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Seth Duncan, Research Manager, Context Analytics, presentation to the Institute for Public Relations 2009 Summit on Measurement, 10/15/09

Seth Duncan, Research Manager, Context Analytics, presentation to the Institute for Public Relations 2009 Summit on Measurement, 10/15/09

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Measuring the Impact of Earned Online Media on Business Outcomes: A Methodological Approach Presentation Transcript

  • 1. Measuring the Impact of Earned Online Media on Business Outcomes: A Methodological Approach Presentation to the IPR Measurement Summit October, 2009 Seth Duncan, Research Manager sduncan@context-analytics.com
  • 2. Itinerary 1. Brief overview of how web analytics work and how they can benefit PR professionals 2. Practical steps for how communications teams can use “out-of-the-box” web analytics 3. How more advanced statistics can be used to integrate web analytics and other forms of media measurement to help communications team target the correct online audiences and optimize messaging strategies 4. Shortcoming of web analytics and emerging uses
  • 3. Standard Media Metrics Sentiment Share of Volume or voice/ prominence Thought leadership Message Penetration
  • 4. Media and Business Outcomes
  • 5. Web Analytics: A Brief Primer 4. JavaScript code 1. Visitor types URL into executed: collects data browser (or clicks on link) and sends to collection server (e.g., Google Analytics, Omniture, etc.) 2. Request sent to 3. Server sends page website server with JavaScript code
  • 6. Web Analytics: A Brief Primer Direct Traffic Search Results Website Email Landing Sale Campaigns Page Landing Earned Media Download Page Paid Search Landing Registration Page Content Network Ads •Number of Unique Visitors •Avg. Time Per Visit Social Media •Bounce Rate Advertisements •Number of Page Views •Conversions
  • 7. Web Analytics: A Brief Primer Earned Media Unpaid Traffic from: •Mainstream Media (e.g., NYTimes.com) •Online Media (e.g., CNET) •Blogs •Number of Unique Visitors •Avg. Time Per Visit •Forums •Bounce Rate •Twitter •Number of Page Views •Social Networking Sites •Conversions •Other Corporate Websites
  • 8. Why Are Web Analytics So Important to PR? Uses same metrics to measure earned and paid media Use fact rather than intuition when addressing questions such as: •Is our corporate Twitter account driving traffic to the right web pages? •Is Key Message A more effective at driving sales than Key Message B? •Should we invest more resources in social or traditional media? •What audiences should corporate communications be targeting? Can help optimize overall communications strategy by matching the right messages with the right audiences Sites that Demand Effective refer a lot generation messages of traffic and sales
  • 9. Why PR Is Not Using Web Analytics
  • 10. Why PR Is Not Using Web Analytics Web Analytics Dashboard Traditional Media Report Social Media Report Raw Referral Data from Web Analytics Solution
  • 11. Why PR Is Not Using Web Analytics Web Analytics Dashboard Traditional Media Report Social Media Report Raw Referral Data from Web Analytics Solution
  • 12. Why PR Is Not Using Web Analytics
  • 13. Practical Steps For PR Professionals
  • 14. Using Web Analytics for PR Basic Analytics Advanced Analytics Pulled directly from solution Integrated with other data Address basic questions Address strategic questions Who visits your website? Which audiences respond best to campaigns and product offerings? Which sites drive most traffic? Which messages are most effective Which sites drive most sales? at driving traffic and engagement? Should we invest more resources in How can we match the right social or traditional media? messages to the right audiences?
  • 15. Basic Analytics What sites drove the most traffic and engagement? Raw Earned Media Report From Web Analytics Clean
  • 16. Basic Analytics What types of sites drove the most traffic and referrals? •Traditional •Blog Raw Earned Media Report Media Type •Forum Categorize •Video From Web Analytics •etc… •General News Site •Lifestyle Content/Vertic •Gaming al •etc… Sites with Outreach relationships/ contact
  • 17. Basic Analytics Just by spending a little time to categorize/segment sites (hypothetical data)… Media Type Site Content Outreach Conversion Rate for Ad Words
  • 18. Practical Tips for Basic Analytics 1. Web metrics depend on PR goals Generating Demand/Leads Sales 1.Unique Visitors 1.Revenue 2.Registrations 2.Orders 3.Downloads 3.Conversion Rate 4.Avg. Time on Site 5.Goal Page Visits 6.Top Exit Pages
  • 19. Practical Tips for Basic Analytics 2. Take the time to download and clean the data Results from search and email campaigns could make earned media appear less effective
  • 20. Practical Tips for Basic Analytics 3. Look at both totals and averages Averages reveal “hidden gems” (hypothetical data): Total Sales Average Sales
  • 21. Advanced Methods What types of stories and posts drive action? Assign different sites and stories attributes that will later be ranked to better understand what’s most effective
