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

1. Measuring the Impact of Earned Online Media on Business Outcomes: A Methodological Approach Presentation to the IPR Measurement Summit October, 2009

2. Itinerary • Brief overview of how web analytics work and how they can benefit PR professionals • Practical steps for how communications teams can use “out-of-the-box” web analytics • 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 • Review a case study of how Context Analytics used web analytics to help a client optimize their online communications around an online financial services product • Shortcoming of web analytics and emerging uses

3. Standard Media Metrics Sentiment Outcomes Website traffic Demand generation Revenue Web Analytics Share of voice/ Thought leadership Volume or prominence Message Penetration

4. Media and Business Outcomes

5. Web Analytics: A Brief Primer 4. JavaScript code executed: collects data and sends to collection server (e.g., Google Analytics, Omniture, etc.) 1. Visitor types URL into browser (or clicks on link) 2. Request sent to website server 3. Server sends page with JavaScript code

6. Web Analytics: A Brief Primer Direct Traffic Search Results Website Email Campaigns Landing Page Sale Earned Media Landing Page Download Paid Search Landing Page Registration Content Network Ads • Number of Unique Visitors • Avg. Time Per Visit • Bounce Rate • Number of Page Views • Conversions Social Media Advertisements

7. 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 refer a lot of traffic Demand generation and sales Effective messages

8. Why PR Is Not Using Web Analytics

9. Integration Challenges Web Analytics Dashboard Traditional Media Report Social Media Report Raw Referral Data from Web Analytics Solution

10. Why PR Is Not Using Web Analytics

11. Practical Steps For PR Professionals

12. Using Web Analytics for PR Basic Analytics Pulled directly from solution Address basic questions Who visits your website? Which sites drive most traffic? Which sites drive most sales? Should we invest more resources in social or traditional media? Advanced Analytics Integrated with other data Address strategic questions Which audiences respond best to campaigns and product offerings? Which messages are most effective at driving traffic and engagement? How can we match the right messages to the right audiences?

13. Basic Analytics What sites drove the most traffic and engagement? Raw Earned Media Report From Web Analytics Clean

14. Basic Analytics What types of sites drove the most traffic and referrals? • Traditional • Blog • Forum • Video • etc… Media Type Raw Earned Media Report From Web Analytics Categorize Site Content/Vertical • General News • Lifestyle • Gaming • etc… Outreach Sites with relationships/contact

15. Basic Analytics Just by spending a little time to categorize/segment sites (hypothetical data)… Site Content Outreach Media Type Conversion Rate for Ad Words

16. Practical Tips for Basic Analytics 1. Web metrics depend on PR goals • Generating Demand/Leads • Unique Visitors • Registrations • Downloads • Avg. Time on Site • Goal Page Visits • Top Exit Pages • Sales • Revenue • Orders • Conversion Rate

17. 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

18. Practical Tips for Basic Analytics 3. Look at both totals and averages Averages reveal “hidden gems” (hypothetical data): Total Sales Average Sales

19. 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

20. 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 • Social media monitoring tool (Radian6, Techrigy, Buzzmetrics, etc.) • Business intelligence tools Site Content Media Type • Search engine/panel data (Google Ad Planner, Microsoft Adcenter, Quantcast, etc.) Referring Site Demographics Traffic At Referring Site • Panel-based data (e.g., comScore, Compete, etc.)

21. 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/Quoteds • Key Messages • Competitor Mentions • Industry Issues • Story/Post size • Brand Prominence • Product Mentions

22. 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: Sentiment, product mentions, messages, story length, etc. Online Media Content

23. 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” Sentiment Audience/ Site Attributes Site Types/Categories Key Messages Site Demographics Competitor Mentions Site Traffic Industry Issues Web Analytics Metric Regression Story/Post Size Product Mentions Content/ Message Attributes

24. Ranking by Coverage Attributes by Importance • Statistical Output Helps: • 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 What Drives Sales? What Drives Visitors?

25. Tying It All Together Creating a Causal Model Using Path Analysis or SEM Sentiment . .48 Sales Messages .88 .25 Visitors Referring Site Traffic .74

26. Playbook Drives Visitors Drives Engagement

27. Playbook Drives Visitors Drives Engagement

28. Final Thoughts

29. Caveats Practical Limitations Technical Limitations • Reliance on cookies • Reliance on clickthroughs • Mobile devices and javascript • You can’t directly track offline activity • Messy Data • Integration requires additional software or technical skill • Time consuming manual analysis/Communications team bandwidth

30. Future Directions Click-throughs View-throughs

31. 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?

32. Takeaway Messages • Web analytics allow communications teams to use the same types of measurement as other forms of marketing • Web analytics can show what sites and stories/posts are driving the most traffic and engagement on a corporate website “out of the box” • 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 • 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