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Big Data, customer analytics and loyalty marketing
The webinar discusses how the travel and transportation industry can leverage big data, social media, and customer analytics, highlighting the adoption curve and the importance of understanding customer insights. It presents the opportunity to enhance operational efficiency while improving customer experiences, presenting solutions such as an analytic management platform to connect data sources and optimize marketing strategies. Key takeaways include the need for targeted initiatives to capture emerging trends and the fragmented landscape that necessitates a coordinated approach to analytics.
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Big Data, customer analytics and loyalty marketing
- 1. Innovations from Retail What TravelCan Learn About Big Data, Social Media & Customer Analytics Webinar November 14, 2013 © 2013 IBM Corporation
- 2. Your hosts K Kevin May Editor& Moderator 2 Gene Quinn CEO & Producer © 2013 IBM Corporation
- 3. Your panelists K Kurt Wedgwood Travel& Transportation Big Data Consultant IBM 3 Tzaras Christon EVP, Industry Sales & Marketing Aginity © 2013 IBM Corporation
- 4. Big Data forthe Travel & Transportation Industry Innovations from Retail: What Travel Can Learn About Big Data, Social Media & Customer Analytics Tzaras Christon EVP tchriston@aginity.com Kurt Wedgwood Big Data Consultant wedgwood@us.ibm.com © 2013 IBM Corporation
- 5. Poll no. 1 Whatrole do you serve in the organization? K 5 © 2013 IBM Corporation
- 6. Today's Objectives Objectives Agenda BenchmarkT&T adoption in Big 1. T&T: Big Data Adoption Curve Data Reveal leading edge learning from Retail Provide ideas for action 2. T&T: Focus & Need in Big Data 3. Retail Learning: Optimizing around the Customer Journey 4. Retail Learning: Real Challenges to Capturing the Value 5. Retail Learning: Analytic Management Platform 6. T&T: What’s next and how to get started 7. Q&A 6 © 2013 IBM Corporation
- 7. The Travel andTransportation industry is broad Railroads Freight Logistics Travel Related Services Airport Authorities Passenger Rail Maritime Container Shipping Hospitality Air Cargo Airport Management Companies Freight Rail Trucking Car Rental Airline Service Providers Airport Service Providers Passenger Terminals Parcel Delivery Global Distribution Systems (GDS) Freight Rail Terminals Logistics Service Providers Cruise Lines Ports and Terminals Travel Agencies / Tour Operators Airlines Airports Passenger Airlines Casinos 7 © 2013 IBM Corporation
- 8. Poll no. 2 Whatindustry segment do you represent? K 8 © 2013 IBM Corporation
- 9. A recent IBM/Oxfordstudy highlights how organizations are adopting big data Big data adoption Total respondents n = 1061 Totals do not equal 100% due to rounding 9 © 2013 IBM Corporation
- 10. Poll no. 3 Whenwill your organization be in the engage stage? K 10 © 2013 IBM Corporation
- 11. How much doesyour success rely on identifying and serving emerging trends in this new landscape 45 of the top 100 global cities will be in China by 2025, by real GDP growth 62% growth rate of unstructured data in the enterprise, vs. 22% overall enterprise data growth 80% of new applications will include cloud delivery or deployment 11 2:1 ratio of working age to dependent population in India, China, Japan, US, Europe; declining to ~1.5:1 by 2050 6.8 billion mobile phone subscriptions worldwide 90% of data on the planet was created in the past two years alone 93% growth in number of cyber attacks since 2005 16 petaflop computational speed of IBM Sequoia supercomputer 60% growth of spending on marketing analytics over the next 3 years © 2013 IBM Corporation
- 12. Retail companies havefocused on investments in growing new revenue and connecting with customers 1 2 3 4 5 6 7 IT initiatives that can grow revenue and increase customer intimacy 8 9 10 Source: IBM Institute for Business Value Analysis, “trends and Impacting technologies”, John Cato Gartner 12 © 2013 IBM Corporation
- 13. Travel & TransportImperatives Maximize availability of assets and infrastructure Dramatically improve the end-to-end customer experience. Travel & Transportation Improve operational efficiency and reduce environmental impact 13 Enhance services to increase revenue and manage capacity © 2013 IBM Corporation
- 14. The Opportunity: Optimizing thebusiness around the Customer Attributes that drive the Customer Journey Industry Point of View: CEO priority is Customer Insight 14 Our Experience: Optimizing on the Right Journey Attributes Yields >20% lift © 2013 IBM Corporation
- 15. Capabilities: 3 Quantum's CustomerExperience Optimization Identify Me Optimize the Touch Point/Execution Know Me Optimize your data Understand Me Optimize the Journey Purpose By Customer’s Personas Pleasure Pleasure Family Business (Solo) Business (Group) 15 © 2013 IBM Corporation
