Get  Closer  to  your  Customers  Turn your data into valuable interactions that your customers expect!

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Connec/ng  with  the  Customer  

Preferences  

Affini4es  

Context  

Behavior  

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Customer  Experience    Customer  spamming  is  doing  more  damage  than  good  

Company  &  Customer    Ac1vity  

Customer  CRM  

Systems  

Customer  Web  &  Mobile  

Customer  Channel  Campaigns  

Customer  Service  Desk  

Social  Data  

Website  &  online  apps  

Mobile  App  Server  

Mail  SMS  

Print  

Broadcast  

Offers  

direct  mail  

ATM  

web  

Agent,  IVR  

email  

mobile  

chat  

Relevance?  Awareness?  

Value?  Timing?  Clarity?  

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direct  mail  

ATM  

web  

Agent,  IVR  

email  

mobile  

chat  

The  Personaliza/on  Customer  Experience  “I  have  a  customer  –  what  does  that  customer  value  most?”  

Customer  Service  Desk  

Customer  Web  &  Mobile  

Customer  Channel  Campaigns  

Social  Data  

Company  &  Customer  Ac4vity  

Customer  CRM  Systems  

Mail   SMS  

Broadcast  

Print  

Mobile  App  Server  

Customer  website  &  online  apps  

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I  have  a  customer  -­‐  what  are  the  top  3  products  he  is  likely  to  buy?  

Answering  the  Tough  Ques/ons…  

Which  top  hundred  customers  are  likely  to  buy  my  product  X  today?  

What  is  the  best  channel  to  connect  with  my  customer,  and  when?    

Can  I  turn  around  my  most  valuable  poten1al  churners?    

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Overcome  “Analysis  Paralysis”  

Proac4vely  Engage  with  

Customers  

Cope  with  plethora  of  data  

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GeIng  to  Know  Your  Customer  From  siloed  channel  interac4ons  into  ONE  customer  “DNA”  

Listen   Learn  

Customer  DNA  

Standardized,  Ac/onable  Metrics  Single  View  of  the  

Customer  

Channel  all  sources  of  customer  interac/ons  into  

one  data  model  

CRM  and  Demographic  

Debit  &  Credit  Card  Transac4ons  

Online  Data  

Loca4on  

Wallet    Informa4on  

IVR  data  

Call  Data  

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“Listen”  is  about  Interac/ons  

•  Interac4ons  are  behavior  

•  Connect  data  silos  •  Unify  &  augment  

interac4ons  

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Augmented  

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“Learn”  is  about  Metrics  &  DNA  

•  Iden4fied,  standard,  comparable  Metrics  

•  Based  on  Interac4ons  

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“Learn”  is  about  Preferences  &  Affini/es  

•  Interac4on-­‐based  Preference  Learning  on  Products  &  Categories  

•  Affinity  Scores  for  longer-­‐term  profiling  

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Empower  End-­‐Users  to  work  with  Customer  DNA  

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Organize  Metrics  along  ac4vity-­‐based  

categories  

Common,  industry  &  custom  DNA  

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Beyond  metrics:  trend  &  accelera4on  

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Execute  

Event  marke4ng  with  ac4onable  

customer-­‐level  data  

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Dynamic,  metric-­‐based  segmenta4on  &  tracking  

Build  Target  Groups  

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Alerts  for  keeping  track  of  key  opportuni4es  (or  impediments)  

Go  from  campaign-­‐based  to  event  marke4ng  

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?

?

?

Website  Real  Time  Offer  Personaliza/on  

Determine  offer  eligibility  from:  •  Joe’s  product  preferences  •  Joe’s  DNA  (Interests,  lifecycle,  ac4vity,...)  

Calls  to  Lilly  with  content:  •  Customer  info.  •  Context  info.  •  Session  data  

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?

?

?

Website  Real  Time  Offer  Personaliza/on  

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Lily  Enterprise  -­‐  Value  

Analy/cs   Transac/ons   Strategic  

Machine  Learning  

Bigger  is  Beher  

Current  BI  Solu4ons  

Prescrip4ve  

Customer  DNA  Results-­‐Driven  

Genius  of  “AND”  

Maximize  Architecture  

Objec4vity  

Governance  

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Experience  the  Difference  with  Lily  

Listen  Bigger.  

VOLU

ME  

Learn  Faster.  

SPEE

D  

Execute  Smarter.  

ANSW

ERS  

Volumes  of  Data   Availability   Questions  Answered  

Start  working  with  Lily  to  discover  results  from  Day  1  

Zettabytes  

Exabytes  

Petabytes  

Terabytes  

Gigabytes  

Seconds  

Minutes  

Hours  

Days  

Weeks  

Unknown  Unknowns  

Known  Unknowns  

Known  Knowns  

DW/BI  DW/BI  DW/BI  

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