core of the solution.Migrate tech stack to the cloudto drive scalability,accessibility,and security.Automate entire workfmows,

215、not justat data collection and ingestion stages but also including insight generation and action.Build multidisciplinary teamsincluding data scientists,developers,analysts,and strategists.Outsource where needed to fjllgaps,particularly in shortage areas such as advanced analytics-while investing in

216、ongoing learning and development to grow and keep internal capabilities fresh.Establish a team structure that best suits your business model,with appropriate levels of centralization and standardization to maintain effjciency and quality control.Tech-stack Automation Skills and capabilities Center o

217、f excellence Key take- IMPLICATIONS world of customer intelligence is in a period of accelerated change Businesses today are under pressure from all sides to optimize their customer intelligence.Dated customer data strategies dont adequately serve empowered customers demand for personalized experien

218、ces in real time.Tightening privacy regulations are hampering organizations ability to deliver against these expectations using existing data strategies.Our study paints a picture of companies on a journey toward addressing these issues and taking advantage of the opportunities that innovations in a

219、nalytics and insights present.For those who get it right,customer intelligence can be a source of competitive advantage,helping them to predict key moments,such as what products and services they might or might not buy,or when they might churn off and build strategies to address this.ImplicationsWha

220、t does this mean for next steps?Every organization is different,in terms of its objectives and the data available to it.But core principles are true for all.At the heart of any strategy is a clear vision for what business decisions the insights are trying to inform,and what data is needed to provide

221、 these insights.Almost everyone will need a data platform to gather this in one place,and the ability to conduct whatever identity resolution and other analysis is required to understand the customer journey and needs.Most will want to make use of the kinds of advanced analytics that enable them to

222、look forward rather than just report retrospectively.As a fjrst step,those in the exploring category can start simply,perhaps by determining the data they need to drive immediate value,fjguring out how to access it,and implementing a platform to manage it.Those that are currently in the developing c

223、ategory might consider implementing enterprise identity to link data signals across and gain a single customer view.And those that are already maturing could look for ways to supplement their advanced analytics with AI or ML,or to share data with carefully chosen partners using a data clean room.Eve

224、n those at the differentiating stage will need to keep up with new technological and regulatory developments.To learn more about how to advance your brands customer intelligence,contact Acxiom at:47 IMPLICATIONS 21Embed CI and analytics into the decision-making of all key players around the Boardroo

225、m tablePut an enhanced CI and analytics strategy in place-real time,predictive,focused on innovationIncreased budget to support innovationConduct real time,automated data ingestion and merging/mappingCommunicate to customers the advantages of sharing 1P data,positioning it as a source of competitive

226、 advantageLeverage data clean rooms to ensure compliance with privacy regulations while gathering 2P dataUse predictive modeling(supplemented by ML/AI)to fjll gaps in customer journeys,predict customer behaviors and test and learnAllow customer intelligence to feed into processes at an earlier stage

227、,e.g.in product,where it can inform decisions about which products are developed,rather than how they are developedLocate all customer data storage/handling processes in the cloudConsider outsourcing ad hoc positions and invest in learning and development programs,to drive a talent pipelines and ret

228、ain talentStandardize approach and drive collaboration between the CI and other insight teams(e.g.via regular knowledge shares)Ensure CI and analytics has a Boardroom sponsorPut a CI and analytics strategy in placeAssign dedicated CI and Analytics budgetImplement an enterprise data management platfo

229、rmPerform data audit of 1/2/3P data and identify what is missing/what us unnecessaryAsk customers for permission prior to collecting 1P dataIdentify where advanced analytics can be applied to customer dataActivate customer intelligence and analytics in marketing functions e.g.to segment customers an

230、d target offersImplement a data platform,and start migrating data storage to the cloudEstablish a core team of CI resources(tech stack and analytics facing)Experiment with de/centralized CI team structuresEnsure CI and analytics has a seat at the Boardroom tablePut a strategic,forward-looking CI and

231、 analytics strategy in placePrioritize and protect budget,particularly through diffjcult economic circumstancesConduct cross-channel identity resolutionBolster 2P data through partnerships with data marketplaces and aggregation platformsMaintain transparency with customers about use of 1P dataFocus

232、on mainly predictive analytics,positioning CI as a contributor to strategyIdentify use cases for customer intelligence at points of interaction across the whole customer lifecycle,from marketing to operations and even internal processesImplement a technology stack which can automate date ingestion,t

233、reatment and analysis,and operate mostly in the cloudPrioritize hiring individuals with commercial backgrounds who can make use of the insightsDecide on a CI team structure,then work to embed knowledge of this team widelyExploring DevelopingExploring DevelopingDeveloping MaturingMaturing Differentia

234、tingA Roadmap to Advance Customer Intelligence48 SURVEY DEMOGRAPHICS and Sample BreakdownAcxiom partnered with research and strategy agency MTM to survey 200 business decision-makers from brands across the UK and the US to gain insight into levels of customer intelligence maturity.Survey participant

235、s are senior leaders in customer intelligence,experience,or related roles.Survey data is supplemented by six,60-minute,in-depth interviews with heads of customer intelligence,CMOs,and equivalent.Approximately,what was the annual revenue of your business in the last full fjnancial year?/$100m-499.9m/

236、$500m-999.9m/$1bnor more38%38%25%50%50%Which country do you work in?Which of the following best describes your organization?Predominantly B2C businesses53%Specialist17%Predominantly B2B businessesC-suite47%Senior manager,Director,VP,SVPC-suite73%C-suiteC-suite11%Which best describes your role?21 ind

