predictive customer intelligence
DESCRIPTION
IBM Canada's Greg Milwid's presentation from the Smarter Business Summit in Montreal, Sept 17, 2014.TRANSCRIPT
1 #SmarterBiz
Smarter Decisions and Better Business Outcomes with Predictive Customer Intelligence
Greg MilwidProduct ManagementAnalytics [email protected]
© 2014 IBM Corporation2 #SmarterBiz
Agenda
• Why are we here?
• Predictive Customer Intelligence solution overview
• The IBM difference
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Age of the Empowered CustomerStay Relevant
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Anticipate and service my purchasing needs
Make it convenient and easy to interact with you
Be there when I need you, in real-time
Know me in context, remember all of our interactions
Empowered ConsumersDEMAND MORE FROM BRANDS
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Ensuring a positive customer experience is an enterprise-wide priority
Increase conversion, marginReduce sales cycle time
Increase brand preference, especially for customers with the greatest lifetime value
Improve customer satisfaction and loyalty
Enable flexible payment options based on need
Enable employee access to usable analytics
Hire capable employees and enable them with appropriate skills
Manage inventory and optimize supply chain
Understand the met and unmet needs
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Execute single view of the customer Develop integrated customer insight engine
Deploy spectrum of approaches to segmentation Adopt agile and connected approach to segmentation
Deliver seamless cross channel experience /digital/physical merge Got chat?
Architect customer experience Build an experience that connects emotionally
Providing the customer with the right offer, right time, right place, in real time if necessary
Right ServiceCustomer Service
Right PlaceOmni-Channel Optimisation
Right TimeCustomer Insight
Right CustomerCustomer Segmentation
How should the brand respond & redesign their customer experience?
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Key challenges uncovered
Difficult to deliver end-to-end customer analytics solution able to consume, integrate, analyze, score and determine most appropriate action with individual customer
Inability to gather and synthesize insights from analysis of social, text and transactional customer data to generate real-time information to predict customer sentiment and needs
Incomplete view of customer information at the time of interaction, resulting in inappropriate or incomplete offers, communications or both
Inconsistent service delivery and weak customer relationships, resulting in high churn
Lack of channel integration and siloed lines of business, causing inconsistent or tactical customer interactions
Focus on uncoordinated marketing offers — one-hit selling, as opposed to lifetime value
Challenged in using analytics to add short-term value or enhance long-term strategy
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Real-time marketing is a disruptive force to embrace now
“In 2013 we’ll see many more marketers take advantage of the power of real-time communications to grow business. In 2013, buyers instantly engage with brands on their websites, talk back via social media like Twitter and Facebook, and follow breaking news in the markets they are interested.
Clearly, the opportunities to grow your business in 2014 and beyond mean real time is key.
Success comes from engaging your buyers when they’re ready, not when it’s convenient for you.”
—David Meerman Scott, Real-Time Marketing & PR
© 2014 IBM Corporation9
“Predictive analytics helps connect data to effective action by drawing reliable conclusions about current conditions and future events.”
—Gareth Herschel, research director, Gartner Group
What is predictive analytics?
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Heads or Tails?
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Would you bet on it?
Toss # Outcome
1 Heads
2 Heads
3 Heads
4 Tails
5 Heads
6 Heads
7 Heads
8 Tails
9 Heads
10 Heads
11 Heads
12 ???
© 2014 IBM Corporation12
What if you had more data?
