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Big Data, customer analytics and loyalty marketing

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Want to improve the customer experience while optimizing customer service, marketing spend and wallet share?

In this FREE webinar from Tnooz and IBM, attendees learn the benefits of big data analytics including:

Developing persona-level customer segmentation.
Improving products/services launches.
Optimizing return on marketing spend.
Utilizing social media analytics.

Webinar presenters are:

Kurt Wedgwood – information agenda consultant for travel and transportation, IBM
Tzaras Christon – executive vice president for growth, Aginity
Kevin May - editor and moderator, Tnooz
Gene Quinn - CEO and producer, Tnooz

Published in: Technology, Business
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Big Data, customer analytics and loyalty marketing

  1. 1. Innovations from Retail What Travel Can Learn About Big Data, Social Media & Customer Analytics Webinar November 14, 2013 © 2013 IBM Corporation
  2. 2. Your hosts K Kevin May Editor & Moderator 2 Gene Quinn CEO & Producer © 2013 IBM Corporation
  3. 3. Your panelists K Kurt Wedgwood Travel & Transportation Big Data Consultant IBM 3 Tzaras Christon EVP, Industry Sales & Marketing Aginity © 2013 IBM Corporation
  4. 4. Big Data for the 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. 5. Poll no. 1 What role do you serve in the organization? K 5 © 2013 IBM Corporation
  6. 6. Today's Objectives Objectives Agenda  Benchmark T&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. 7. The Travel and Transportation 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. 8. Poll no. 2 What industry segment do you represent? K 8 © 2013 IBM Corporation
  9. 9. A recent IBM/Oxford study 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. 10. Poll no. 3 When will your organization be in the engage stage? K 10 © 2013 IBM Corporation
  11. 11. How much does your 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. 12. Retail companies have focused 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. 13. Travel & Transport Imperatives 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. 14. The Opportunity: Optimizing the business 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. 15. Capabilities: 3 Quantum's Customer Experience 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. 16. The Problem: Digital Interaction Data 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. 17. The Problem: Media, Customer and 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. 18. The Problem: Time Spent on 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. 19. The Problem: You Face A Fragmented Solution Landscape 19 © 2013 IBM Corporation
  20. 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. 21. The Solution: Analytic Management Platform – 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. 22. Example 1: Large Eyewear 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. 23. Example 2: Finding Attributes 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. 24. Predicative Patterns that drive 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. 25. Example 3: Apparel Retailer - 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. 26. Digital ambitions: CMOs want to put the components of a strong digital strategy in place Source: IBM Institute of Business Value: CXO Study, 2013 26 © 2013 IBM Corporation
  27. 27. Voice over the board: 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. 28. Taking the next step 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. 29. Poll no. 4 K What’s the major challenge holding back your adoption? 29 © 2013 IBM Corporation
  30. 30. Thank You Please Continue the Dialog Tzaras Christon EVP, Industry Sales & Marketing Big Data Consultant tchriston@aginity.com 30 Kurt Wedgwood wedgwood@us.ibm.com © 2013 IBM Corporation
  31. 31. Q&A K 31 © 2013 IBM Corporation
  32. 32. Thank You! Replay and presentation from today’s webinar will be K available at www.tnooz.com Please send your questions to kevin@tnooz.com 32 © 2013 IBM Corporation

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