#RIC16

Beyond  Clienteling  Building  Loyalty  with  

Differen;ated  Customer  Experience

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#RIC16

Power  has  shi3ed  

1.7x conversion

+26% profitability

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The  Challenge:  How  to  create  loyalty  in  an  era  of  greater  customer  choice  and  increased  expecta7ons?    

TRUST     HABIT  AFFINITY  

EXPERIENCES   CONSISTENCY   PATTERNS  

Engaging  Experience  

Consistent  Delight  

Pa=ern-­‐building  Triggers  

Contextual  Customer  

Understanding  

Product  Insight  

Responsive    PlaEorm  

Experiences Consistency

Patterns

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ArBficial  intelligence  meets    consumer  psychology  

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INSPIRE   ENGAGE   ADVISE/  ENABLE   SUPPORT   REINFORCE  

DISCOVER   EXPLORE   BUY   EXPERIENCE   SHARE  

shop

per  

associate  

The  Sale  is  Only  Part  of  the  Rela7onship  

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Contextual  Cura7on  

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AI-­‐enabled  visual/  behavioral  search  

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The  Hurdles:  Expect  challenges  

Data Systems  Integra;on

Change  Management

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GePng  Started:  How  to  manage  the  challenges  

Design  the  Experience  

Test,  Learn,  Repeat  

Start  with  a  Thin  Slice  

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Design  the  Experience  

Human  Centered  

Relevant   Transparent  

Contextual   Connected  

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Start  with  a  “thin  slice”  

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Vision   Speed  to  Value   EvoluBon   TransformaBon  

Current   Vision   Current   Vision  Thin  Slice   Current   Vision  Evolve   Current   Vision  Done  

#RIC16

But  what  about  our  data?  Data  Warehouse  

With  a  data  warehouse,  incoming  data  is  cleaned  and  organised  into  a  single  consistent  schema  before  being  put  into  the  warehouse.    

Data  Lake  

With  a  data  lake,  incoming  data  goes  into  the  lake  in  its  raw  form.  

We  select  and  organise  data  for  each  need.  

This  makes  the  Data  Warehouse  the  bo;le  neck  for  analyzing,  cleansing  and  making  sense  of  data  

The  Data  Lake  distributes  those  ac?vi?es  throughout  the  business  

Analysis  is  done  directly  on  the  curated  warehouse  data.  

#RIC16

Opera7ng  an  effec7ve  data  lake  

Opera?onal  systems  communicate  with  each  other  via  service  connec?ons  

Opera?onal  systems  feed  data  into  the  lake  using  topical  queues  

A  few  data  scien?sts  inves?gate  the  lake  for  poten?al  insights  

Lakeshore  marts  curate  and  organise  the  data  for  most  analy?cs  uses  

Mul?-­‐?ered  data  lake  for  processing,  distribu?on,  and  serving  

#RIC16

Customer    Engagement  

Employee    Empowerment  

OperaBonal  Enhancement  

The  Payoff:  Three  key  areas  

#RIC16

THANK  YOU  

Dianne  Inniss  dinniss@thoughtworks.com