predictive customer intelligence

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1 #SmarterBiz Smarter Decisions and Better Business Outcomes with Predictive Customer Intelligence Greg Milwid Product Management Analytics Solutions [email protected]

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IBM Canada's Greg Milwid's presentation from the Smarter Business Summit in Montreal, Sept 17, 2014.

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Page 1: Predictive Customer Intelligence

1 #SmarterBiz

Smarter Decisions and Better Business Outcomes with Predictive Customer Intelligence

Greg MilwidProduct ManagementAnalytics [email protected]

Page 2: Predictive Customer Intelligence

© 2014 IBM Corporation2 #SmarterBiz

Agenda

• Why are we here?

• Predictive Customer Intelligence solution overview

• The IBM difference

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© 2014 IBM Corporation3 #SmarterBiz

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

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“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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© 2014 IBM Corporation10

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 ???

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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

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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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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

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© 2014 IBM Corporation

Key Industry Use Cases

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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

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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

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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

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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

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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

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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

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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

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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

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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

Email

SMS

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Next Steps

• Meet me in the Social Café to continue the conversation

• Find more information about Predictive Customer Intelligence at https://ibm.biz/BdFzCt

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