big data, customer analytics and loyalty marketing

© 2013 IBM Corporation

What Travel Can Learn About Big Data,Social Media & Customer Analytics

WebinarNovember 14, 2013

Innovations from Retail

© 2013 IBM Corporation2

K

Kevin MayEditor & Moderator

Gene QuinnCEO & Producer

Your hosts


K

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]

mailto:[email protected]



K

Poll no. 1What role do you serve in the organization?


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


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


K

Poll no. 2What industry segment do you represent?


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


K

Poll no. 3When will your organization be in the engage

stage?


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


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

1

2

3

4

5

6

7

8

9

10

IT initiatives that can grow revenue and

increase customer intimacy


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


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


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)


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


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…


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


The Problem: You Face A Fragmented Solution Landscape


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


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

22

Result


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


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


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

25


Digital ambitions: CMOs want to put the components of a strong digital strategy in place

Source: IBM Institute of Business Value: CXO Study, 2013


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


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


K

Poll no. 4

What’s the major challenge holding back your adoption?


Thank You

Please Continue the Dialog

Kurt Wedgwood

Big Data Consultant

[email protected]

Tzaras Christon

EVP, Industry Sales & Marketing

[email protected]




K

Q & A


K

Thank You!

Replay and presentation from today’s webinar will be available at www.tnooz.com

Please send your questions to [email protected]

http://www.tnooz.com/


big data, customer analytics and loyalty marketing

Technology

ibm corporation

ibm institute

wedgwood big data consultant

big data adoption curvedata

customer attributes

transaction data arent

digital interaction

customer intimacy8