big data, customer analytics and loyalty marketing
DESCRIPTION
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, TnoozTRANSCRIPT
© 2013 IBM Corporation
What Travel Can Learn About Big Data,Social Media & Customer Analytics
WebinarNovember 14, 2013
Innovations from Retail
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Kevin MayEditor & Moderator
Gene QuinnCEO & Producer
Your hosts
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Kurt WedgwoodTravel & TransportationBig Data ConsultantIBM
Your panelists
Tzaras ChristonEVP, Industry Sales& MarketingAginity
© 2013 IBM Corporation
Innovations from Retail: What Travel Can Learn About Big Data, Social Media & Customer Analytics
Big Data for the Travel & Transportation Industry
Kurt WedgwoodBig Data Consultant [email protected]
Tzaras [email protected]
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Poll no. 1What role do you serve in the organization?
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Objectives Benchmark T&T adoption in Big Data
Reveal leading edge learning from
Retail
Provide ideas for action
Today's Objectives
Agenda
1. T&T: Big Data Adoption Curve
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
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Airlines Airports Railroads Freight LogisticsTravel Related
Services
Passenger Airlines
Airport Authorities Passenger Rail
Maritime Container Shipping
Hospitality
Air CargoAirport
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
Casinos
The Travel and Transportation industry is broad
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Poll no. 2What industry segment do you represent?
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Big data adoption
Total respondents n = 1061Totals do not equal 100% due to rounding
A recent IBM/Oxford study highlights how organizations are adopting big data
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K
Poll no. 3When will your organization be in the engage
stage?
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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
2:1 ratio of working age to dependent population in India, China, Japan, US,
Europe; declining to ~1.5:1 by 2050
90% of data on the planet was created in the past
two years alone
16 petaflop computational speed
of IBM Sequoia supercomputer
6.8 billion mobile phone subscriptions worldwide
60% growth of spending on marketing analytics over the next 3 years
93% growth in number of cyber attacks
since 2005
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Retail companies have focused on investments in growing new revenue and connecting with customers
Source: IBM Institute for Business Value Analysis, “trends and Impacting technologies”, John Cato Gartner
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IT initiatives that can grow revenue and
increase customer intimacy
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Dramatically improve the end-to-end
customer experience.
Improve operational efficiency and reduce environmental impact
Enhance services to increase revenue and
manage capacity
Travel & Transportation
Travel & Transport Imperatives
Maximize availability of assets and infrastructure
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The Opportunity: Optimizing the business around the Customer Attributes that drive the Customer Journey
Our Experience: Optimizing on the Right Journey Attributes Yields >20% liftIndustry Point of View: CEO
priority is Customer Insight
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Pleasure
Pleasure Family
Optimize the Journey PurposeBy Customer’s Personas
Optimize your data Optimize the Touch Point/Execution
Capabilities:3 Quantum's Customer Experience Optimization
Identify Me Know Me Understand Me
Business (Solo)
Business (Group)
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The Problem: Digital Interaction Data is Growing
1.15B Users+41% Y/Y
Social
972MM Users+8% Y/Y
Search
1.1B Smartphone Users
Mobile
485MM Visitors+40% Y/Y
Information Sharing
130MM Users+15% Y/Y
Gaming
51MM Users+25x Y/Y
Commerce
17MM Users> +40x Y/Y
PinterestReview
Play
Pause
Record
Preview
Browse
Compare
+92% Y/Y Internet Usage>80% is App Usage
In-store Wireless
90% of Retails plan toimprove the in-store experience with Wifi in the next 18 months
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The Problem: Media, Customer and Transaction Data aren’t connected
Transactions Chain-
Scale History
Guest Purchas
es
Booking time to Travel
Companion types
E-mail / Chat
Call center notes
Web click-
streamsIn-
person dialogs
Opinions
Preferences
Desires
Needs
Characteristics
Demo-graphics
Attributes
Demographicdata
Transactiondata
Interactiondata
Behavioraldata
But which ones are predictive of opportunity and risk?