- 16. The Problem: Digital InteractionData is Growing Mobile Social 1.1B Smartphone Users +92% Y/Y Internet Usage >80% is App Usage Search Compare 972MM Users +8% Y/Y Gaming 130MM Users +15% Y/Y 16 Pinterest 17MM Users > +40x Y/Y 1.15B Users +41% Y/Y Commerce 51MM Users +25x Y/Y In-store Wireless Information Sharing 485MM Visitors +40% Y/Y 90% of Retails plan to improve the in-store experience with Wifi in the next 18 months © 2013 IBM Corporation
- 17. The Problem: Media, Customerand Transaction Data aren’t connected Millions Of Attributes in the Journey… Demographic data Attribut es Transacti ons ChainScale History Transaction data Guest Purchas es Demographics Characteri stics Booking time to Travel Needs Companion types E-mail / Chat Desires Call center notes Prefer ences Behavioral data 17 Opinion s Inperson dialogs Web clickstreams Interaction data But which ones are predictive of opportunity and risk? • • • • • Combination Weight Order Timing Execution Context © 2013 IBM Corporation
- 18. The Problem: Time Spenton Low Value Data Prep 1 Poor Customer Identification 2 Siloed Data by Function, Division or BU 3 IT waterfall dictates business agility 4 Analytics isolated to reporting or “in application” 5 Analysis is one off and not extensible to ultimate value 6 7 18 Disconnected from execution systems Scare analytic resources focused on overcoming IT hurdles Smart Analytics “There was a 15,000% increase in job postings for data scientists between summer 2011 and summer 2012, which spanned across all industries including retail, banking, healthcare and airlines” - HBR Sept 2012 © 2013 IBM Corporation
- 19. The Problem: You FaceA Fragmented Solution Landscape 19 © 2013 IBM Corporation
- 20. The Solution POS CoreMetrics Metadata Manager ESP/ eMessage Publisher Customer Insight Appliance(CIA) Communication Channels Campaign Management IBM Campaign/ IBM Interact An Analytic Management Platform (AMP) that connects a three dimensional view of your customer to marketing execution systems Smarter Commerce Data Sources Big Insights (Hadoop) Customer Analysis Analytic Manager Customer Insights and Reporting (Cognos) Presence Zones 20 SPSS Modeler © 2013 IBM Corporation
- 21. The Solution: Analytic ManagementPlatform – Ending Fragmentation CONNECTORS Corporate EDW Reporting and Customer Applications • Analytics running at 10X traditional methods Marketing Execution • 50% reduction in IT cost Big Insights • Full Connected in 90 days Customer Experience Management . 21 • Actionable Insights in 2 weeks Data Management Predictive Analytics © 2013 IBM Corporation
- 22. Example 1: LargeEyewear Retailer Challenge • The client lacked a 3D view into its customer and product purchases across 9 Retail Brands online and offline • Product, sales and customer data was managed by multiple agencies and vendors. Solution • CIA deployed to create a connected Analytic driven enterprise: All customer data sources, analytic functions and execution systems were connected in 89 days . • Now segments and scoring of customers down to the individual level isolating the most critical attribute to take action upon based on thousands of behavioral attributes Result Operational in 89 days • 3 countries • 10 years of customer data • 9 different retail brands • Custom KPI reports • All powered by a couple hundred indicative customer behavioral attributes 22 22 © 2013 IBM Corporation
- 23. Example 2: FindingAttributes that drive your business CIA Standup Predicting 95% of Path to Purchase: 3 Weeks 3 Brands: 4 Products 5 data sources 1710 total attributes (150 predictors) 3 weeks to load data, create attributes, rank, model and score Iterative adaptation with no data silos Data mapping and load Create Attributes 23 Rank Attributes Implementation Timeline Create Interaction Reports and Attribute Heat Maps Model Purchase Paths Plot Audience on Purchase Paths © 2013 IBM Corporation
- 24. Predicative Patterns thatdrive Prescription Purchased Model x Automobile 1 95% of Model X Purchasers Follow 1 of 4 Paths 61-90 days 65% 46-60 days Price sensitivity 31-45 days Unique models attribute Model Focus 16-30 days Peak sessions* 11-15 days Sessions drop 6-10 days Sessions flat 0-5 days Session peak Large number of makes and models viewed, search on new and used, consider used brand 12% Purchased model Brand Sessions drop Session, Search and view volume NonDealer sites Purchased model Narrow number of makes and models, very low brand interaction 9% Unique model views, pric e High search, views, unique models Search, vi ew, model s, price Search, v iews Product Price sensitive throughout search, visiting all dealers 9% Search volume, 1st time views Search, unique models Search, view, dealers Search, vi ews, Price High view count, Looking at all dealers * Red text indicates make/model decision point 24 © 2013 IBM Corporation
