the brainyard webcast - social business & social analytics - 3/1/12

Social Analytics - Putting the Social Analytics - Putting the Science into Social BusinessScience into Social Business

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Mark Heid Program Director Social Analytics at IBM

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© 2011 IBM Corporation

IBM Social Analytics - Putting the Science into Social Business

Mark Heid, Program Director Social Analytics, IBMEmail: [email protected]: @mheid

March 1, 2012

mailto:[email protected]

© 2011 IBM Corporation© 2011 IBM Corporation

Agenda

5

Why be an interactive, social business?1

Social Analytics & Enterprise Marketing Management3

The New Marketing Imperative2

How to Get Started4


Marketing’s Challenges…and Opportunities

6

§ Channels proliferate…

Network of pages Network of people

§ The Internet evolves…

§ The consumer is in control…

§ The rate of change accelerates…

Marketing’s role must evolve…

Years to reach 50M users:

TV13 Yrs

Internet4 Yrs

Facebook3 Yrs

Tablet2 Yrs


Expanding marketing’s role, and contribution to the business

Agenda:

ü Understand the market and the customer

ü Build awareness and demand

ü Steward the company’s brand

ü Drive brand strategy and execution

Agenda: + Understand the customer in real time,

across the business+ Anticipate customer needs+ Drive consistent, compelling interactions

across all channels+ Steward the customer experience across

all touch points+ Monitor and harness customer evangelism+ Accountable for business outcomes and

return on investment

Traditional CMO

Transformative CMO+

7


The vast majority of CMOs are underprepared to manage the impact of key changes in the marketing arena

50%71%

68%

65%

63%

59%

57%

56%

56%

56%

55%

54%

50%

UnderpreparednessPercent of CMOs reporting underpreparedness

Data explosion

Social media

Growth of channel and device choices

Shifting consumer demographics

Financial constraints

Decreasing brand loyalty

Growth market opportunities

ROI accountability

Customer collaboration and influence

Privacy considerations

Regulatory considerations

Source: Q8 How prepared are you to manage the impact of the top 5 market factors that will have the most impact on your marketing organization over the next 3 to 5 years? n=149 to 1141 (n = number of respondents who selected the factor as important)

Global outsourcing

Corporate transparency 47%

8


Customers are the New Intellectual Property

ProductLeadership

(Make the promise)

OperationalExcellence

(Deliver the promise)

CustomerIntimacy

(Keep the promise)

DecisionManagement

9


We are seeing unprecedented upheaval in the consumer buying process

* David C. Edelman, McKinsey, Dec 2010

In the past….there was a funnel

• Many Brands - Consumers start buying process with a large number of brands in mind

• Fewer Brands: These choices are narrowed down to a few

• Final Choice: A decision is made between the few

• Buy: A purchase is made…

• Post Purchase: Consumers’ relationship with the brand is focused on the use of the product or service

Today’s consumer buying process is far more dynamic and interactive…..

10


Increasingly, customer acquisition is more nuanced. Generating loyalty is the new marketing imperative

Strengthen brand preference

through advocacy

Accelerate re-purchase through propensity models

Gain insights and increase positive sentiment in social conversations

* David C. Edelman, McKinsey, Dec 2010

Social Analytics is the key to success in this new environment

11


Agenda




How to Get Started4

12


Knowing the customer… involves creating a complete picture

Jane Cogswell Demographic Profile• Financial Planner• Single• 28 years old• Located in Boston, MA

TargetAudience

Preferences• Channel• Contact Time• Value Buyer

• Gender / Age• Geography• Income

Demographics

• Visit Frequency• Purchases• Lifecycle stage

Behaviors

• Hobbies• Family • Lifestyle

Interests

13


Social attributes will improve understanding and results

Typical audience targeting: demographics

Social media informs interest, brand disposition, likes/dislikes

Accountant

Mom Wife

Golfer

14


Pulling together the whole scenario

Comes to the web site and gets a cookie,browses, but does not buy

Later receives an email with a personal URL, and clicks through to the web site.

Jane makes a purchase and enters her email for the confirmation and address for shipping

Jane, loves her product so much she becomes a fan on The Facebook.

Connections made between:§ Cookie and Email § House Hold and Cookie§ Email and House Hold

Cookie=24601Regular web site browserRecently looked at green widgets

Email [email protected] =24601Open rate: 73%Click-through rate: 5%

Facebook ID=01810210 Facebook friendsBorn in Houston, TXGadget’s Galore Fan

Facebook ID

And cookie tied together?

Jane, tweets about #GreenWidget

@BrainyJanieFollowing 53Followed by 152

Twitter handle appended through third party

Channel IDCookie 24601

Email [email protected]

Direct Jane Cogswell

Facebook 01810

Twitter BrainyJanie

Jane gets an email invitation to attend a sneak preview of Green Widget 2.0 and she can invite her friends via Twitter.

@BrainyJanieTweets sneak preview link, opened by 25 friends

Rinse and Repeat

Email and cookie are tied together

Channel IDCookie 24601

Email [email protected]

Direct Jane Cogswell

Facebook 01810

Twitter BrainyJanie

15


An Example: SmartPhone User Personas

SPSS Modeler identifies clusters and maps the authors in social media to personas established from the CCI concepts and hotwords.

16


Monetizing Social Media

Optimize Cross Channel, Integrated

Campaigns

Marketing CampaignsPR Activities

Merchandising MixCategory Management

Sales

Retailer POSData

E-Commerce

Web Browsing

Contact Center

Social Media

Surveys, Focus groups

Map Aggregate Models to 1:1 User Profiles

Execute at the individual level by mapping

aggregate insights to 1:1 social media profiles

Capture, Analyse & Model

Extract trends

Expose patterns

Discover relationships

17


Social Media Improves Traditional Predictive Analytics

Behavioral data- Orders- Transactions- Payment history- Usage history

Descriptive data- Attributes- Characteristics- Self-declared info- (Geo)demographics

Attitudinal data-Market Research-Social Media

Interaction data- E-Mail / chat transcripts- Call center notes - Web Click-streams- In person dialogues

Customer View

360 degree

“Traditional approach”

High-value, dynamic approach- source of competitive differentiation

18


…..and more accurately answers “Why?”

