A Marketer’s Guide To Customer Analytics: People, Processes & Technology - 24 June 2013 - IBM...

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© 2013 IBM Corporation A Marketer’s Guide To Customer Analytics: People, Processes and Technology Srividya (Sri) Sridharan, Analyst - Customer Insights, Forrester Research Marygrace Bateman, Market Manager, IBM July 24, 2013

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A marketers guide to customer analytics people processes and technology A Marketer’s Guide To Customer Analytics: People, Processes & Technology Presentation Slides Webinar: IBM and Forrester 24 June 2013 Srividya Sridharan Analyst Serving Customer Insights Professionals Forrester Research Marygrace Bateman Market Manager IBM Heather Clancy Award-winning Business Journalist Webcast - http://goo.gl/Rld3T5

Transcript of A Marketer’s Guide To Customer Analytics: People, Processes & Technology - 24 June 2013 - IBM...

Page 1: A Marketer’s Guide To Customer Analytics: People, Processes & Technology - 24 June 2013 - IBM Presentation Slides  - PDF

© 2013 IBM Corporation

A Marketer’s Guide To Customer Analytics: People, Processes and Technology

Srividya (Sri) Sridharan, Analyst - Customer Insights, Forrester Research

Marygrace Bateman, Market Manager, IBM

July 24, 2013

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© 2013 IBM Corporation

Speakers

3

Marygrace Bateman Market Manager

IBM @bateman_mg

Srividya (Sri) Sridharan

Analyst - Customer Insights

Forrester Research

@Srividya

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#big data and marketing

What‟s trending now?

#customer analytics

#strategy #people

#strategy #process

#strategy #tech & services

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© 2013 IBM Corporation

2+

billion

people on

the Web

by end

2011

30 billion RFID

tags today

(1.3B in 2005)

4.6

billion

camera

phones

world wide

100s of

millions

of GPS

enabled

devices

sold

annually

76 million smart

meters in 2009…

200M by 2014

12+ TBs

of tweet data every day

25+ TBs of log data

every day

? T

Bs o

f d

ata

eve

ry

day

Current business and technology trends

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© 2013 IBM Corporation

The uncertainty of new information is growing alongside its complexity

2010

9000

2015

Sensors & Devices

VoIP

Enterprise Data

Social Media

8000

7000

6000

5000

4000

3000

Source: IBM Global Technology Outlook 2012 IBM source data is based on analysis done by the IBM Market Intelligence Department. IBM Market Intelligence data is provided for illustrative purposes and is not intended to be a guarantee of future growth rates or market opportunity

We are here.

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© 2013 IBM Corporation

Under preparedness Percent of CMOs selecting as “Top 5 Factors”

Data explosion 71%

Social media 68%

Channel & device choices 65%

Shifting demographics 63%

Financial constraints 59%

Decreasing brand loyalty 57%

Growth markets 56%

ROI accountability 56%

Customer collaboration 56%

Privacy considerations 55%

Global outsourcing 54%

Regulatory considerations 50%

Corporate transparency 47%

Need for change to deal with data explosion and social media Percent of CMOs indicating high/significant need

Invest in technology

Understand analytics

Collaborate with peers

Validate ROI

Address privacy

Integrate insights

Rethink skill mix

73%

69%

65%

64%

52%

49%

28%

Source: IBM’s 2011 Global CMO Study: From Stretched to Strengthened (2011)

IBM Global CMO Study: CMOs underprepared for new market dynamics

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“What enterprise areas does your big data initiative address?”

Base: 60 IT professionals

(multiple responses accepted) Source: June 2011 Global Big Data Online Survey

Marketing leads the enterprise in Big Data initiatives

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#customer analytics

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What is Customer Analytics?

Customer analytics solutions (technology, software, or

services) allow firms to analyze customer data to optimize

customer decisions and use the analytical insight to design

customer-focused programs and initiatives that drive

acquisition, retention, cross-sell/upsell, and targeted

marketing campaigns.

Some examples of customer-focused applications of

analytics include customer segmentation, targeting,

customer profitability analysis, next-best-offer analysis,

profiling, and customer attrition assessment.

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A regional bank uses uplift response modeling to generate incremental sales for direct deposit acquisition campaign.

