DATA-DRIVEN MARKETING AND ADVERTISING A GLOBAL PERSPECTIVE

Transcription

1 DATA-DRIVEN MARKETING AND ADVERTISING A GLOBAL PERSPECTIVE 1

2 Jodie Sangster, CEO, ADMA Jonathan Margulies Managing Director, Winterberry Group Marek Rucinski, Managing Director, Accenture Interactive 2

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4 Use the text box at the end of the presentation to ask questions

5 DATA DRIVEN MARKETING AND ADVERTISING Data = feedback. Enables rich customer insights. Allows for hyper-targeted messaging, offers and content that drive response. A means of learning about changing markets in real time. An omnipresent customer survey evolving us toward a customer-centric approach to doing business. Data-driven marketing and advertising is a means of putting data to work; leveraging a wide range of channels delivering creative content that s appropriate to each, in order to establish and grow relationships with consumers. 5

6 SESSION OBJECTIVES Rise of data driven marketing and analytics Paths to mastery of data driven marketing analytics Activating analytical talent 6

7 THE GLOBAL REVIEW of Data-driven Marketing and Advertising Explores the role of data-driven marketing and advertising across 17 countries from more than 3,000 practitioners. N = 3,053 Panelists 7

8 THE RISE AND RISE AND RISE OF DATA 92% say data is growing in importance to marketing and advertising 63.2% say spending up over last year 73.5% predict further growth

9 DATA IS DIGITAL. DIGITAL IS DATA Major shifts in channel spend

10 CUSTOMER-CENTRICITY IS DRIVING DDMA Factors responsible for driving investment

11 AROUND THE WORLD TALENT IS THE BIG ISSUE Respondents that believe that better skilled talent would generate value from DDMA Global Panel Argentina Australia Belgium Brazil France Germany Hungary India Ireland Italy Netherlands New Zealand Singapore South Africa Sweden United Kingdom United States 28.3% 29.3% 42.1% 41.7% 34.7% 39.1% 40.4% 41.9% 45.5% 50.0% 53.3% 52.2% 51.5% 46.5% 61.1% 57.8% 62.1% 61.9%

12 TALENT AND TECHNOLOGIES What resources would help drive DDMA most

13 HYBRIDS WANTED Most valued skillsets for DDMA investment

14 Source: iapa.org.au/article/2014iapaskillsandsalarysurveyresults

15 SESSION OBJECTIVES Rise of data driven marketing and analytics Paths to mastery of data driven marketing analytics Activating analytical talent 15

16 5-stage Maturity Model for Analytics Analytical master fully competing on analytics 5 Analytical Competitors Data insight drives all decisionmaking Google Analytics Founding father of retail analytics Tesco trials transactional in-store kiosks Build broad Analytic capability analytics for differentiation 4 Analytical Practitioners Analytics recognised as a separate business unit Business Sphere Use analytics to improve distinct capability Use analytics to improve one or more functional activities 3 Analytical Aspirations 2 Localised Analytics Pioneers of telco data monetisation (Precision Market Insights) Implementing single source of truth RFID Drink Dispensers: Coke Freestyle Pockets of localised analytics capability Market optimisation for 30% uplift with SAS Get accurate data to improve operations 1 Analytical Novice This document makes descriptive reference to trademarks that may be owned by others. The use of such trademarks herein is not an assertion of ownership of such trademarks by Accenture and GDMA and is not intended to represent or imply the existence of an association between Accenture and/or GDMA and the lawful owners of such trademarks. Pockets of localised analytics capability Kraft foods listening to social media to inform product placements 16

