The Unrealized Power of Data Andreas Weigend people & data

© people & data | www.weigend.com Andreas S. Weigend, Ph.D. 韦思岸教授

Predictive Analytics WorldSan Francisco, February 19, 2009

The Unrealized Power of Data

Andreas Weigendpeople & data

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0 Outline

Q: Current bottleneck for you in your business? (Scarce vs abundant)?

Historical perspectiveBusiness, Data and Communication

Current trendsFrom Transaction Economics to Relationship EconomicsThe Customer Data Revolution: Shift in Customer Expectations

Implications: From CRM to CMRCustomer Managed Relationships

Applications to business: Marketing 2.0 Why predictive analytics: Relevance How to do it: PHAME

Problem – Hypotheses – Action – Metrics - Experiments

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0 Business, Data, and Communication

1970’s “Experts” learn a language the

computer understandsDigitizing back office10M people

1980’s Front office interacts with back

office100M people

1990’s Customers interact with firmSearch: 1bn people poking at stuff

2000’s1bn people poking at stuff100M people producing stuff Peer-production and collaboration Customers interact with customers

NowDiscovery in addition to search Serendipity: Discover what not

searched People in addition to pages Social commerceMobile in addition to PC, and paper) Continuous partial attentionModel current situation plus history Sensing

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0 Amount of data

Overall : About 100GB per person on the planetDoubling every 1-2 yearsMainly user generated

Example: Youtube15 hours of video uploaded every minute

Example: Flash1bn installs

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0 My behavior

•IMMI Listening into

your roomevery 30 seconds,for 10 seconds.

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0 Current trends

Market researchCombine surveys with click data

Assumption heavy Data rich model

Trans-action

Inter-action

s

Relation-ships

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0 The Customer Data Revolution

1. Sniffing the digital exhaustMainly implicit data, some explicit dataWhat is new? More data sources, esp. location data

2. Individuals talk about themselvesMainly explicit contributions

3. Individuals reveal relationships with othersDirected, asymmetrical, multidimensional (not binary!)

The Customer Data Revolution: Shifting expectationsAttitude of individuals to their informationEconomics of data

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0 Wishlist

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0 Outline



Implications: From CRM to CMRCustomer Managed RelationshipsCustomer valueE-Business Me-BusinessWho pays whom?

Applications to business: Marketing 2.0

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0 Marketing 2.0

Broadcast 1:1 Marketing? Social marketing Implications for predictive analytics: redefining CLV

Intrinsic / individualExternal / network component

Applications to businessAmazon’s “Share the Love”

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0 Conversations

Conversation / CommunicationBetween whom?

Company

Individuals

down

cast

ing

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0 Leverage the social graph

Example: New communications service US phone company with deep experience with targeted marketing Sophisticated segmentation models based on experience, intuition, and

datae.g., demographic, geographic, loyalty data

• Hill, S., F. Provost., and C. Volinsky.Network-based Marketing: Identifying likely adopters via consumer networks.

Statistical Science 21 (2) 256–276, 2006• .

Response increases by a factor of 4.82 by marketing to nearest neighbors (NN)

From 0.28% based on segmentation, to 1.35% based on social graph

1

4.82

2.96

0.4

Non-NN 1-21 NN 1-21 NN 22 NN nottargeted

(0.28%)

(1.35%)

(0.83%)

(0.11%)

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0 Recommendations 2.0

•People Friends

Specific people you knowViral marketing

PeersFans (G-star)

ExpertsFashion bloggers

•Data Clicks

Purchases

Forward, tell a friendRelationship

AnnotateAttention

SearchIntention

LocationSituation

Product data

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0 Outline



Implications: From CRM to CMRCustomer Managed Relationships

Applications to business: Marketing 2.0 Why predictive analytics: Relevance

Respect How to do it: PHAME

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0 You want to be PHAME-ous!

•PHAME Problem Hypotheses Action Metrics Experiments

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0 Summary



Implications: From CRM to CMR (Customer Managed Relationships) Applications to business: Marketing 2.0 Why predictive analytics: Relevance How to do it: PHAME

Web: www.weigend.com Phone: +1 650 906-5906

The Unrealized Power of Data Andreas Weigend people & data

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