Qualitative / Quantitative - Learn More About Your Users With Web Analytics
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This document discusses using web analytics and user research data to understand users. It emphasizes that both quantitative ("what" and "behaviors") and qualitative ("why" and "language") data are needed to fully understand users. User segments and specific user groups should be analyzed rather than just aggregate data. Both web analytics and user experience data have limitations and are best used together to optimize products and identify problems.
Qualitative / Quantitative - Learn More About Your Users With Web Analytics
- 1. qualitative / quantitativeLearn more about your users with web analytics.Erin Jo Richey
- 2. WHAT IS DATA GOOD FOR ANYWAY?
- 3. Data helps us understand how people use a product.
- 4. Data gives us the opportunity to discover trends, patterns, and anomalies.
- 5. With data, we can optimize a product to be better, easier, and more awesome.
- 7. “what” data
- 8. “why” data
- 9. qualitative & quantitative+you need both to live
- 10. WHO ARE THESE PEOPLE ANYWAY?
- 11. user segmentsFocus on specific groups of users with shared traits, don’t analyze the aggregate.
- 12. These are not your users.
- 13. Your users have different problems and different intentions.
- 14. user segmentsprevious customernot a customersite membernot a memberfrom americafrom mexicoread your emailclicked on your tweetuses chrome on a pc running windows xpvisited your site from an iphonesaw your ad on that other guy’s site
- 15. Mac userreferred via an adsearched on Googleis a past customeriPhonefrom the United States
- 16. WHAT ARE THEY DOING?
- 17. behaviors and actionsAnalytics measures how many times a page was viewed, how many times a movie was watched, and which items were clicked on.
- 18. behaviors and actionsFocus on the behaviors or actions that your work can have an impact on.
- 22. WHAT ARE THEY SAYING?
- 23. language & terminologyFrom on-site search, we can gain insights from user-generated terminology. tabletable setstablestables and deskstables / deskswood tablechairchairschairs for all purposescomputer chairoffice chairswivel chairboarddry erasedry erase boardpresentation boardwhite boardwhite boards
- 24. language & terminologyWe can see the words people use, the mistakes they type, and what they’re searching for.tabletable setstablestables and deskstables / deskswood tablechairchairschairs for all purposescomputer chairoffice chairswivel chairboarddry erasedry erase boardpresentation boardwhite boardwhite boards
- 25. Search TermSearch Termloginlove quotes lurexmicro denim shortsreturn labelreturnsshipping to canadastone rosetibi bianca shift dresstibi juma shortstorres shirtthe lizettewedding boutique72% cotton95% rayonbelle fleur chemisebridesmaid dresschunky sweater dresscocktail dresscommunity denimcustomer servicedenim dressdouble zero clothingfuscha brides maid dresseskimono satin
- 26. Search TermTotal SearchesSearch Exit Rate72% cotton95% rayonbelle fleur chemisebridesmaid dresschunky sweater dresscocktail dresscommunity denimcustomer servicedenim dressdouble zero clothingfuscha brides maid dresseskimono satin57348423001221758210%3%0%7%0%27%2%82%73%20%50%100%
- 27. THE DANGERS OF WEB ANALYTICS
- 28. Statistical significance is not baked in.
- 30. -23.32%
- 31. It is very hard for even your most important set of numbers to really represent what you value as a company.
- 32. WA & UX <3
- 34. web analytics datagreat for monitoring and measuring how well an organization is meeting its goals
- 35. user research datagreat for finding outliers and identifying causes, reasons, and intentions
- 36. wa + ux datause data from multiple sources to more efficiently discover problems, optimize designs, and test solutions
- 37. {a plug for nonprofits}Analysis ExchangePartner with a web analytics mentor and an analytics student.Get analytics projects done for your organization…for free!http://www.analysis-exchange.com
- 38. {the end}Erin Jo Richey@erinjoerin@flatfrogdesign.com