17 DELTA Model path to industralisation of Data Driven Marketing DATA 1 Analytical 2 Localised 3 Analytical 4 Analytical 5 Novice Analytics Aspirations Practitioners Inconsistent, poor quality and unstandardized data; difficult to do substantial analysis, no groups with strong data orientation Standardized and structured data, mostly in functional or process silos; senior executives do not discuss data management Key data domains identified and central data repositories created Integrated, accurate, common data in central repositories; data still mainly an IT matter, little unique data Analytical Competitors Relentless search for new data and metrics leveraging structured and unstructured data (e.g. text, video); data viewed as a strategic asset ELEMENTS OF THE MODEL Quantitative Methods Tools & Technology ENTERPRISE LEADERSHIP Mostly ad hoc, simple math, extrapolation, trending Desktop technology, standard office packages No enterprise perspective on data or analytics; poorly integrated systems Little awareness of or interest in analytics Basic statistics, segmentation database querying, tabulations of key metrics are leveraged to gain insights Basic statistics, database querying, tabulations Islands of data, technology, and expertise deliver local value Local leaders emerge but have little connection Simple predictive analytics, classification and clustering; dynamic forecasts Enterprise platforms and predictive analytical packages Process or business unit focus for analytics; infrastructure for analytics beginning to coalesce Senior leaders recognize importance of analytics and developing analytical capabilities Advanced predictive methods deployed to discover insights; advanced optimization, sentiment analytics, text and image analytics Cloud-based Big Data Key data, technology and analysts managed from an enterprise perspective Senior leaders develop analytical plans and build analytical capabilities Neural nets, genetic algorithms, advanced machine learning Prescriptive analytics and cognitive computing Key analytical resources focused on enterprise priorities and differentiation Strong leaders behave analytically and show passion for analytical competition TARGETS No targeting of opportunities Multiple disconnected targets, typically not of strategic importance Analytical efforts coalesce behind a small set of important targets Analytics centered on a few key business domains with explicit and ambitious outcomes Analytics integral to the company s distinctive capability and strategy ANALYTICAL TALENT Few skills which are attached to specific functions Unconnected pockets of analysts; unmanaged mix of skills Analysts recognized as key talent and focused on important business areas Highly capable analysts explicitly recruited, developed, deployed, and engaged Leading edge professional analysts; cultivation of analytical amateurs across the enterprise DIFFERENT LEVEL OF MATURITY 17 Copyright 2015 Accenture. All rights reserved

18 SESSION OBJECTIVES Rise of data-driven marketing and analytics Paths to mastery of data driven marketing analytics Activating analytical talent 18

19 Analytics talent integration into the fabric of the organisation 1% Sponsors Drive the vision Lead analytical and data initiatives 5-10% 15-20% 60-70% Scientists Apply analytics methods to solve business challenges Build models, algorithms and visualisations Experts Apply analytical models to improve business decisions Link insights to business realities and process Specialists Put the output of analytical models to work Provide tactical level direction and execution 19 Copyright 2015 Accenture. All rights reserved

20 THE NEW HYBRID ANALYST = 20

21 Analytical Unicorns & Hybrids vs. power of Teams Leading companies are relying more on analytical teams vs. unicorns Team size varies from a handful of people to ten, twenty or more people for on going work On business side, teams can include quantitatively oriented analysts and visualisation designers Some of these roles may already exist, but it can be difficult to identify and free up the talent Systems Architect Quantitative Analyst Skillsets: Software Engineer Low Med Visualization Designer Business Analyst Data Scientist Advanced Analytics Business Acumen Communication & Collaboration Creativity Data Integration Data Visualisation Software Development Systems Administration High 21 Copyright 2015 Accenture. All rights reserved

22 3 KEY ANALYTICS INTEGRATION ARCHETYPES Distributed Hub and Spoke Centralized Enterprise Central Analytics Business Units Corporate Centers Enterprise Analytics Business Unit Analytics Corporate Center Analytics Basic Analytics / Reporting Intermediate Analytics Advanced Analytics Tools / Processes / Governance Analytical Data Pros Business has control of resources / investments Analytics resources have better understanding of business opportunities Flexibility in resource allocation to optimise productivity Accommodates varying levels of analytics maturity across enterprise Common standards, tools, and sharing of leading practices All analysts reside in a central unit enabling flexible resourcing Reduced variance in Insight development and application Minimal duplication of work effort Cons Resource constraints based on capacity and skills Disjointed and duplicative work efforts Inconsistent quality across business units Difficult to set enterprise-wide priorities Lack of career path development Potential contention for resources Potential independent analytics efforts by spokes if hub can not meet demand Creates distance between analysts and the business lessening business acumen Loss of control over analytics resources within business groups lower trust levels WHERE? Complex business structure Immature reporting and analytics capabilities Autonomous business units or complex business structure Advanced analytics need specialised knowledge Straightforward business structure Less time critical requirements Mature reporting and analytics capability 22 Copyright 2015 Accenture. All rights reserved

23 TREND TOWARDS HUB & SPOKE MODEL Centralised Model Analytics Operating Model Trend & Level of Maturity Convergence towards Hub & Spoke model driven by: Hub &Spoke Model Distributed Model Shift from functional to cross-functional analytics Increasing pace of technology innovation Scarcity of analytics talent Need for more complex and real time solutions ANALYTICAL NOVICE LOCALISED ANALYTICS ANALYTICAL ASPIRATIONS ANALYTICAL PRACTICIONER ANALYTICAL COMPETITORS 23 This document makes descriptive reference to trademarks that may be owned by others. The use of such trademarks herein is not an assertion of ownership of such trademarks by Accenture and GDMA and is not intended to represent or imply the existence of an association between Accenture and/or GDMA and the lawful owners of such trademarks. Copyright 2015 Accenture. All rights reserved

