understanding web analytics

Understanding  Web  Analy1cs    

Jon  Whitehead

Metricks.org

Who  is  Jon  Whitehead?  

•  Web  designer/developer  through  dotcom  crash  

•  Analy1cs  part  of  role  for  over  10  years  •  Full  1me  Web  Analyst  since  2006  

•  Formed  Metricks  2010    

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Data,  Data  everywhere…  

•  Google  Analy1cs,  Omniture,  Webtrends,  KISSmetrics,  Springmetrics,  Woopra  

•  Clicktale,  CrazyEgg,  Lucky  Orange  •  Social  Media  measurement  tools  

•  EDM  data  –  Mailchimp,  Icontact,  Vision6  

•  App  data  –  Flurry,  Otherlevels  •  And  that’s  just  online!  

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How  do  we  cut  through  it  all?  

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ABC  of  Web  Analy1cs  

Understanding  and  Focus  •  Acquisi1on  -­‐  How  do  prospects  get  to  your  site  •  Behaviour  -­‐  what  do  they  do  on  your  site    •  Consequence  -­‐  what  propor1on  are  doing  what  you  want  them  to  

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Consequence  

What  is  the  objec1ve?  •  Business  •  Website  

•  Macro  and  micro  goals  – Macro  –  a  sale,  a  lead,  a  download  – Micro  –  a  like,  a  tweet,  video  watched  

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Goals  and  Events  

Objec1ves  in  Google  Analy1cs  called  Goals  Macro  -­‐  Leads,  sales,  subscrip1ons  Setup  in  GA  interface  

Events  Ac1ons  on  the  site  Macro  and  Micro  -­‐  submit,  play  video,  download  Very  important  for  apps  Needs  code  

Measure  what  prospects  are  doing  against  objec1ves  

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Goal  setup  

1)  add  a  name  2)  This  goal  is  based  on  finishing  on  a  certain  page  -­‐  confirma1on  page  3)  The  thankyou  page  url  4)  Head  Match  from  dropdown  -­‐  matches  the  start  of  the  goal  page  5)  Goal  value  –  value  of  a  lead  6)  1ck  to  setup  a  funnel  -­‐  a  series  of  pages  a  user  progresses  through  7)  the  funnel  steps  

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Acquisi1on  

Where  are  prospects  coming  from?  Search,  Referral,  Direct  

•  Campaign  tagging  hcp://www.metricks.org?  utm_campaign=2012-­‐presenta1ons  

&utm_medium=presenta1on  

&utm_source=rivercitylabs  

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Ques1on  the  data  

•  Use  business  ques1ons  – How  are  our  campaigns  performing?  – What  are  our  best  keywords?  – Why  do  I  have  such  high  bounce  rate?  

•  Frame  as  ‘which’  – Which  campaigns  perform  best?  – Which  keywords  convert?  – Which  elements  are  causing  prospects  to  bounce?  

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Which  campaigns  perform  best?  

All  Traffic  report  

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Which  Keywords  convert?  

Greater  than  site  average  

Terms  that  have  good  traffic  and  a  higher  than  site  average  conversion  rate  

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Which  Keywords  convert?  

100  =  100%  conversion  

Terms  that  convert  at  100%  -­‐  use  in  content,  social,  PPC  etc  

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Which  elements  are  causing    prospects  to  bounce?  

Examine  page  and  devise  hypotheses  No  call  to  ac1on,    Wrong  informa1on,    Slow  page  

Use  GA  experiments  Test  different  layouts  

Also  Unbounce,  VWO,  Op1mizely  

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Mobile  and  Apps  Mobile  App  Analy1cs  -­‐  beta  

hcp://analy1cs.blogspot.com.au/2012/06/measuring-­‐mobile-­‐world-­‐introducing.html  

hcps://services.google.com/p/forms/mobileappanaly1csbeta/  

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Call  tracking  

•  Complete  view  of  leads  •  Include  call  details  in  Google  Analy1cs  – Amount  of  calls  

– Call  dura1on  – Answered  or  not  

•  Can  also  use  with  Adwords  numbers  

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Notes  

•  Keep  track  of  what  is  happening  that  could  influence  traffic,  internal  and  external  

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Final  Word  

It’s  not  about  how  much  data  you  have,    it’s  what  you  do  with    

the  data  that  is  important  

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…  That’s  All  Folks  …  

jon@metricks.org    Twicer:  @jonny_whitehead    

linkedin.com/in/jonnywhitehead    

Training:  hcp://in-­‐a-­‐day.com.au/workshops/website-­‐

training/web-­‐analy1cs-­‐in-­‐a-­‐day/