Research Presentation: How Numbers are Powering the Next Era of Marketing
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This document discusses how numbers and data are powering the next era of marketing. It notes that nearly 4 in 10 CMOs say they do not have the right tools and resources to meet their marketing objectives. Companies are turning to providers like Accenture Interactive to bring together full marketing solutions using consulting, technology, and analytics. The CMO agenda is being disrupted by the explosion of data from sources like mobile devices, social media, and the internet of things. This data needs to be captured, analyzed, and used to optimize marketing interactions and drive continuous discovery. Strong collaboration between marketing and IT is needed to take advantage of big data technologies and manage various data environments.
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Research Presentation: How Numbers are Powering the Next Era of Marketing
- 1. Accenture Interactive How Numbers are Powering the Next Era of Marketing
- 3. Copyright © 2012 Accenture. All rights reserved. 3 Intro Hypothesis Opportunities New Rules Context Storyline
- 4. Evolution of the CMO Agenda Nearly 4 in 10 CMOs1 say they do not have the right people, tools and resources to meet their marketing objectives. This is a 5% drop in preparedness from Accenture’s 2011 study. Companies are increasingly turning to non-traditional marketing service providers such as Accenture Interactive to bring together the full end- to-end solution (consulting, technology and analytics) that drives key outcomes globally and locally. Accenture Interactive is the marketing services arm of Accenture addressing the CMO and CIO business challenges to help clients achieve both marketing effectiveness and efficiency. 1Based on the 2012 Accenture Interactive CMO Insights survey of more than 400 senior marketers from 10 countries.
- 5. CMO Agenda is Being Disrupted by Technology Data Explosion • Unstructured data is doubling every 3 months • 2011 saw 47% growth overall • Driving greater emphasis on data innovation Economics • Commodity priced storage and compute • Emergence of open source and big data technologies solving production problems at scale • Enable bringing analytics to the data Data Mobilization • Novel approaches to analyze unstructured data creating shorter time from data to insight • Shift towards data consumption in multiple environments (business apps, mobile, social) Data Led Innovation • De-coupling data from applications • Disparate external data shaping context • Cost effective mobilization of massive scale data
- 6. Data Explosion: Today’s World is Defined By Data Things From the human Genome to Smart Meters, From Set-Top-Boxes to Social Networks, every click, every search, every swipe and every like is captured and stored and analyzed and monetized…
- 7. Data Explosion: Mobile COMMUNICATIONS There are 7 Billion PEOPLE With over SIX BILLION PHONES Wikipedia APPS We will download over 70B apps – TEN for every human ABI LOCATION Smart phones are continuously pinging GPS, WIFI and cell towers M-COMMERCE Will grow to $31B with the entire funnel of data from search and advertising to Conversion being captured
- 8. Data Explosion: Content (Audio, Video, Images) Video, Audio, Text and Images streaming over the internet, IPTV & Cable TV are the most obvious types of content. But medical images, traffic cameras, CCTV, satellite are among the growing sources of content.
- 9. Data Explosion: The Internet of Things • The Environment • Industry • Places • People Sensable Scanable Payable Wearable Drivable Flyable
- 10. Stakes are higher: Amongst marketing strategy issues, customers are at the top for the third year in a row (improving acquisition, retention and sales). Copyright © 2012 Accenture. All rights reserved. 10 Very Important 2012 CMO Insights – Market Context Q 2a&b The top 3 marketing issues also have the highest difficulty levels. New strategy areas (e.g. the end-to-end customer experience, enabling relevant marketing, using data for real-time marketing) have high levels of importance. Importance levels have also increased for efficiency related factors such as reducing costs of the marketing workforce and non-payroll marketing costs. * New items included in 2012 ** Slight word change Global Top 3 Very Difficult
- 12. Copyright © 2012 Accenture. All rights reserved. 12 Intro Hypothesis Opportunities New Rules Context Storyline
- 13. Brand is the Organizing principle of people, process and technology of the organization.