- 25. Example 3: ApparelRetailer - Segmentation and Optimization During Peak Season Challenge Solution Benefits Blanket Marketing lacked relevance and effective conversion Aginity/IBM CIA System: Multiterabyte Customer Marketing Solution with clickstream data (Omniture), sales and customer data 200-400% increased conversion Relevance: Over 200,000 unique offers, increasing conversion and retention Met Holiday Targets: Retailer executed on promise to positively impact the holiday season bottom line Needed quick project setup to hit projections in fast-approaching Holiday season Online project had been stalled for 5 months in jeopardy of missing deadlines 25 25 2 5 $14MM+ revenue in 4 weeks over holiday 79 Day Implementation © 2013 IBM Corporation
- 26. Digital ambitions: CMOs wantto put the components of a strong digital strategy in place Source: IBM Institute of Business Value: CXO Study, 2013 26 © 2013 IBM Corporation
- 27. Voice over theboard: CEOs say customers come second only to the C-suite in terms of the strategic influence they wield “As customers gain more power over the business via social media, their expectations keep rising and their tolerance keeps decreasing.” – CIO, Retail Source: IBM Institute of Business Value: CXO Study, 2013 27 © 2013 IBM Corporation
- 28. Taking the nextstep with your strategy and execution Big data adoption Educate Explore Engage Execute Focused on knowledge gathering and market observations Developing strategy and roadmap based on business needs and challenges Piloting big data initiatives to validate value and requirements Deployed two or more big data initiatives and continuing to apply advanced analytics Join the business community Big data case studies, whitepapers, book s, and IBM Institute for Business Value reports ibmbigdatahub.com Blog http://www.ibm bigdatahub.co m/blog/author/ kurt-wedgwood Self-paced learning, exploration with downloads & test environment BigDatauniversity.com, YouTube Big Data Channel IBM Readiness Assessment for Big Data -Prioritized business use cases -Recommend big data platform Solution Design & Custom Demo -Validate business value of the big data use case -Demonstrate big data capabilities to execute use case Enterprisewide big data initiatives -Incremental value across multiple use cases -Leverage investment from re-using the same big data platform -Enterprise data platform to support analytics Join the technical community 28 © 2013 IBM Corporation
- 29. Poll no. 4 K What’sthe major challenge holding back your adoption? 29 © 2013 IBM Corporation
- 30. Thank You Please Continuethe Dialog Tzaras Christon EVP, Industry Sales & Marketing Big Data Consultant tchriston@aginity.com 30 Kurt Wedgwood wedgwood@us.ibm.com © 2013 IBM Corporation
- 31. Q&A K 31 © 2013 IBMCorporation
- 32. Thank You! Replay andpresentation from today’s webinar will be K available at www.tnooz.com Please send your questions to kevin@tnooz.com 32 © 2013 IBM Corporation
Editor's Notes
- #6 Thank you Gene and Kevin for the introductions and to all of you for taking this hour out to join the webinar.To Open, we just wanted to share with everyone who is in the audience. Using you keyboard would you please answer the poll?
- #9 upd
- #11 We’d like to do our own Poll, here and see how it compares
- #14 Doing a quick switch from retail to T&T, I wanted to call out what IBM has defined as our major Trav & Trans imperatives that are represented in one or many of our clients major strategic intiatives:Maximize availability of assets and infrastructureDramatically improve the end-to-end customer experience.Improve operational efficiency and reduce environmental impactEnhance services to increase revenue and manage capacityAs in the prior slide, we will focus on the customer, and you should know that BigData&analytics is central to all 4 of these imperatives.Tzaras, would you take our lead in going further into the Dramatically improve the end-to-end customer experience?
- #18 Do we want to highlight the predictive prescriptive bubbles?Specify which data lives in the Corp DW & what is in the Mrkting DWAttributes
- #21 Dark Gray = CIABlue = Connected systemsCIA is a marketing hub that brings disparate systems togetherWe are highlighting integration with a select list. This is A list of connections, not THE list of connections.Advance to see a list of typical integration pointsThe next slide is a duplicated slide to make the animations work right. If changes are made here, we will want to duplicate them there.
- #24 Line through representing CIA that pulled everything together.
- #26 Consider changing order in solution column…also what did they really do?
