TABLE OF CONTENTS FOREWORD 4 KEY FINDINGS 6 ABOUT THE RESEARCH 6 CUSTOMER DATA ANALYTICS 7 MARKETING ATTRIBUTION CAPABILITY 20 CUSTOMER DATA AND GDPR 25 UNDERSTANDING EXTERNAL INFLUENCES 27 HARNESSING ARTIFICIAL INTELLIGENCE 30 SAS’ VIEWPOINT 33 ABOUT SAS 34 REFERENCES 35 FOREWORD Research by Gartner supports this, suggesting 89 percent of marketers will primarily compete on customerexperience instead of price in the coming years.1At the same time, the increased use of social mediaand mobile devices, combined with the burgeoningInternet of Things, is resulting in higher volumes ofincreasingly complex data being generated. For anorganisation to understand their customers and deliverrelevant and personalised experiences, they need toconsider the best way to analyse all of this data, extractuseful insights and action those insights in a timelymanner, even in real time where appropriate. Those organisations that can achieve this will realisesignifcant competitive advantage.McKinsey reveals that organisations using analytics toleverage customer behavioural insights outperformpeers by 85 per cent in sales growth, and more than 25per cent in gross margin.2 And there is evidence that many organisations arerecognising the competitive edge that analytics candeliver. According to research by Gartner, the biggest share of marketing budgets – 9.2 per cent –went to marketing analytics in 2017, indicating thatcustomer insight is a priority for Chief MarketingOfcers (CMOs).3 There is clearly a drive for improved customerexperience and more efcient use of resources throughuse of analytics, but there remains a broad spectrum ofanalytical capability – from organisations that are juststarting out using analytics to segment their customerbase, to ‘leaders’ that are deploying predictive analyticsand machine learning in real time. We were interestedto fnd out more about where organisations are on thisanalytical spectrum and, in particular, where they think they are. We also investigated organisations’progress in the adoption of Artifcial Intelligence (AI),given the amount of conversation and interest aroundthis technology. What is clear is that while many organisations arealready using analytics to enhance decision-making,there is signifcant opportunity to improve. Manyorganisations are still targeting broad audiencesand using analytics to report on the past rather thanfor predict the future; very few are able to capturerelevant data in a timely manner and fewer still haveany capacity to apply analytics to the data in real time.The net result is that they are making decisions basedon their customers’ ‘digital shadows’, working within anecho chamber. This means they are making decisions to and aboutcustomers based on an incomplete view of thosecustomers.Many organisations are not as far along theanalytical maturity curve as they would like to be whenit comes to delivering relevant customerexperiences.Three key business challenges are most often citedwithin the context of customer data and analytics: Tifany Carpenter Head of Customer Intelligence SAS UK & Ireland Over the last few years we’ve seen a major shiftfrom a product-based economy to an experience- based economy. Customers increasingly wantto do business with organisations on theirown terms. They demand fast, easy access toinformation and expect to receive relevant andpersonalised experiences that consider all thedata an organisation holds on them, regardlessof where and when they choose to engage. 4 。。。。。。