- 14. Copyright © 2013 Accenture. All rights reserved. 14 BRAND Measurement and Value is going to be richer, more refined and more reactive due to Big Data technologies
- 15. “The battle in marketing will remain the same – a battle for consumers’ trust. Trust is built on honesty, openness and consistently taking the consumer’s side. […] the world revolves around the consumer – and that won’t change.” Sir Terry Leahy, Chief Executive, Tesco plc 250 ms Copyright © 2013 Accenture All rights reserved. 15
- 16. Copyright © 2013 Accenture. All rights reserved. 16 Because BRAND VALUE can be destroyed in 250MS Brand has the Biggest Risk from Outlier Behavior Big Data Analytics are Designed to find Outliers and Unseen Patterns
- 17. Copyright © 2012 Accenture. All rights reserved. 17 Intro Hypothesis Opportunities New Rules Context Storyline
- 18. Marketing Analytics Revolution If you can’t access data, you can’t explore it. Failure to explore data is a missed-opportunity that can cost valuable initiatives that competitors may discover and exploit before you have the opportunity. Data Liberation.How does liberateddata drive value in our organization? Efficiencyat scale. The majorityof time spent by predictivemodelersisaround data preparation. Fluidframeworks helpreduce the amount of time they spendpreparingthe data sothey canfocusondevelopingmodels. Fluid Frameworks.Where do we see the value in clean frameworks? Data Rich Environments. Where do we see value in rich data? A simple algorithm can do a lot with rich data. With stagnant data, at some point, algorithms converge at finite value.
- 19. Copyright © 2013 Accenture. All rights reserved. 19 Brand Management Use Cases Reputation Monitoring Brand Relevance Brand Fraud Brand Advertising Brand Energy Brand Extensions Data Aggregation Pattern Matching Outlier Analysis Pathing Real-Time Analytics Text Analytics
- 20. 20 TEXT ANALTYICS Sentiment analytics is used to analyze what is being communicated. While Text analytics may count words or identify keywords, Sentiment seeks to understand the gist of what is being said. With social media growing in importance analyzing customer conversations to find key topics, trends and meaning is critical. • Word Frequency • Word Distance • Passion / Intent • Change of Text over Time
- 21. 21 TIME SERIES Time series allow us to order data across time. • Sessionization • Customer journey • Conversion funnels • Multi-touch attribution
- 22. 22 GRAPH ANALYTICS • Customer Connections • Market Baskets • Decision Trees • Single Shortest Path
- 23. Copyright © 2012 Accenture. All rights reserved. 23 Intro Hypothesis Opportunities New Rules Context Storyline
- 24. Copyright © 2013 Accenture. All rights reserved. 24 BRAND IT WikiCommons
- 25. Big Data in Marketing Level 1 Awareness / Pain
- 26. Big Data in Marketing W F M N A P C S ! X ? O B A MOBILE SEARCH E-COMMERCE & WEB BRAND PRODUCT MARKETING CMO MARKETING ANALYTICS SOCIAL PRESS CUSTOMER EXPERIENCE MARKETING SCIENCE MARKETING RESEARCH MARKETING OPERATIONS ADVERTISING Level 2: Big Data Channels
- 27. Big Data in Marketing W F M N A P C S ! X ? O B A MOBILE SEARCH E-COMMERCE & WEB BRAND PRODUCT MARKETING CMO MARKETING ANALYTICS SOCIAL PRESS CUSTOMER EXPERIENCE MARKETING SCIENCE MARKETING RESEARCH MARKETING OPERATIONS ADVERTISING Level 3: External Solutions MONITORING
- 28. Big Data in Marketing W F M N A P C S ! X ? O B A MOBILE SEARCH E-COMMERCE & WEB BRAND PRODUCT MARKETING CMO MARKETING ANALYTICS SOCIAL PRESS CUSTOMER EXPERIENCE MARKETING SCIENCE MARKETING RESEARCH MARKETING OPERATIONS ADVERTISING Level 4: Optimizing Interactions MONITORINGOPTIMIZATION
- 29. COMPANYLO GO BIG DATA IN MARKETING ORGANIZATION BIG ANALYTICS W F M N A P C S ! X ? O OPTIMIZATION MONITORING DISCOVERY B A MOBILE SEARCH E-COMMERCE & WEB BRAND PRODUCT MARKETING OFFICE OF CMO MARKETING ANALYTICS SOCIAL PRESS CUSTOMER EXPERIENCE MARKETING SCIENCE MARKETING RESEARCH MARKETING OPERATIONS ADVERTISING Big Data in Marketing Level 5: Continuous Discovery
- 31. Copyright © 2012 Accenture. All rights reserved. 31 Embed Algorithms Align Marketing
- 32. Copyright © 2012 Accenture. All rights reserved. 32 Intro Hypothesis Opportunities New Rules Context Storyline
- 33. Copyright © 2012 Accenture. All rights reserved. 33