237、ustries including:Retail18%Financial Services8%Tech11%Utilities5%Healthcare8%49 REFERENCES intelligence,2022:Most consumers want brands to personalizetheir communications.Link.2.Acxiom,2022:Beyond the Metaverse:CX Predictions for 2023.3.B2B Customer Intelligence Maturity Assessment Survey,QG1:“How m

238、uch doyou agree or disagree with the following statements in relation to your company?:Our consumer insight function is mainly focused on delivering the companys key commercial objectives;We maintain a single customer view across all channels;We maintain a single customer view,across all channels,an

239、d it is updated in real time;We carry out identity resolution;We utilise a customer data platform to combine and manage our customer data;We maintain a clear view of whereindividual customers are in their“journey”with us,and are able to target ourmarketing based on this view;We use customer data to

240、create personalisedexperiences for our customers;I am confjdent that our consumer insight solutions can help us overcome the challenges created by regulatory changes regarding privacy and cookies”4.B2B Customer Intelligence Maturity Assessment Survey,QB2:“At what level do you feel customer insight(C

241、I)is being actively championed?”5.B2B Customer Intelligence Maturity Assessment Survey,QD1:“Which of the following best describes the types and sources of data beingimplemented in the customer insight(CI)function at your company?”6.B2B Customer Intelligence Maturity Assessment Survey,QD5:“Which of t

242、he following would you say best describes the analytics capabilitiesat your company?”7.B2B Customer Intelligence Maturity Assessment Survey,QF3:“Which of the following would you say best describes the structure of theconsumer insight function(s)across your company?”8.B2B Customer Intelligence Maturi

243、ty Assessment Survey,QF4:“Which of the following best describes the technology solution your organisationuses to integrate and activate its customer data and analytical output?”9.and$revenues have been combined here for ease UK orgs were categorizedin the survey by 1bn,500m-999m and 100m-499m.10.Mck

244、insey,2020:The COVID-19 recovery will be digital:A plan for the fjrst 90 days.Link.11.Acxiom Responsible Marketing Report,B2B questionnaire,QC1:“To what extent has your organisation focussed on the following when setting policies for how personal data is collected,managed and used?”12.ONS website(20

245、22):Internet sales as a percentage of total retail sales:Link.50 REFERENCES CX Trends,QA7:“To what extent do you agree with each of the following statements about personalised shopping experiences?I would be more likely to buy from a brand that treated me as an individual”14.BCG study:Link.15.B2B Cu

246、stomer Intelligence Maturity Assessment Survey,Q C2:“How would you describe the trajectory of your budget for CI?”16.B2B Customer Intelligence Maturity Assessment Survey,Q C1:“Which of the following best describes the budget for customer insight(CI)in your organisation?”17.B2B Customer Intelligence

247、Maturity Assessment survey,Q D2:“How often would you say you are updating your customer data to make surethat it is accurate and up to date?”18.B2B Customer Intelligence Maturity Assessment survey,Q D3:“Which of the following apply to how data is stored and managed withinyour company?”19.Kinesso,202

248、2:A connected approach to the disconnected identity ecosystem.Link.20.Business intelligence is focused on reporting and querying,advanced analyticsis about optimizing,correlating,and predicting the next best action or the next most likely action.21.B2B Customer Intelligence Maturity Assessment surve

249、y,QE1:“How would you describe the analysis and insights provided by customerinsight data?”22.B2B Customer Intelligence Maturity Assessment survey,QE2:“Which of the following describe the areas within the business that consumerinsight analytics are used?”23.B2B Customer Intelligence Maturity Assessme

250、nt Survey Q D4:“How would you best describe the data storage philosophy of your company?”24.B2B Customer Intelligence Maturity Assessment Survey,Q F2:“Which of the following best describes the consumer insight capability acrossyour company?”25.B2B Customer Intelligence Maturity Assessment Survey,Q F

251、1:“Which of the following best describes the degree to which your teamsare in-house or sourced via partners?”51ABOUT is a strategy and insight agency specializing in media,entertainment and technology.We work with many of the biggest names in our sectors to deliver actionable insight,helping them to

252、 adapt,stay ahead,and thrive.Were a blend of award-winning researchers,commercial strategists,analysts and cultural trend junkies,all immersed in the modern digital world.Our research and strategy guides organizations from question to insight,from decision to action.And our long-term partnerships wi

253、th clients like Acxiom are something were incredibly proud of.Read more about us here:AcxiomAcxiom partners with the worlds leading brands to create customer intelligence,enabling data-driven marketing experiences that generate value for people and for brands.The experts in identity,the ethical use

254、of data,cloud-fjrst customer data management,and analytics solutions,Acxiom makes the complex marketing ecosystem work,applying customer intelligence wherever brands and customers meet.Acxioms Customer Intelligence Cloud(CIC)brings it all together,combining data,technology,and expert services so bra

255、nds can acquire the customers theyd love to have,grow trusted and valued customer relationships,and retain their best customers for today and tomorrow.CIC is a connected suite that includes identity solutions,data and audience insights,and analytics,integrated with leading marketing platforms and te

256、chnology partners,and supported by award-winning services.By helping brands genuinely understand people,Acxiom enables experiences so relevant and respectful,people are willing to explore new brands and stay loyal to those they love.For more than 50 years,Acxiom has turned the complexity of customer

257、 data into the simplicity of customer understanding,delivering better experiences for people and growth for brands.With locations in the US,UK,China,Poland,and Germany,Acxiom is a registered trademark of Acxiom LLC and is part of The Interpublic Group of Companies,Inc.(IPG).For more information on Acxiom and their Customer Intelligence Cloud,visit:A 06/24 US