Toss # Person Wind Surface Humidity # Rotations Outcome
1 Person A Light Grass 40% 5 Heads
2 Person B Heavy Asphalt 70% 6 Heads
3 Person B Light Sand 55% 12 Heads
4 Person A Light Asphalt 55% 15 Tails
5 Person A Heavy Asphalt 76% 9 Heads
6 Person B Heavy Sand 35% 8 Heads
7 Person B Medium Grass 36% 8 Heads
8 Person B Light Grass 44% 3 Tails
9 Person A Heavy Sand 46% 7 Heads
10 Person A Medium Grass 41% 6 Heads
… … … … … … …
99 Person B Medium Grass 36% 8 Heads
100 Person A Medium Sand 76% 10 ?
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• Reduce operational costs• Improve asset productivity• Increase process efficiency
AccelerateTime to ValueAccelerateTime to Value
Big data, predictive and advanced analytics, decision management, scoring and business intelligence
Real-time capabilities Industry-specific samples: retail, telco,
insurance and banking IBM Interact, IBM Campaign and GBS
Lifetime Value Maximizer connectors Open architectureSingular
Software Capabilities (IBM SPSS, IBM Cognos Business Intelligence)
CustomizableCross-IBM, Software and GBS Solution (Analytics With Real-time Data Integration With CLTV)
Packaged Cross-IBM, Software Product (Analytics With Real-time Data, Connectors and Industry Samples)
2012
2013
Q22014
IBM Predictive Customer Intelligence Real-time, optimized recommendations at point of decision
Personalization with rich 360-degree view of customer
Exemplary customer experience — every interaction in context
New analytics offering for marketing, customer service and sales
© 2014 IBM Corporation14 #SmarterBiz
IBM Predictive Customer Intelligence drives optimized customer interaction at the point of contact based on predicted outcomes and behavior to achieve desired results
Loyalty and profitabilityTarget cross-selling and up-selling of
customers, based on loyalty and profitability, to grow customer
relationships
Churn and lifetime valueRespond to customer needs and sentiment during the engagement to proactively decrease churn, continuous CLTV calculations
Market-basket analysisTailored offers are targeted to a customer’s basket of existing or new goods and services—at the point of purchase for up-sell and cross-sell
Customer acquisitionIdentify and segment
customers, target them for profitable marketing and
acquisition efforts (wisdom of the crowd)
Offer optimizationDevelop offers, tailored to business objectives
and targeted to customer’s unique profile
Ma
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Ma
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Sal
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IBM Predictive Customer Intelligence key capabilities
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Chat
Voice Email
Social Media
Interactive Voice Response
Mobile Apps
Short Message Service
Web
IBM Predictive Customer Intelligence delivers intelligence to marketing and operational systems
Data IBM Predictive Customer Intelligence
IBM EMM/Third-party Marketing
Multichannel Customer Interactions
HOW?Interaction Data• Email and chat
transcriptions• Call center notes• Web click-streams• In-person dialogues
WHY?Attitudinal Data• Opinions• Preferences• Needs and desires
WHO?Descriptive Data• Attributes• Characteristics• Self-declared information• Geographic demographics
WHAT?Behavioral Data• Orders• Transactions• Payment history• Usage history
Acquisition Models
Campaign Response Models
Churn Models
Customer Lifetime Value
Lifetime Value Maximizer (GBS)
Market Basket Analysis
Price Sensitivity
Product Affinity Models
Segmentation Models
Sentiment Models
Up-sell/Cross-sell Models
IBM Predictive Customer Intelligence Available Both Inbound (Real Time) and Outbound (Batch)
Campaigns
Offers
Messaging
Lead Management
Cross-channel Campaign Management
Real-time Marketing
Marketing Event Detection
Digital Marketing
© 2014 IBM Corporation
Key Industry Use Cases
© 2014 IBM Corporation18
Millennial Female Shopper Lily is a good, long time shopper making a new move.She leaves her footprints in many places…
Lily
VT Living Marketing ExecutiveTasked with driving personalized offers and successful segment migration campaigns
John
VT Living Marketing AnalystRuns analysis on data to deliver actionable customer insightsMarketing needs to execute personalized messages and offers
Ann
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Lily launches VT Living app, browses the natural bamboo cutting boards and organic cotton sheets
Drops cotton sheets in her basket, but closes app without making a purchase
LilyLily browses products online, but does not complete the transaction
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Lily
Opt-in
Offer 1
Lily receives a conciergetext message at the entrance
Welcome to the Brooklyn store, Lily! We have the organic cotton sheets in the Your Home Department. Click here to view our Brooklyn Store layout for your convenience.