- #27 Tzaras, thank you for the great examples. I believe you really captured how other companies are differentiating themselves in this enriched world of customer information.Tying to your last example, In IBM’s CXO study, we found that CMOs (across industries) are currently working on integrating cross channel to capture all customer interaction and proactively reachout through all touchoints, the use analytics for customer insight, and the use of social networks to foster collaboration beyond brand development to new channels, business models and products/services.Note the numbers don’t ad up, missing today – 3 years. And the first one adds over 100%.
- #28 The CMO, and now the CEO, are really adjusting their ways as, the voice of the customer is being not only heard, but invited into the organization in new ways.In fact, In IBM’s 2013 CXO study, theCEOs told us that customers come second only to the C-suite in terms of the strategic influence they wield. When asked, “Who has the most influence on your strategic vision and business strategy?” 55 percent of interviewed CEOs cited customers. This not only underscores the need to act now, but the amount of process change that is happening across all industries.
- #29 So, we have shared a lot. We To better understand the big data landscape, we asked respondents to describe the level of big data activities in their organizations today. The results suggest four main stages of big data adoption and progression along a continuum that we have labeled Educate, Explore, Engage and Execute.In each of these stages, IBM has offerings to help you on your journey.Educate: Building a base of knowledge (24 percent of respondents)In the Educate stage, the primary focus is on awareness and knowledge development. Almost 25 percent of respondents indicated they are not yet using big data within their organizations. While some remain relatively unaware of the topic of big data, our interviews suggest that most organizations in this stage are studying the potential benefits of big data technologies and analytics, and trying to better understand how big data can help address important business opportunities in their own industries or markets. Within these organizations, it is mainly individuals doing the knowledge gathering as opposed to formal work groups, and their learnings are not yet being used by the organization. As a result, the potential for big data has not yet been fully understood and embraced by the business executives. IBM offerings: IBM BIG DATA HUB – the Big Data Hub is intended to be your source for information, content and conversation regarding big data analytics for the enterprise – filled with whitepaper, books, videos, customer case studies, etcIBM Briefings and Solution Centers – face to face opportunity for big data education and ability to bring your business and IT team together to get on the same page about big dataBig data University and YouTube Big Data channel – learn at your own pace – downloads, test environment and sandboxExplore: Defining the business case and roadmap (47 percent)The focus of the Explore stage is to develop an organization’s roadmap for big data development. Almost half of respondents reported formal, ongoing discussions within their organizations about how to use big data to solve important business challenges. Key objectives of these organizations include developing a quantifiable business case and creating a big data blueprint. This strategy and roadmap takes into consideration existing data, technology and skills, and then outlines where to start and how to develop a plan aligned with the organization’s business strategy. IBM Offering – IBM can come in and do a Big Data workshop briefing to help your business team prioritized the best use cases to apply big data based on impact to the business from a strategic, business value and TCO standpoint. Likewise IBM can recommend the big data platform that will support the business use casesIN SOME CASES, where your business has already identified the business use case, we can proceed with helping you design the solution and prove it out in a Proof of ConceptEngage: Embracing big data (22 percent)In the Engage stage, organizations begin to prove the business value of big data, as well as perform an assessment of their technologies and skills. More than one in five respondent organizations is currently developing POCs to validate the requirements associated with implementing big data initiatives, as well as to articulate the expected returns. Organizations in this group are working – within a defined, limited scope – to understand and test the technologies and skills required to capitalize on new sources of data. IBM offering: Proof of Concept is an important stage – for IBM this does NOT mean experiments and test environments. Instead it is helping clients after they’ve identified the business use case to have their big data environment, with IBM’ value add technologies on top of hadoop, to have this big data platform supporting their business environment. It is an important validation and learning phase before clients deploy across multiple use cases and across the enterpriseExecute: Implementing big data at scale (6 percent)In the Execute stage, big data and analytics capabilities are more widely operationalized and implemented within the organization. However, only 6 percent of respondents reported that their organizations have implemented two or more big data solutions at scale – the threshold for advancing to this stage. The small number of organizations in the Execute stage is consistent with the implementations we see in the marketplace. Importantly, these leading organizations are leveraging big data to transform their businesses and thus are deriving the greatest value from their information assets. With the rate of enterprise big data adoption accelerating rapidly – as evidenced by 22 percent of respondents in the Engage stage, with either POCs or active pilots underway – we expect the percentage of organizations at this stage to more than double over the next year. IBM VALUE: Only IBM has the full breadth of big data platform to support analytics needs across the enterprise and across multiple business use cases. We have the platform to support the operational requirement of big data business use cases, ability to scale as volume of data grows, variety of types of data to handle real-time and the need to have visibility and trusting the data that the big data platform provides.