Evans-Defosse-Aug-24-2012

Social Commerce Engines

sCEs will power Next Gen market research…

Meet Jane Power of Social Data

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ZMOT Culture

Iterative & Accessible

70%  of  consumers  read  reviews  before  purchase  (84%  for  Millenials)  

Reciprocity

•  90%  of  reviewers  want  to  help  others  •  70%  of  reviewers  give  feedback  to  

improve  product  

•  50%  of  Millenials  trust  online  opinion  over  friends  and  family  

•  50%  of  consumers  trust  UGC  more  than  company  websites  or  news  ar?cles    

Anonymous Trust

Visible sCE

Visible sCE

Visible sCE

Social  Commerce  Engine  ICEBERG  

retailZ.com

ZX.com brandQ.com

brandY.com

buildS.com newretail.com Websites

Product Pages Reviews/Comments

Q&A Stories

What you see …

What you don’t see …

Behavior Customer Profiles

Purchase Data Product Data

Social  Commerce  Engine  NETWORK  

Social media monitoring … <<  scrape  –  report  >>  

What SMM misses: •  Non-public UGC •  SKU level •  Behavioral data •  Purchase data •  Network effect

Ra8ngs  &  Reviews  Q&A  

Product  Stories  

Web  Analy8cs  Post  Purchase  Email  

Campaigns  

Online  Check  Out  

Loyalty  Programs  

Connecting Consumers With Products

CRM  sCE  In-­‐store  Purchase  

Using sCEs - Early Hints

Nexxus  

3M  

Cabela  

3M Dish Wand Fix

3M Scissors Messaging

Cabela’s Pant Design

New  product  polarizes  segments  

Nexxus Product Testing

Recrui?ng  advocates  to  test  new  products…  

NEW RESEARCH LANDSCAPE Social commerce engines are creating a …

Integration & Big Data

Read/Write    Ra8ngs  &  Reviews   Read/Write  Q&A  

Read/Write  Product  Stories  

Websites  I  visited   Contacted    aNer  buying  

Ac8ons    taken  

My  loyalty    programs  

My  profile  sCE  My  in-­‐store    purchases  

Consumer-Product Universe

Transacted/Purchased  Crea?ng  Reviews  

Answering  Ques?ons  

Considering  Products  Browsing  Web  Reading  Reviews  

New  Product    Experience  Data  

New  Purchase    Funnel  Data  

Conven?onal  Survey  Samples  

Richer Product Experience

Theme/Func?on  /Characteris?c  

Posi?ve  

Nega?ve  

Anger  

Sa?sfied  

Excited  

Frustra?on  

Product  Experience   Calls  to  Ac8on  

Ac?on  

Recommend  

Reject  

Alterna?ve  

Consider  

Buy  

Discredit  

Building  Narra8ve  Based  Metrics  

Next Gen MR •  Broaden Reach •  Richer Natural Product Experience •  Extensive X-Market Comparison •  SKU-level analysis •  Detailed Behavioral Patterns

MR Expertise … •  Generalization (e.g., weighting) •  MR assets (e.g., segmentations) •  Consumer modeling

THANK YOU

Presenters: R. Scott Evans, PhD, Bazaarvoice Erin Defosse, VP Product Strategy, Bazaarvoice