Behavioral data- Orders- Transactions- Payment history- Usage history

Descriptive data- Attributes- Characteristics- Self-declared info- (Geo)demographics

Attitudinal data- Opinions- Preferences- Needs & Desires

Interaction data- E-Mail / chat transcripts- Call center notes - Web Click-streams- In person dialogues

“Traditional”

High-value, dynamic- source of competitive differentiation

Who?Who? What?What?

Why?Why?How?How?

Customer View

360 degree

19


Drill-Down: Web Analytics and Predictive Analytics

With web analytics data alone, we get some insight into web metrics that are important in predicting item sales on an ecommerce website.

20


Drill-Down: Web Analytics, Social Media and Predictive AnalyticsWith web analytics and Cognos Consumer Insight data, we get new insights into other factors that may be important in predicting item sales, such as conversations around “modern” designs.

Key Social Media Insight: Messaging “modern” really

matters. This wasn’t picked-up with traditional

predictive analytics

21


DET

RAC

TION/D

ISAG

REE

MEN

T

ADV

OC

AC

Y/AGREEM

ENT

ACTION

INACTION

Detractorx%

Believerx%

Consumerx%

Uncertainx%

Supporterx%

Skepticx%

Antagonistx%

Personal

Doubtfulx%

Advocatex%

Social

* SEGMENTS REPRESENTATIVE

Real-world Example: Predicting Advocacy

Uncertain: The majority of posters “casually” discuss the product.

Believers: Scored population that is either overall less active or only active on a single or small group of concepts

Advocates: Scored population that is regularly active on a high number of

brand concepts

Online bloggers are clustered using the segmentation model

A predictive model uses posting patterns to identify the propensity of a blogger to be moved into a more positive participation segment

Current State

93 (1.84%)

353 (7.0%)

4599 (91.16%)

339 (6.72%)

97 (1.92%)

74 (1.47%)

152 (3%)

5 (0.1%)

0 (0%)Future State

259 (5.13%)471 (9.34%)

4315 (85.3%)

Predicted Movement

339 (6.72%)

97 (1.92%)

74 (1.47%)

152 (3%)

5 (0.1%)

0 (0%)Future State

259 (5.13%)471 (9.34%)

4315 (85.3%)

Predicted Movement


Social Analytics – Integrated with Social Business


IBM HR Social Intelligence Dashboard


Agenda




How to Get Started4

25


Three types of media: Paid, Owned, Earned

Customer

Owned media

Earned media

Paid media

26


Earned Media

Traditional Digital§ Public relations

generated news

§ Analyst coverage

• Twitter• Blogs• Product reviews

Delivered through a third party without exchange of payment.

27

PR

word of mouth

social media


Owned Media

Traditional

ATM

CALL CENTERDIRECT MAIL

BRANCH

POS

KIOSK

Digital

MICROSITES FAN PAGES

WEB SITE EMAIL

Includes off domain digital

outposts

Media, content, and channels that the company directly delivers, has control over, or owns.

28


Paid Media

Traditional Digital

Delivered through a third party or intermediary in exchange for payment.

29

radioTV

Adsprintoutdoor

Ads

display

Google PPC


Looking ahead – The future must be intelligent marketing that understands the interrelations of all channels and media

Customer

Owned media

e

PR

Google

Earned mediaAds

Google

Paid media

30


3 simple steps to a great social strategy

1. Capture2. Monitor and Analyze3. Act and Engage

31


1. Capture

“Earned” media feeds

SOCIAL NETWORKS

(Publicly available)

WIKIS PHOTO SHARING

BLOGS

100+ million

MICROBLOGSFORUMS/NEWSGROUPS

120+ million

VIDEO SHARING SOCIAL MEDIA NEWS

AGGREGATORS

Consumer InsightSocial

“owned” media outpostsSocial referrals and

downstream conversations

Social Email Analytics

Links from emails and websites that are shared, liked, and

commented on

SocialSources

32


2a. Monitor and Analyze “Earned” MediaSocial Media Analytics with CCI

Social Media Analytics

Analyze “earned” social media,identify brand sentiment,

emerging topics

Consumer Insight

33


2b. Monitor and Analyze“Owned” Social Analytics and ROI with Coremetrics Social

Analysis of “owned” media outposts

ROI of social clickthroughs

Social


34


2c. Monitor and AnalyzeSocial Email Analytics with Unica


Social Email Analytics

Analytics for email and web links that are shared, liked, and

commented on

35


2d. Monitor and AnalyzePredictive Social Analytics with SPSS

Predictive Social Analytics

Social segmentationPredict behavior based on social

attributes


36


3a. Act and Engage

Social Media Marketing Execution

Social segmentation,social sharing, and

real-time offers inside of social media widgets /

applications.

37


3b. Act and Engage

Social MediaBusiness Execution Customer Experience Suite

Social MediaBusiness Execution

Social MediaBusiness Execution

Social commerce, branded communities,

social widgets,product ratings, and

more…

38


Mark [email protected]

twitter: @mheid

39

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Q&A SessionQ&A Session

Mark Heid Program Director Social Analytics at IBM

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the brainyard webcast - social business & social analytics - 3/1/12

Technology

ibm corporation

ibm social analytics

social media68

social attributes

email jane

email invitation

marketing organization

customer collaboration