- 34. Marketers Need IT to Masters Many Different Data Environments PrivateData • Data Created inside the Enterprise • The structure, design and manage-ment of this data is controlled by users PaidData • Data bought from third parties to enhance analytics • The structure, design and manage-ment is controlled by contract PublicData • Data created or shared by third parties such as social networks or government. • The structure and design is not controlled
- 35. Accenture Technology Vision 2013 Relationships at Scale Design for Analytics Data Velocity Seamless Collaboration
- 36. 36Copyright © 2012 Accenture. All rights reserved. Rethinking the CMO / CIO Relationships • Drive IT Investment in Big Data • Design your Interactive Data Collection for Analysis • Enhance measurement of Offline Channels • Reduce Data Friction in your systems keep up with your customers and the Market. • Take Advantage of Big Data Technologies to • Collaboration between IT and Marketing
- 37. Brand is the Organizing principle of people, process and technology of the organization.
- 38. Copyright © 2012 Accenture. All rights reserved. 38
Hinweis der Redaktion
- That represents some BIG challenges that needs to be addressed, but according to our2012 Accenture Interactive CMO Insights survey of more than 400 senior marketers from 10 countries, nearly 4 in 10 CMOs say they do not have the right people, tools and resources to meet their marketing objectives. This is a 5% drop in preparedness from Accenture’s 2011 study.All these new digital devices are creating new channels that need to be integrated, managed and optimized to provide a seamless, engaging and RELEVANT consumer experienceand huge amounts of BIG data – that needs to be analyzed to drive actionable insights. Companies are realizing that they need to bring the CMO and CIO functions together and are increasingly turning to non-traditional marketing service providers such as Accenture Interactiveto bring together the full end-to-end solution (consulting, technology and analytics) that drives key outcomes globally and locally.Accenture Interactiveis the marketing services arm of Accenture addressing the CMO and CIO business challenges to help clients achieve both marketing effectiveness and efficiency.Accenture Interactive helps the world’s leading brands drive superior marketing performance across the full multichannel customer experience. Working with over 4,000 Accenture professionals dedicated to serving the marketing function, Accenture Interactive offers integrated, industrialized and industry-driven marketing solutions and services across consulting, technology and outsourcing powered by analytics.
- There are many use cases for marketers in Sentiment Analytics given the increase of social conversations, customer engagement and interactive channels such as Chat and E-mail. Firms are seeking to automate listening to customers to understand their relationship with brands, products and services – and how they share their experience with the social marketplaceBeyond the brand, marketers can better understand the Voice of the Customer, Promoter vs. Haters, and pick up signals from individual customers about their experience.
- Time Series is a fundamental capability that .has been beyond the reach of marketers without a big data analytics solution. As we seek to tie together the customer journey across touch points – we naturally run into different systems that have usually been in a different silo – web sites and call center data for instance. If we want to understand the customer experience from the customer’s point of view, we need to deply technologies that can easily tie together the customer journey across technologies. Customers quickly move from social to mobile, from search to websites, from online to in-store. Marketers have been limited by their own technologies from becoming customer centric.
- Frequently we reduce the value of a social network down to a series of connections. However for a marketer Graph Analytics hold incredible predictive power especially for acquisition and retention modeling. Customers tend to cluster into groups that somewhat similar. People who travel internationally know other travelers. Connected groups have similar spending patterns – and brand or product movement of one part of a network can signal coming changes with the rest of the network. For marketers, this does not have to be highly predictive – even a low level of confidence can be used to build lift in acquisition – or identify potential risks in churn.