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Introduction to Digital Analytics by Peter O'Neill @ MeasureCamp Cardiff

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This covers the Basics, such as purpose & definitions.

Published in: Data & Analytics
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Introduction to Digital Analytics by Peter O'Neill @ MeasureCamp Cardiff

  1. 1. Introduction to Digital Analytics
  2. 2. Quick introduction to me  Australian living in London  Worked in Digital Analytics for over 10 years  Founder of L3 Analytics in 2010  London based Digital Analytics Consultancy  GA & GTM Certified Partner  Merging with AEP Convert to form LeapThree  Support with Google Analytics and Adobe Analytics  Services from Set-up to CRO, Personalisation and Data Strategy  Work with clients of all sizes and across all sectors  Founder of MeasureCamp  Co-founder of MeasureBowling Page 2
  3. 3. To provide intelligence that informs business actions leading to an improvement in performance for online organisations Purpose of Digital Analytics Page 3 To provide intelligence that informs business actions leading to an improvement in performance for online organisations
  4. 4. Purpose of Digital Analytics To be more blunt, the purpose of Digital Analytics is: 1. To make your company more money 2. So you get a bigger bonus/pay rise Page 4 Photo Credit: HikingArtist.com via Compfight cc
  5. 5. What is Digital Analytics all about?  It is not  creating mountains of reports  endless tables of data  an IT or Finance function  Digital Analytics is quite simply about  using data to make smarter business decisions  insights and information  enabling everyone to understand performance Page 5
  6. 6. The 1st task to get value from a Digital Analytics tool Back away from your computer… …what are your business questions? Page 6 © dotmatchbox via Compfight cc
  7. 7. The Biggest Barrier  What is the biggest barrier for Digital Analytics?  TOO MUCH DATA  Easy to be overwhelmed, not sure where to start, what to look at – drown in it and give up  An early piece of advice, start with the basics  And always focus on the business questions Page 7
  8. 8. Caveat: Digital Analytics tools are not 100% accurate  Why?  Not all visitors allow JavaScript  Fake traffic coming from bots  Errors in the implementation  Different technologies and definitions  Doesn’t contain offsite actions/information  How many unique visitors are you?  So what should you do about it?  Get over it...  Remember, the point of digital analytics is to make smarter business decisions  The absolute numbers don’t matter as long as the error is consistent Page 8
  9. 9. Some definitions to start with  HITS  How Idiots Track Success  Page Views  A view of a page  Sessions  One or more website interactions (pageviews or events)  Ends after 30 min of inactivity or by re-entering the website  Users  Number of people who visited the website within a specified date range based on cookies Page 9
  10. 10. Some definitions to start with  Bounce Rate  Proportion of sessions that viewed a single page only  (or had a single interaction e.g. no events were triggered)  Conversion Rate  Proportion of sessions who perform a desired action  Session Duration  (Timestamp of the last interaction of the session) minus (Timestamp of the first interaction) Page 10
  11. 11. Let’s test your knowledge...  Fred visits your website  On Mon and views 3 pages  On Wed and views 1 page  On Fri via an email and views 1 page  Returning 5min later via Organic Search and view 3 pages  Mary visits your website  On Mon and views 1 page  On Tues and views 5 pages  How many... Page 11 – Hits – Users – Sessions –Page Views –What is the Bounce Rate? –What is the Conversion Rate?
  12. 12. So what data can/should you collect e.g. article page  Title: chinas refined nickel imports rise 59 in september  Content ID: 3500554  Category: base metals  Author: ellie wang  Language: english  Image Flag: no  Video Flag: no  Access Method: homepage article list  Publication Date: 2015-10-26  Days since Publication: 16  Recency: recent  Number of Words: 265  Length: medium Page 12
  13. 13. So what data can/should you collect e.g. article page  View Article  Read Article  Based on time on page  Based on scrolling to bottom  Comment on Article  Share Article  Via Social Media  View email  Print Article/Add Clipping  Click on email address  Click to view another article  Sign up with website Page 13
  14. 14. This generates an actionable report for Publishers  Article #2  Popular  Not very effective  Access via other sites  Article #11  Less popular  High reads, shares & comments  Access via internal links Page 14
  15. 15. How to get value from Digital Analytics  Define business requirements in advance  Business requirements => KPIs/metrics => data requirements  Do a thorough implementation and configuration  Ensure users understand and can use the tool  Identify issues & opportunities through the data  Integrate digital analytics into business processes  Use the data to make business decisions, not the HiPPO  Digital Analytics tools, free or paid, are very powerful if:  You know what you need to know  The information is available  You know how to get at that information Page 15
  16. 16. Thank you for your time today To get in touch, please contact me at: Email: peter.oneill@leapthree.com Twitter: @peter_oneill Phone: +44 (0)7843 617 347 LinkedIn: www.linkedin.com/in/peteroneill Page 16

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