Developing a Web Analytics Strategy for Your Content

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Without context, our data is meaningless. …

Without context, our data is meaningless.

Measurement is the “so what?” of content strategy, letting us evaluate content quality, including the efficacy of communications, usability, SEO, branding, and user experience design. Web analytics is crucial: it identifies how users interact with our content, informing content audits, analysis, and governance. But standard dashboard metrics aren’t sufficient. Real insight depends on context—so we need an analytics strategy.

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  • \nSo, what’s the holdup? Why are we stuck?\n\nWhy is it so hard to use web analytics to measure content value?\n\n\n
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  • \nWe need to apply the same disciplinary values we adhere to in our content strategy work with analytics strategy.\n
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Transcript

  • 1. Developing a WebAnalytics Strategy forYour ContentRick Allen@epublishmediaCS Forum 2011, September 6#csforum11
  • 2. “ #csforum11 | @epublishmedia [Web analytics] changed the game for marketers and advertisers. But with respect to content quality, many practitioners are flip-flopping with regard to which numbers matter, and whether we can make use of them. Kristina Halvorson Content Strategy for the Web
  • 3. #csforum11 | @epublishmediaSo what?
  • 4. #csforum11 | @epublishmediaSo what? Exactly.
  • 5. #csforum11 | @epublishmediaBe clear-headedabout analytics.
  • 6. “ #csforum11 | @epublishmedia Broadly speaking - and thanks largely to the ubiquity and ease of access to Google Analytics (GA) - businesses have become fixated by traffic volumes, bounces, sources, journeys and subsequent destinations and the like and arent looking to learn more. Clare O’Brien CDA
  • 7. Stand-alone metricsare meaninglesswithout a plan.
  • 8. “ #csforum11 | @epublishmedia Most people understand that content has value. Big value. They just can’t prove or measure the ROI. And, therefore, they have no concept of how much content is worth. Melissa Rach Brain Traffic
  • 9. Web analyticsstrategy bringscontext andmeaning to data.
  • 10. #csforum11 | @epublishmedia• Lack of budget/resources (45%)• Lack of strategy (31%)• Siloed organization (29%)• Too much data (18%)• Lack of senior management buy-in (18%)• Difficulty reconciling data (17%)• IT blockages (17%)• Lack of trust in analytics (16%)• Finding staff (12%)• Poor technology (9%) Source: 2009 Econsultancy Online Measurement and Strategy Report
  • 11. #csforum11 | @epublishmedia• Lack of budget/resources (45%)• Lack of strategy (31%)• Siloed organization (29%)• Too much data (18%)• Lack of senior management buy-in (18%)• Difficulty reconciling data (17%)• IT blockages (17%)• Lack of trust in analytics (16%)• Finding staff (12%)• Poor technology (9%) Source: 2009 Econsultancy Online Measurement and Strategy Report
  • 12. #csforum11 | @epublishmedia• Lack of budget/resources (45%)• Lack of strategy (31%)• Siloed organization (29%)• Too much data (18%)• Lack of senior management buy-in (18%)• Difficulty reconciling data (17%)• IT blockages (17%)• Lack of trust in analytics (16%)• Finding staff (12%)• Poor technology (9%) Source: 2009 Econsultancy Online Measurement and Strategy Report
  • 13. #csforum11 | @epublishmedia• Lack of budget/resources (45%)• Lack of strategy (31%)• Siloed organization (29%)• Too much data (18%)• Lack of senior management buy-in (18%)• Difficulty reconciling data (17%)• IT blockages (17%)• Lack of trust in analytics (16%)• Finding staff (12%)• Poor technology (9%) Source: 2009 Econsultancy Online Measurement and Strategy Report
  • 14. #csforum11 | @epublishmedia• Lack of budget/resources (45%)• Lack of strategy (31%)• Siloed organization (29%)• Too much data (18%)• Lack of senior management buy-in (18%)• Difficulty reconciling data (17%)• IT blockages (17%)• Lack of trust in analytics (16%)• Finding staff (12%)• Poor technology (9%) Source: 2009 Econsultancy Online Measurement and Strategy Report
  • 15. #csforum11 | @epublishmedia• Lack of budget/resources (45%)• Lack of strategy (31%)• Siloed organization (29%)• Too much data (18%)• Lack of senior management buy-in (18%)• Difficulty reconciling data (17%)• IT blockages (17%)• Lack of trust in analytics (16%)• Finding staff (12%)• Poor technology (9%) Source: 2009 Econsultancy Online Measurement and Strategy Report
  • 16. #csforum11 | @epublishmedia
  • 17. Say no todashboard metrics.
  • 18. Numbers rarely speakfor themselves• 2,000 page views• 70% returning visitors• 80% bounce rate
  • 19. “ #csforum11 | @epublishmedia Data doesnt automate [design and content] decisions...Data will never replace human judgment. Colleen Jones Content Science
  • 20. Analytics can do morethan report progress, itcan inform process.• Research and discovery• Content audits• Content analysis• Content governance
  • 21. How do we decide what content tocreate and update? How do we prioritize on- page content?
  • 22. How do we know our message is being seen (or shared) by the right audience? How do we determine appropriate communication channels?
  • 23. “ #csforum11 | @epublishmedia Often numbers don’t speak as loudly as they should because you are missing one simple ingredient: context. Avinash Kaushik Web Analytics 2.0
  • 24. Context conveysmeaning.
  • 25. “ #csforum11 | @epublishmedia I’m astounded at how few decision makers actually use web analytics data...I’m convinced it’s because we report things they don’t care about. Avinash Kaushik Web Analytics 2.0
  • 26. Without context, yourdata is meaningless.
  • 27. #csforum11 | @epublishmedia
  • 28. #csforum11 | @epublishmedia
  • 29. #csforum11 | @epublishmedia Analytics Analysis Framework1 Business objectives What is the purpose of your website? What actions do you want people to take on2 Goals your website to meet your business objectives? Key Performance What relevant web metrics can be used to3 measure the efficacy of your website goals Indicators (KPIs) over time? What are the benchmarks for your KPIs? How4 Targets do you rate success? What visitor attributes will provide meaningful5 Segments insights? Source: http://www.kaushik.net/avinash/web-analytics-101-definitions-goals-metrics-kpis-dimensions-targets/
  • 30. #csforum11 | @epublishmedia Analytics Analysis Framework Improve communications and feedback1 Business objectives systems • Read news blog2 Goals • Leave a comment Key Performance • Time on page3 Indicators (KPIs) • Comment rate • 2+ minutes per page4 Targets • 5% comment rate • Visits from social media sites5 Segments • Visits to conversions Source: http://www.kaushik.net/avinash/web-analytics-101-definitions-goals-metrics-kpis-dimensions-targets/
  • 31. #csforum11 | @epublishmediaWe can’t measure content bynumbers alone. But we can’t demonstrate content success without them.
  • 32. #csforum11 | @epublishmediaRewards• Demonstrate how content meets business objectives and users’ needs.• More adequately define the value of quality content.• Enable content owners to measure the success of their content.
  • 33. #csforum11 | @epublishmediaThanks!Rick Allen@epublishmedia