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Signia	
  Analy*cs	
  Inc.	
  
   info@signia.ca	
  
Engage Your Best Customers
         grow sales by making better decisions for your business


                                         Know your best customers

                                         Identify which products or services are vital
                check-in
                                         Recognize new opportunities and trends

                                         Grow sales by rewarding your customers




reward                          scan
              best customer




                analytics
Signia	
  Analy*cs	
  Inc.	
  
   info@signia.ca	
  
THE	
  CHALLENGE	
  

         Imagina*on	
  &	
  Crea*vity	
  
             in	
  Data	
  Science	
  
             •  Use	
  our	
  data	
  (~2	
  yrs	
  of	
  
                data	
  from	
  fitness	
  gym)	
  
             •  Take	
  it	
  to	
  the	
  next	
  level	
  	
  
             •  Do	
  not	
  repeat	
  what	
  we	
  
                have	
  already	
  done	
  
EXAMPLE	
  OF	
  TYPES	
  OF	
  ANALYSIS	
  
•  Segmenta*on	
  of	
  Customers	
  
    –  Determine	
  if	
  there	
  are	
  segments	
  (or	
  groups)	
  of	
  customers	
  
       who	
  behave	
  similarly	
  or	
  different.	
  
    –  What	
  criteria	
  can	
  determine	
  if	
  a	
  customer	
  belongs	
  to	
  a	
  
       certain	
  segment.	
  	
  For	
  example,	
  is	
  a	
  par*cular	
  customer	
  a	
  
       fan/evangelist	
  or	
  just	
  a	
  regular	
  customer.	
  
•  Time-­‐series	
  analysis:	
  Analyze	
  paWerns	
  in	
  the	
  data	
  on	
  a	
  
   weekly	
  v.s.	
  monthly	
  basis	
  	
  
•  Average	
  Life-­‐cycle	
  of	
  client	
  
•  Life-­‐*me	
  Value	
  of	
  a	
  Customer	
  (may	
  need	
  to	
  make	
  some	
  
   assump*ons	
  on	
  the	
  value	
  of	
  different	
  services)	
  
•  Predic*ve	
  Analysis:	
  Hypothesis	
  tes*ng	
  (or	
  other	
  
   methods)	
  to	
  determine	
  how	
  a	
  customer	
  might	
  behave	
  
   based	
  on	
  the	
  first	
  few	
  data	
  points.	
  
JUDGING	
  CRITERIA	
  
•  Clear	
  descrip*on	
  of	
  business	
  ques*on	
  you’re	
  
   trying	
  to	
  answer	
  for	
  business	
  owner/manager	
  
•  Descrip*on	
  of	
  solu*on	
  and	
  sta*s*cal	
  methods	
  
   used	
  to	
  analyze	
  the	
  ques*on	
  
•  How	
  well	
  do	
  you	
  account	
  for	
  variances	
  in	
  the	
  data	
  
•  Clearly	
  document	
  and	
  explain	
  any	
  assump*ons.	
  
•  Presenta*on	
  
•  Imagina*on	
  &	
  Crea*vity	
  

•  BONUS:	
  What	
  new	
  data,	
  if	
  made	
  available,	
  could	
  
   help	
  to	
  answer	
  addi*onal	
  business	
  ques*ons.	
  
TIMELINE	
  



•    Kick-­‐off	
  &	
  Project	
  Proposal	
  
•    Q&A	
  –	
  mid-­‐november	
  
•    Project	
  Due	
  
•    Presenta*on	
  
Signia	
  Analy*cs	
  Inc.	
  
   info@signia.ca	
  

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ECMB12 Signia Project Presentation

  • 1. Signia  Analy*cs  Inc.   info@signia.ca  
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12. Engage Your Best Customers grow sales by making better decisions for your business Know your best customers Identify which products or services are vital check-in Recognize new opportunities and trends Grow sales by rewarding your customers reward scan best customer analytics
  • 13. Signia  Analy*cs  Inc.   info@signia.ca  
  • 14. THE  CHALLENGE   Imagina*on  &  Crea*vity   in  Data  Science   •  Use  our  data  (~2  yrs  of   data  from  fitness  gym)   •  Take  it  to  the  next  level     •  Do  not  repeat  what  we   have  already  done  
  • 15. EXAMPLE  OF  TYPES  OF  ANALYSIS   •  Segmenta*on  of  Customers   –  Determine  if  there  are  segments  (or  groups)  of  customers   who  behave  similarly  or  different.   –  What  criteria  can  determine  if  a  customer  belongs  to  a   certain  segment.    For  example,  is  a  par*cular  customer  a   fan/evangelist  or  just  a  regular  customer.   •  Time-­‐series  analysis:  Analyze  paWerns  in  the  data  on  a   weekly  v.s.  monthly  basis     •  Average  Life-­‐cycle  of  client   •  Life-­‐*me  Value  of  a  Customer  (may  need  to  make  some   assump*ons  on  the  value  of  different  services)   •  Predic*ve  Analysis:  Hypothesis  tes*ng  (or  other   methods)  to  determine  how  a  customer  might  behave   based  on  the  first  few  data  points.  
  • 16. JUDGING  CRITERIA   •  Clear  descrip*on  of  business  ques*on  you’re   trying  to  answer  for  business  owner/manager   •  Descrip*on  of  solu*on  and  sta*s*cal  methods   used  to  analyze  the  ques*on   •  How  well  do  you  account  for  variances  in  the  data   •  Clearly  document  and  explain  any  assump*ons.   •  Presenta*on   •  Imagina*on  &  Crea*vity   •  BONUS:  What  new  data,  if  made  available,  could   help  to  answer  addi*onal  business  ques*ons.  
  • 17. TIMELINE   •  Kick-­‐off  &  Project  Proposal   •  Q&A  –  mid-­‐november   •  Project  Due   •  Presenta*on  
  • 18.
  • 19. Signia  Analy*cs  Inc.   info@signia.ca