  • 22. Tying It All Together Web Analytics Dashboard Traditional Media Report Social Media Report Raw Referral Data from Web Analytics Solution
  • 23. Where to Get Data About the Site Knowing who is visiting your site and where they are coming from What sort of data is useful? Where do you get it? Site Category •Human categorization Site •Social media monitoring tool (Radian6, Media Type Techrigy, Buzzmetrics, etc.) Content •Business intelligence tools Referring Site •Search engine/panel data (Google Ad Demographics Planner, Microsoft Adcenter, Quantcast, etc.) Traffic At Referring Site •Panel-based data (e.g., comScore, Compete, etc.)
  • 24. How to Measure Story/Post Content These are the components of media coverage that drive perceptions and action Similar to what is usually found in traditional and social media monitoring reports: •Sentiment •Spokespeople/Quote ds •Key Messages •Competitor Mentions •Industry Issues •Story/Post size •Brand Prominence •Product Mentions
  • 25. Data Integration and Analysis Audience Data Site-Level Attributes: Site type, site content, audience, traffic, number of posts, etc. Unpaid Referral Data From Web Analytics Integrated Data Integrated, Causal Model Post-Level Attributes: Online Media Sentiment, product Content mentions, messages, story length, etc.
  • 26. Ranking Attributes by Importance It’s like multivariate testing, only for earned media instead of advertisements Apply multiple regression, hierarchical linear modeling, or any statistical analysis that can provide an estimate of “effect size” Audience/ Site Types/Categories Site Attributes Site Demographics Site Traffic Regression Web Analytics Sentiment Metric Key Messages Content/ Message Competitor Mentions Attributes Industry Issues Story/Post Size Product Mentions
  • 27. Ranking by Coverage Attributes by Importance Statistical Output Helps: What Drives Visitors? What Drives Sales? •Understand what types of articles/posts are effective •What messages are most effective? •What types of media outlets are effective? •Ultimately, helps to prioritize PR efforts
  • 28. Tying It All Together Creating a Causal Model Using Path Analysis or Structural Equation Modeling
  • 29. Playbook Drives Visitors Opportunities Very Effective Drives Engagement Ineffective Missed Opportunities
  • 30. Playbook Drives Visitors Opportunities Very Effective Site/Audience Types Site/Audience Types 1.… 1.… 2.… 2.… Drives Engagement Story/Post Content Story/Post Content 1.… 1.… 2.… 2.… Ineffective Missed Opportunities Site/Audience Types Site/Audience Types 1.… 1.… 2.… 2.… Story/Post Content Story/Post Content 1.… 1.… 2.… 2.…
  • 31. Playbook Match messages Key Message: that drive “Product makes you engagement with smarter” audiences that are likely to visit the site Sites With High Income Audiences
  • 32. Playbook Match messages “Product makes you that drive smarter” In engagement with Sites With High Income audiences that are Audiences likely to visit the site
  • 33. Final Thoughts
  • 34. Caveats Technical Limitations Practical Limitations •Reliance on cookies •You can’t directly track offline activity •Reliance on clickthroughs •Messy Data •Mobile devices and javascript •Integration requires additional software or technical skill •Time consuming manual analysis/Communications team bandwidth
  • 35. Future Directions Click-throughs View-throughs
  • 36. Future Directions Integrating Advertising and Earned Media •Are ads more effective when they appear alongside unpaid media? •Is unpaid media more effective when paired with ads?
  • 37. Takeaway Messages 1. Web analytics allow communications teams to use the same types of measurement as other forms of marketing 2. Web analytics can show what sites and stories/posts are driving the most traffic and engagement on a corporate website “out of the box” 3. When integrated with other types of media measurement, web analytics can help communications teams match the right types of messages with the right audiences to increase engagement and revenue - this allows communications teams to use sophisticated segmentation and targeting methods used in paid media marketing 4. Web analytics are not perfect: Imperfections with data collection, reliance on click- throughs, and difficulty integrating different data sources are barriers to widespread PR adoption of web analytics
  • 38. About Context Analytics  Context Analytics helps marketing and communication teams gain a competitive edge by identifying and Service offerings assessing perceptions, positioning strategies, and • Global Media Research & Measurement emerging relevant issues in mainstream and social • Social Media Analytics & Influence Mapping media • Consulting & Research Program Management  Our research adds strategic insight to campaign • Primary Research planning and is critical to assessing and demonstrating • Competitive Research the value of marketing programs to executives. • Business Impact Analysis  Context Analytics is a subsidiary of Text 100. Groups served within our clients’ Representative Clients: organizations: • Corporate Communications/PR • Product PR • Pricing Strategy • Marketing • Branding • Advertising • Sponsorship Marketing • Investor Relations • Customer Service • Legal/HR