• Combination• Weight• Order • Timing • Execution Context
Millions Of Attributes in the Journey…
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The Problem: Time Spent on Low Value
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 Disconnected from execution systems
7 Scare analytic resources focused on
overcoming IT hurdles
Data Prep
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
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The Problem: You Face A Fragmented Solution Landscape
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Communication Channels
Customer Analysis
CustomerInsight Appliance (CIA)
An Analytic Management Platform (AMP) that connects a three dimensional view of your
customer to marketing execution systems
CoreMetrics
SmarterCommerce
Big Insights(Hadoop)
PresenceZones
SPSSModeler
IBM Campaign/IBM Interact
ESP/eMessage
MetadataManager Publisher
AnalyticManager
Customer Insights and Reporting
(Cognos)
POS
Data Sources
Campaign Management
The Solution
© 2013 IBM Corporation21 Predictive Analytics
The Solution: Analytic Management Platform – Ending Fragmentation
CONNECTORS
Big Insights
Marketing Execution
Data Management
Customer Experience
Management.
Reporting and Customer
Applications
Corporate EDW
• Analytics running at 10X traditional methods
• 50% reduction in IT cost
• Full Connected in 90 days
• Actionable Insights in 2 weeks
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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
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
Example 1: Large Eyewear Retailer
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Result
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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
Example 2: Finding Attributes that drive your business
CIA Standup Predicting 95% of Path to Purchase: 3 Weeks
Data mapping and load
Create Attributes
Rank Attributes
Model Purchase Paths
Create Interaction Reports and Attribute Heat Maps
Plot Audience on Purchase Paths
Implementation Timeline
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Automobile 195% of Model X Purchasers Follow 1 of 4 Paths
Purchased Model x
Non-Dealer sites
Purchased model
Session, Search
and view volume
16-30 days31-45 days
Unique models attribute
46-60 days
High search, views, unique models
Search, view,
models, price
Unique model views, price
Price sensitivity
Model Focus
Peak sessions*
Purchased model
65%
12%
9%
61-90 days
Sessions drop
11-15 days
Sessions flat
6-10 days
Session peak
0-5 days
Large number of makes and models viewed, search on new and used, consider used brand
Narrow number of makes and models, very low brand interaction
Sessions drop
Search, views
Price sensitive throughout search, visiting all dealers
Search volume, 1st time views
9%Search, unique models
Search, view,
dealers
Search, views, Price
High view count, Looking at all dealers
* Red text indicates make/model decision point
Predicative Patterns that drive Prescription
Brand
Product
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Example 3: Apparel Retailer - Segmentation and Optimization During Peak Season
Challenge
Blanket Marketing lacked relevance and effective conversion
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
Solution
Aginity/IBM CIA System: Multi-terabyte Customer Marketing Solution with clickstream data (Omniture), sales and customer data
Relevance: Over 200,000 unique offers, increasing conversion and retention
79 Day Implementation
Benefits
200-400% increased conversion
$14MM+ revenue in 4 weeks over holiday
Met Holiday Targets: Retailer executed on promise to positively impact the holiday season bottom line
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Digital ambitions: CMOs want to put the components of a strong digital strategy in place
Source: IBM Institute of Business Value: CXO Study, 2013
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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
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ExecuteDeployed two or more big data initiatives and continuing to apply advanced analytics
EngagePiloting big data initiatives to validate value and requirements
ExploreDeveloping strategy and roadmap based on business needs and challenges
EducateFocused on knowledge gathering and market observations
Big data adoption
Learn the technology & gain expertise
Validate and realize business value Enterprise-wide 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
Big data case studies, whitepapers, books, andIBM Institute for Business Value reportsibmbigdatahub.com
Join the technical community
Blog
IBM Readiness Assessment for Big Data -Prioritized business use cases- Recommen
d big data platform
Solution Design & Custom Demo- Validate business value
of the big data use case
- Demonstrate big data capabilities to execute use case
Self-paced learning, exploration with downloads & test environmentBigDatauniversity.com, YouTube Big Data Channel
Join the business community
Taking the next step with your strategy and execution
http://www.ibmbigdatahub.com/blog/author/kurt-wedgwood
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Poll no. 4
What’s the major challenge holding back your adoption?
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Thank You
Please Continue the Dialog
Kurt Wedgwood
Big Data Consultant
Tzaras Christon
EVP, Industry Sales & Marketing
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Q & A
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Thank You!
Replay and presentation from today’s webinar will be available at www.tnooz.com
Please send your questions to [email protected]