Image source: http://abcnews.go.com/

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A financial services firm uses cross-sell and next-best action models to personalize offers at the point of customer interaction.

Image source: http://www.gunster.com/practice/banking-and-financial-services/

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Customer analytics drives value across the life-cycle

Source: July 29, 2011, “How Analytics Drives Customer Life –Cycle Management” Forrester report

WHO to acquire/retain?

HOW MUCH to spend?

WHEN to target?

WHAT to offer?

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Customer analytics use is acquisition-heavy

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Segmentation and targeting is bread and butter for analytics users…..NBA, social, loyalty would be icing on the cake

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#customer analytics

#strategy #people

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Expert User Casual User

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Marketing scientists must now translate „geek‟ to „Greek‟

Marketing scientists

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© 2013 IBM Corporation

Product Marketing ...can identify the best performing micro-segments for a new product offering

Brand Manager...can understand and quantify exactly how social media is affecting my business and the brand

CMOs ...can deliver personalized and consistent value across all channels at any time to all customers

Demand Generation ...can always deliver the customer the right offer at the right time at the right place

Marketing Operations ...can understand which programs were best performing across any touchpoint or segment

Applying analytics to specific marketing functions So that…

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© 2013 IBM Corporation

IBM SPSS Analytic Catalyst Demo

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#customer analytics

#strategy #process

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Four core activities define the customer analytics process

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Production Consumption &

Activation

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Identify the level of insights sharing across the organization

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© 2013 IBM Corporation

Gains a 360 degree view of customers to drive cross-brand, targeted marketing campaigns The Opportunity

Redcats, a retail group in France that includes 17 major retail brands around the world, wanted to deepen the customer experience across its brand websites by understanding how customers behave online. Each brand was already collecting an enormous amount of data from both online channels and stores, but no one had a complete, cross-brand view of customers.

4 Core Activities to Enable Customer Analytics Process:

Data Management: near-real-time stream of customer data is collected and stores in central database (purchases, click streams, mobile app usage, online surveys, store transactions)

• Reduced data processing times by 90%

Redcats

Analytics Production: sophisticated statistical and predictive analytics used to analyze patterns in

customer behavior and demographics and use them to predict how customers will behave in the future

• Higher conversion rates due to rich understanding of why customers buy

Analytics Consumption: analysis tools available to statisticians and brand managers to gain insight into

cross-brand efforts; solution integrated in CRM

• Monitors customers tendencies and detects patterns in behavior used to predict response

Analytics Activation: analysis enables marketing teams to run personalized marketing campaigns

• Gained full payback on investment in 7 months, with total ROI of 122%, due to smarter targeting

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Insight at the point of interaction is a key challenge

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What does real-time optimization look like?

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What does real-time optimization look like?

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Structured,

unstructured,

social media

and business

intelligence

data

Business

rules

Optimization

Predictive

analytics

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#customer analytics

#strategy #technology and

services

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The customer analytics ecosystem has three degrees of separation

Source: November 2012 “Deciphering A Fragmented Customer Analytics Ecosystem”

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Analytics/BI tops the list of marketers‟ technology needs

Marketing

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© 2013 IBM Corporation

Customer analytics maturity model

.

.

.

Insight for Decision Makers

The Next Best Action

Information Cost Reduction

Foundational

0.2% - 2.9%

Information Sharing

Competitive

6.2% - 18.7%

Information Responsiveness

Differentiating

16.9% - 38.2%

Information on Demand

Breakaway

24.1% - 64.3%

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#customer analytics

#takeaways

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Customer analytics gets a makeover

Big Data poses new challenges for customer analytics, faced with three key

trends:

• Analytics production to analytics consumption and activation

• Expert user to casual user

• Static intelligence to dynamic, real-time intelligence

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© 2013 IBM Corporation

Next Steps…

Identify place to start

• Focus on 1 business problem

• Perform cost/benefit analysis 1

Leverage existing tools

• Team up business strategy + implementation strategy

• Start with readily accessible data, open architecture 2

Execute

• Define achievable goals

• Build on small wins to launch larger initiatives 3

Perform cost/benefit

analysis:

What is spend on avg.

marketing campaign now?

What if we could send offers

to 20% of our customers, but

receive 70% returns?

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© 2013 IBM Corporation