Versium Real-Life Data Intelligence Platform

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CONTACT US 425$941$9080)cma-y@versium.com)www.versium.com))7530)164th)Ave.)NE)Suite)A240)Redmond,)WA)98052)

Real-Life Data (LifeData) Intelligence

Versium)(www.versium.com))is)a)data)technology)company)that)operates)a)real$life)data)(LifeData))services)and)analyPcs)plaQorm.)))These)technologies)enable)organizaPons)to)be)more)data$driven)by)powering)and)creaPng)soluPons)that)help)opPmize)consumer)engagement,)improve)markePng)efficiencies)and)be-er)understand,)retain)and)find)new)customers.))))

Versium)brings)together)disparate)sets)of)observaPonally)available)data,)comprised)of)over)100)billion)real$life)a-ributes)and)combines)these)insights)with)an)organizaPon’s)exisPng)enterprise)data)to)provide)a)richer,)more)acPonable)profile)of)each)individual)consumer)and)more)intelligent)analyPc)models.))

WWW.VERSIUM.COM

About 2

A"person’s"real"life"profile"is"a"tremendously"powerful""predictor"of"how"that"person"will"interact"with"an"enterprise"

CHRIS MATTY - CEO )

•  Has held executive positions including GM, CMO, SVP of Sales/Business/Corporate Development

•  Founding executive of InfoSpace - Grew revenue to $200M+

- General Manager, Merchant Services Division - SVP Business Development and Sales - Led wireless data strategies

•  Start-up executive at: DepotPoint, Payscale, Smartworks

•  Previously McCaw and AT&T )

Founders 3

http://www.linkedin.com/in/chrismatty/

KEVIN MARCUS - CTO)

•  Co-founder and Chief Technology Officer of Intelius

•  Co-founder and Chief Software Architect of InfoSpace

•  Author and co-author of several issued patents related to user authentication, messages, geographic search and CPU emulation

•  Has advised on over 30 mergers and acquisitions)

Founders 4

www.linkedin.com/in/kmarcus

What We Do " LifeData Services " LifeData Analytics

Real-Life Data Services (LifeData) " 100+ Billion consumer real-life data (LifeData) attributes " Information created as a person interacts in the real world outside an enterprise – Both online and offline " Social data, demographics, interests, purchase histories, real-time life event trigger data, More… " 3.2 billion email database for matching LifeData to consumers " Patent pending validation and consumer profiling technology " All available via API; priced per query and bulk license

LifeData – Data Services Platform 7

100+ Billion LifeData Attributes 3.1 Billion Emails 200 million Mobile Phones with Name/Address

145 Million Social Profiles and Likes

Email)Address)Phone)First)Name))Last)Name)Address))City)

State)ZIP)DOB)IP)Address)OpPn)URL)Source)Timestamp)

Line)Type) Carrier)

Email)is)Socially)AcPve)Mapping)to)Social)Network)Social)Profile)Behavioral)Data)Number)of)ConnecPons)Facebook)Likes)

Facebook)Profile)ID)LinkedIn)Profile)ID)Twi-er)Profile)ID)

375 million Unique Opt-In Email Addresses

And More…

60M Profiles)500M$Likes$Mapping$to$Email$Like$analy4cs$Num$friends,$subscribers,$likes$Social$graphic$details;$ac4vity)

45M Profiles)$$$$$Number$of$Followers$$$$$$Number$of$Tweets$$$$$$Tweet$Stream$Analysis$)

65M Profiles)$$$$Number$of$Connec4ons$$$$$Career$Details,$Educa4on$Etc$$$$$Professional$Network$AHributes$)

LifeData - Social 9

And More…

900 Million Historical Addresses Profiles

Full)Name)Address)

City)State)

ZIP)County)

Phone)Date)of)Birth)

Date)of)Birth)

Home)Value)Purchase)Price)Purchase)Amount,))Purchase)Date)Purchase)Lender)Code)Lender)Name)

Interest)Rate)Type)Purchase)Interest)Loan)to)Value)EsPmated)Wealth)Credit)RaPng)Range))))Est.)Income)

Est.)Household)Income)Net)Worth)Range)of)New)Credit)Credit)Card)User)Visa)Card)Visa)Gold)Card)

MasterCard)American)Express)Discover)Regular)

Financial$

Demographic$

240 Million Records With Interests & Purchase Data

Apparel))Audio)Books)Books/Magazines)Career)Improvement)Cat)Owner)Dog)Owner)Charitable)Donor)ChrisPan)Families)

Computers)Consumer)Electronics)DiePng/Weight)Loss)DIY:)Home)Improvement)Electronics)Gaming)Gardening)

Health)&)Beauty)Health)Medical)High)End)Appliances)InvesPng)Military)History)Music)Online)EducaPon)Online)Purchasing)

ParenPng)Self)Improvement)Single)Parent)Spectator)Sports)ParPcipant)Sports)Camping/Hiking)Fishing)Golf)

Scuba)Diving)TV/Cable/)Sat/Dish)Veteran)in)Household)

Interests$

And More…

100+ Billion LifeData Attributes

LifeData – Event Trigger Data 11

Life Events Change Behavioral Patterns, Interests and Desires

" Analytics using enterprise data combined with real world LifeData " LifeData signals and patterns mapped to enterprise segments –

yield actionable insights and improved ROI " More accurate machine learning and analytic results " Analytic output includes: Predictive scoring, predictive

segmentation, social influence level, predicted behavior… " SaaS Pricing Model: Monthly Fee plus variable component based

on size of customer base to be modeled or scored

LifeData ANALYTICS

Analytics built using enterprise data combined with LifeData

LifeData ANALYTICS

Objectives – Social Commerce MLM !  Problem: Limited insights and understandings about selling base

!  Can better understanding different member segments provide insight into how to improve member performance?

!  Can we use analytics to predict or reclassify members in order to identify members most likely to improve in performance?

!  Can we leverage Social Influence scoring to predict viral success

!  Can we compare member base to other top MLM companies using Social and LifeData analytics

CLIENT: MLM)Company))

PROJECT: LifeData)insights)and)segment)comparison)Compare)members)to)other)MLM)groups)Social)influence)scoring)Predict)viral)members))

Results: 50%)Match)of))members)to)LifeData)Successful)LifeData)a-ribute)idenPficaPon)More)male)then)female)vs)other)MLM’s)Viral$45%$more$likely$to$have$SI$score$8N10$19%)Non$viral)modeled)as)“likely”)viral)Prospect)gen)modeled)to)other)MLMs))))))

CASE STUDY – Social Commerce MLM 15

Social Analytics

Viral vs Non-Viral SI Score

Chris$MaHy$$Phone:)425$941$9080)

Email:)cma-y@versium.com)

Thanks for your time 17

Address:$7530)164th)Ave.)NE)Suite)A240)Redmond,)WA)98052)