How are other leading organisations gaining marketplace advantage from their customer data? What has Big Data allowed them to achieve? How have they taken their customer insights and used it to go beyond traditional segmentation in order to deliver personalised offerings, improve marketing effectiveness and drive down churn? Join us for a lively session that takes a cross-industry look at different, real-world use-cases and the value that they have derived from their Big Data journey.

1. 1© Cloudera, Inc. All rights reserved.
Customer Insight @ Work
Mahdi Askari / System Engineer

2. 2© Cloudera, Inc. All rights reserved.
Customer targeting
 Leverage transactions
 Leverage interactions
 Personalized incentives for target
markets and inventories
 Deeply personalized
 Cross-sell & up-sell
 Extends across lines of business
 Leverages key partnerships
 “Brand, not channel”
Real-time offers
 Behavior-based
 Location-based
 Cross-platform (mobile, web, call
center, store, etc.)
 Inventory-based

3. 3© Cloudera, Inc. All rights reserved.
Provide in-game markets and virtual and real currency exchange
Store complete, granular in-game telematics for fraud detection & revenue management..

4. 4© Cloudera, Inc. All rights reserved.
Quick Look
• 2 to 3 years to a game.
• 275 million active users
• 50 TB of data daily
• A login/logout produce 80 metrics
• Data being collected:
• Interactions, durations, when, where,who.
• Use Cases
• Funneling- start,play,end
• Console vs Mobile
• Level designs – Heat maps, difficulty , order
• A/B testing
• Pick Performance Predication
• In game recommendation
• Fraud
• All departments using big data- developers, designers and etc..
• Technologies

5. 5© Cloudera, Inc. All rights reserved.
Collect coarse grained, low fidelity datasets during flight?
Enhance pre-flight and post-flight Customer experience and increase ancillary revenue.

6. 6© Cloudera, Inc. All rights reserved.
Quick Look
• Making money from “fees”! but no more my friend! Well, a little only..!!
• Use Cases:
• USA Base Airline:
• Build a data mart containing 150 factors and variables for customer
• 0.2 seconds to deliver customized offer to customer.
• Baggage tracking app to locate if where your bag is!
• ”A” British Airline:
• Every crew member equipped with an iPad containing:
• Your call center history, your complains
• Countries you travel, languages you speak, food you have ordered
• matching tweets from current and past flights,
• Tonal analysis of your conversations
• Allowing you to pick a “seat mate” based on FB and LinkedIn information pulled from social media
• "Scandinavian” Airline:
• Enable call center with , call history, other visits to other website, social interaction, customer baskets
• Pre-flight recommendation. Understand work vs leisure , family vs single, weather, offer alternatives based on past data, offer ATM
card activation for overseas, roaming activation
• Technologies

7. 7© Cloudera, Inc. All rights reserved.
Omnichannel Sales, Real-Time Personalization, Unified Customer Identify, Next Best Offer
Automate the creation and deployment of recommendation models based on customer behaviour

8. 8© Cloudera, Inc. All rights reserved.
Quick Look
• In US only it is 2.6 trillion business.
• 42 million Americans work in retail business.
• Use Cases:
• ”A” USA based chain retailer
• Social listening for trend forecasting. Black Friday, Cyber Monday, Boxing Day, Game releases, Console Releases and etc..
• Using NLP extracting information from social media web.
• Correlating social activity with in-store products. Baby shower register.
• Segment of one! They know about it first!!
• Game on! Which , what , where, how many,-> movie, ads, social, web browsing pattern, internal data, demographic, local buzz. 19% !
• UK Based global retailer
• In-depth analysis of customer browsing paths through the company’s online store/website
• Understanding Path to Purchase. Uncover 67% of purchase happens before first contact.
• Basket/cart assessment and segmentation of both online and point of sale (POS) data.
• Improving store layout based on basket/cart/day assessment.
• A pizza company
• Matching social data with customer data to offer on spot promotions.
• Matching local weather data and predicating outage and location data to offer in advance coupons and warning about an
outage and special price for delivery during the outage.
• Technologies

9. 9© Cloudera, Inc. All rights reserved.
What has the customer bought from us?
Are we about to lose this customer, what can we do to prevent this?

10. 10© Cloudera, Inc. All rights reserved.
Quick Look
• Massive amount of data- various sources. IPDR, CDR, PoS, Device Data, Profile Data, Location data, click stream
• They know us better than we do.
• Use Cases:
• French Telco:
• Where do I build next?
• “Mobile” shops around the city.
• Segmentation in customer call center- 61 segments- with different treatments. i.e. data user, roaming user, handset geek!
• Potential outage/pro-active reach.
• Location based , personalized promotion , minutes before you walk toward POS.
• A British Telecom
• Ingest 15x data .
• Reduce resolution time in call center.
• Increase first call closure %.
• Call router to “next best agent” depending on the customer profile and history and previous interactions.
• Very common use cases
• Churn,
• Network optimization
• Up-sell/cross-sell
• Technologies

11. 11© Cloudera, Inc. All rights reserved.
Q&A

12. 12© Cloudera, Inc. All rights reserved.
Thank You
Mahdi Askari
mahdi@cloudera.com