Enterprise Analytics 2016 - IIH Nordic Int.
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1. The document discusses the challenges of enterprise analytics, including technical setup issues, the "human factor" of how humans implement things differently, user access challenges, dealing with multiple or different sites, and data quality issues. 2. It provides examples of each challenge area and potential remedies, such as using a tag management system to help with technical setup, standardizing utm parameters to minimize human errors, and using a TMS to help with issues like cookie-less tracking or anonymizing users on some sites. 3. The document is written by someone with over 10 years of analytics experience who provides analytics consulting, setup, and optimization services.
Enterprise Analytics 2016 - IIH Nordic Int.
- 1. Enterprise Analytics Making it big…
- 2. • 10+ years of analytics – Including log file analyzing ;-) • 19 years of web development – 7 years of Sitecore coding – C#, SQL, HTML, CSS and the likes • Certified in Google Analytics, Adobe Analytics, Ensighten TMS, Tealium TMS, Sitecore + some • Have worked at Aller Media and GN ReSound between 2006 and 2014, and then at IIH Nordic from 2014 Call me Peter
- 3. 1. Technical setup 2. The ”Human factor” 3. User access 4. Multiple or different sites 5. Data quality Challenges of Enterprise Analytics
- 4. 1. Technical setup 2. The ”Human factor” 3. User access 4. Multiple or different sites 5. Data quality Challenges of Enterprise Analytics
- 6. Data sent to analytics can be of mixed quality Technical setup
- 12. Remedy #1 – Before analytics • Send data as consistent as possible • Separate test and staging data from that of the production environment TMS is a great help here Technical setup
- 13. Remedy #2 – In analytics • Refine and clean incoming data Lowercase, include, exclude, and in some cases rewrites • Define correct settings Paths, search, qs params, goals ... Technical setup
- 15. Humans think differently (and act accordingly) The ”Human factor”
- 16. The pain ?utm_source=Newsletter&utm_medium=e-mail&utm_campaign=octo10 ?utm_source=newsletter&utm_medium=E-mail&utm_campaign=October10 ?utm_source=newsleter&utm_medium=mail&utm_campaign=OCT10 ?utm_source=nyhedsbrev&utm_medium=Email&utm_campaign=oktober10 Different values = different campaigns The ”Human factor”
- 17. The pain ?utm_source=Newsletter&utm_medium=e-mail&utm_campaign=octo10 ?utm_source=newsletter&utm_medium=E-mail&utm_campaign=October10 ?utm_source=newsleter&utm_medium=mail&utm_campaign=OCT10 ?utm_source=nyhedsbrev&utm_medium=Email&utm_campaign=oktober10 Different values = different campaigns The ”Human factor”
- 18. The pain ?utm_source=Newsletter&utm_medium=e-mail&utm_campaign=octo10 ?utm_source=newsletter&utm_medium=E-mail&utm_campaign=October10 ?utm_source=newsleter&utm_medium=mail&utm_campaign=OCT10 ?utm_source=nyhedsbrev&utm_medium=Email&utm_campaign=oktober10 Different values = different campaigns The ”Human factor”
- 19. The pain ?utm_source=Newsletter&utm_medium=e-mail&utm_campaign=octo10 ?utm_source=newsletter&utm_medium=E-mail&utm_campaign=October10 ?utm_source=newsleter&utm_medium=mail&utm_campaign=OCT10 ?utm_source=nyhedsbrev&utm_medium=Email&utm_campaign=oktober10 Different values = different campaigns The ”Human factor”
- 20. Remedy #1 – Tools More hands off the keyboard The ”Human factor”
- 21. Remedy #2 – utm_id /page1?utm_id=abc987 Minimizes the ‘human error factor’ The ”Human factor” ga:campaignCode ga:source ga:medium 123abc Winter Newsletter email abc987 Summer Newsletter email
- 23. Demands to analytics implementations differ from website to website Multiple or different sites
- 24. The pain Cookies are not allowed before a policy has been seen by the users Multiple or different sites
- 25. A remedy • Use a TMS to connect cookie-less tracking with normal cookie tracking Multiple or different sites +
- 26. Multiple or different sites
- 27. The pain For some countries you need to anonymize users Multiple or different sites
- 28. A Remedy • Use a TMS to anonymize users Multiple or different sites
- 29. 1. Technical setup 2. ”Human factor” 3. User access 4. Multiple or different sites 5. Data quality Challenges of Enterprise Analytics