Offer 2
After wandering more than10 minutes in Your Home zone
Receive 10% off select Bamboo cutting boards. Valid today only!
Next day, Lily goes to the store
© 2014 IBM Corporation21
Lily
We appreciate your
business and would like to
offer you free 2 day express
shipping on home soda
makers. No more bottles
to recycle!
Email …
We appreciate your business and would like
to offer you free 2 day express shipping on
home soda makers. No more bottles to recycle!
Love VT Living for rewarding return customers. Thx for the deals #FavStore
Lily Gets a third offer later that evening at home
© 2014 IBM Corporation22
VT Living Marketing ExecutiveTasked with driving personalized offers and successful segment migration campaigns
John
VT Living Marketing AnalystRuns analysis on data to deliver actionable customer insights
Marketing needs to execute personalized messages and offers
Ann
LilyHow it works
© 2014 IBM Corporation23
PCI uses a breadth of data to build predictive models – that are used to determine the right action at the right time through the right channel
CoreMetricsPOS
SmarterCommerce
Big Insights(Hadoop)
PredictiveCustomer
Intelligence
PresenceZones
IBM Campaign/IBM Interact
ESP/eMessage
MetadataManager Publisher
AnalyticManager
Customer Insightsand Reporting
Lily
© 2014 IBM Corporation24
Real time scoring using contextual data to determine the right interaction – Lily’s location in the store, stock levels, promotions etc. Lily
• Last item browsed
• Discount response
• Passion for Eco-friendly products
• SMS offer response rate
• PZ focused shopper-N
10% Sample Predict Persona Next
PERSONA_NEXT_BEST_AC
Predict Persona Next Format Scored Data PERSONA_NEXT_BEST_AC
Opt-in
Receive 10% off select Bamboo
cutting boards. Valid today only!
Receive 10% off selectBamboo cutting boards.Valid today only!
Product, PromotionAvailability
© 2014 IBM Corporation25
Industry Vignettes
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Scenario 2: Real-time Offers and Cross-sell
• Anne’s product portfolio shows she recently bought a new home
• Recent spending patterns in her demand account and her bank card show she’s made a number of large household purchases recently
• Real-time transaction data shows Anne just purchased a kitchen appliance
Scenario 1: Optimizing Offers
• Pete called the bank contact center today to ask about loan processing times
• He checked mortgage rates on the bank website three times
• He tweeted for information on buying a second home
IBM Predictive Customer Intelligence in action: Banking
Bank Action
• Proactively sends Anne an offer to her smartphone for an increase in her credit line and a reduction in interest rate—while she is still shopping. This heads off possible card offers from retailers.
• Alerts Anne to the bank’s secure digital vault service by simply taking pictures of important documents with a smartphone
Bank Action
• Sends an offer to Pete, via his channel of choice, for a mortgage with special terms
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Scenario 1: Churn Reduction• Roger called the contact center today to talk about poor reception at his home• Roger has had 10 dropped calls in last week in his home area – that’s 10x the average of 1 dropped call per week!• Roger will be eligible for a new Smartphone under his contract in 6 months
IBM Predictive Customer Intelligence in action: Telco
Communications Service Provider (CSP) Action
• Customer service representative acknowledges the issue, apologizes to Roger for poor network service at his home, informs him of the estimated time for resolution of the issue
• CSR knows that the client is at risk of churning (due to PCI solution) and offers the client early upgrade to the latest Smartphone with a new signed contract (PCI solution recommendation).
• Roger accepts the offer, renews the contract for 2 years and is delighted at the exceptional service
Scenario 2: Improved Cross-sell / Up-sell • Sara changes jobs and starts consuming media content over 3G in the public transport• Sara tries 4G but decides not to subscribe to the Full High Speed Bandwidth for 4G Offer.