24 Challenges to scaling data driven & analytics capabilities Leadership - Leadership will get greater transparency and will use it to micromanage my function. Mindset - Leadership today grew up using instinct to drive decision making due to the lack of timely actionable insight. Culture - Unwritten rules around how information is used in an organisation Information as a power broker to pocket-veto decisions. Always have the answer to senior management s questions. Comfort in nebulous data as a means to avoid accountability. Education - Needs to have context and be targeted to level of maturity and intent focus on content, process and technology in that order. Behavioural Change - This typically takes 4 6 months to bed down once deployed Think Differently + Act Differently = Drive Different Outcomes. Governance - Necessary and sufficient minimalist approach - organisational, content and business process focus. Copyright 2015 Accenture. All rights reserved

25 How to scale data driven and analytics capabilities. 1. Be an analytical leadership role model 2. Experiment! 3. Think BIG 4. Ask smarter questions and question conventional wisdom 5. Identify and seek out valuable data and then generate NEW insights 6. Identify factors that lead to stronger business performance to make it REAL 7. Develop integrated analytics vision business priorities, structure, talent, tools and data 8. Prioritise efforts on high value challenges solve real problems to prove the value 9. Embed analytics broadly and deeply throughout the enterprise 10. Continue to push the boundaries DO NOT SETTLE! Copyright 2015 Accenture. All rights reserved

26 Q & A 26

27 Our content experts For further information or to learn more, please contact: Jodie Sangster CEO, ADMA & Chair, GlobalDMA Marek Rucinski, Managing Director, Accenture Interactive Australia, New Zealand and Asia Pacific lead for the Digital Marketing and Analytics Practice Jonathan C. Margulies Managing Director Winterberry Group LLC 27

28 Our organisations About GlobalDMA The GlobalDMA is an organisation that represents, supports and unites marketing associations from around the globe that focus on data-driven marketing. It leads worldwide initiatives aimed at providing marketers with global trends, thought leadership and know-how on data-driven marketing and advertising across all sectors, disciplines and channels. In excess of 30 affiliate organisations are part of GDMA. Collectively, they represent a significant proportion of the world's major brands, corporations, suppliers and agencies. Through its members associations, the GlobalDMA provides access to the world's largest network of datadriven marketing organisations and influencers. About Accenture Accenture is a global management consulting, technology services and outsourcing company, with more than 319,000 people serving clients in more than 120 countries. Combining unparalleled experience, comprehensive capabilities across all industries and business functions, and extensive research on the world s most successful companies, Accenture collaborates with clients to help them become high-performance businesses and governments. The company generated net revenues of US$30.0 billion for the fiscal year ended Aug. 31, Its home page is Accenture, its logo, and High Performance Delivered are trademarks of Accenture. Accenture Digital Accenture Digital, comprised of Accenture Analytics, Accenture Interactive and Accenture Mobility, offers a comprehensive portfolio of business and technology services across digital marketing, mobility and analytics. From developing digital strategies to implementing digital technologies and running digital processes on their behalf, Accenture Digital helps clients leverage connected and mobile devices; extract insights from data using analytics; and enrich end-customer experiences and interactions, delivering tangible results from the virtual world and driving growth. Learn more about Accenture Digital at 28

29 Our organisations cont. About Winterberry Group Winterberry Group is a unique strategic consulting firm that supports the growth of advertising, marketing, media and information organizations. Our services include: Corporate Strategy: The Opportunity Mapping strategic development process helps clients prioritize their available customer, channel and capability growth options, informed by a synthesis of market insights and intensive internal analysis. Market Intelligence: Comprehensive industry trend, vertical market and value chain research provides in-depth analysis of customers, market developments and potential opportunities as a precursor to any growth or transaction strategy. Marketing System Optimization and Enterprise Data Strategy: Process mapping, marketplace benchmarking and holistic system engineering efforts are grounded in deep industry insights and real-world understandings with a focus on helping advertisers, marketers and publishers better leverage their core assets. Mergers & Acquisitions Due Diligence Support Services: Company assessments and industry landscape reports provide insight into trends, forecasts and comparative transaction data needed for reliable financial model inputs, supporting the needs of strategic and financial acquirers to make informed investment decisions and lay the foundation for valuefocused ownership. Additionally, Winterberry Group is differentiated through its affiliation with Petsky Prunier LLC, the leading investment bank serving the technology, media, and marketing, e-commerce and healthcare industries. Together, the two firms provide one of the largest and most experienced sources of strategic and transactional services in their addressable markets. For more information, please visit

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