Communications Service Provider (CSP) Action
•CSP’s PCI solution suggests that Sara may like temporary 4G access. Based on Sara’s mobility profile (locations visited during the day, time spent at each location) & demographics, Sara is similar to Jane who utilizes high speed access during her commute to work on public transport.
•CSP offers Sara location based high speed access subscription to allow her to stream videos on the way and back from her using public transport (selected lines on partnered public transport network)
•The solution is custom-fit for Sara – Sara accepts the offer, CSP gets the additional revenue
© 2014 IBM Corporation28
IBM Differentiators
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IBM Predictive Customer Intelligence
What’s distinctive?
Cross-channel, real-time action• Including customer service, issue resolution, account management, response and billing, with
touchpoints managed in near–real time via appropriate channel
Decision management• Mature technology combining analytics and business-rules creation, integration and execution• Near-real-time recommendations beyond just marketing offers
IBM big data platform• Integration and management of the variety, velocity and volume of data• Phased approach for enhanced 360-degree customer view• Advanced analytics applied to information in its native form
Advanced analytics• Marketplace-leading tools for predictive and advanced analytics• Integrated optimization techniques that combine analytic output for the best answer
Multiple entry points• Analytics, decision and information management for quantitative starting points for next best
action project
© 2014 IBM Corporation30
Customer examples
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142 percent reductionin revenue erosion for customers at most risk of churning
$10 million+ savings/yearfrom increased retention and reduced customer service costs
5 months to achieve full return on investment
Solution components
The transformation: XO Communications had already taken the first steps in identifying customer retention risks through analytics; now it wanted to seize the opportunity to put these insights into action more effectively. By using IBM® SPSS® solutions to hone its predictive models, the company built a richer, more up-to-date picture of its client base and began delivering this data to a greater range of employees.
“We are only just starting to realize the true potential that IBM analytics holds across the business.”
— Bill Helmrath, Director of Business Intelligence, XO Communications • IBM® SPSS® Analytics Catalyst• IBM SPSS Modeler• IBM SPSS Modeler Server• IBM SPSS Statistics• IBM InfoSphere® BigInsights™
YTP03235-USEN-00
XO Communications takes control of customer satisfaction
© 2014 IBM Corporation32 #SmarterBiz
Communications provider C Spire Wireless uses predictive analytics and decision models to optimize cross-selling and prevent churn
Business Challenge ⏐ Outcompete the resource-rich wireless giants, C Spire Wireless needed to beat them at the small things that matter most: getting closer to customers and keeping them satisfied. Its challenge was to convert what it knows about customers into actionable insights that help account reps craft the optimal offers that meet their needs and head off customer dissatisfaction.
Smarter Solution ⏐ C Spire Wireless is using predictive models to examine the complexity of its customers’ behavior and determine which service mix is optimal for each customer’s need, as well as the indicators of imminent churn. By embedding these insights into its customer-facing processes, C Spire Wireless has empowered its reps to optimize their interactions with customers.
270% increasein cross-sales of
accessory products
Increased satisfaction by creating a more
personalized customer experience
50% increasein effectiveness of customer
retention campaigns
Excellent buy-infrom front-line crew
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Connecting more closely to customers
What should we offer this customer? • Use models to predict churn risk, propensity to respond to different offers
• Use rules to enforce eligibility, policy, and regulatory compliance
“We’re not only getting a more complete picture of our customers’ needs, we’re translating those insights into a higher-value customer experience.”
- Justin Croft, Manager of Brand Platforms and Analytics
Systems of recordPULSE database is constantly
updated with every customer interaction – including purchases,
demographics, and prior offers / responses
Systems of engagementPersonalize interactions across all touch points
Connect CRM, Web and mobile into one seamless experience
Point of Sale
Web
Call Center
SMS
© 2014 IBM Corporation34 #SmarterBiz
Next Steps
• Meet me in the Social Café to continue the conversation
• Find more information about Predictive Customer Intelligence at https://ibm.biz/BdFzCt
35 #SmarterBiz