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Webtrends Data Access And Integration

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Webtrends Data Access And Integration

  1. 1. WebTrends Data Access and Integration John DeFoe Vice President of Solution Services Guest Speaker Tom Masterman Internet Broadcasting
  2. 2. Agenda • Explore the possibilities of data access and integration through real world integration and data access examples – Site optimization – feed WebTrends data back to your site for higher clickthroughs – Email targeting/remarketing– increase conversion by automating remarketing to specific targeted segments. – CRM – get a comprehensive view of your customer and create targeted leads based on site engagement from the missing channel in your CRM system.
  3. 3. Open Exchange with WebTrends Connect
  4. 4. Optimizing Distributed Ad Products Tom Masterman Internet Broadcasting
  5. 5. Agenda • About Internet Broadcasting • The “DAP” dilemma • Instant insights with custom reports • Optimization through automated data integration • Future plans & lessons learned
  6. 6. About Internet Broadcasting • Leading provider of Web sites, content and advertising revenue solutions to the world’s largest and most successful media companies – Partners include Hearst-Argyle, Post-Newsweek, McGraw-Hill, Cox Television, Meredith Broadcasting, Telemundo and CNN • Ad network of 500+ local media properties – 40-50mm monthly UVs, 93% U.S. market reach • Worked with WebTrends for 5 years – Began with ’04 Olympics – Rolled out WebTrends across network in ’06
  7. 7. The “DAP” Dilemma • Distributed Ad Products (DAP) Premium paid links – “Links We Like” – Strategic advertisers – IB controls & customizes the content – Runs on media sites across the U.S. – • Business issue Limited click data via DART – Difficult to extract and interpret reports – Content selected by gut instinct – Impossible to price the value of the product –
  8. 8. Instant Insights • Leveraged WebTrends custom reporting – Impressions tracked using existing tag – Also began tracking click-throughs – Created click-through reports using custom reports and calculated measures – Automated translation file uploaded daily to translate values from our CMS • Instant insights – Clicks and CTR for: Advertiser • Link title • Link position • Site, section, page •
  9. 9. Data Integration: Why We Did It • Limitations of the UI – Tons of great data, but difficult to derive deep insights – Content editor was “cherry picking” just the top performing links • Needed to connect to external cost per click data • Wanted the data to end up in Excel for analysis
  10. 10. Data Integration: What We Did • Import data from WebTrends using variety of automated tools – Making the transition from manual exports, to scheduled reports, to APIs • Set up automated script: – Parse the WebTrends data – Marry it to external metrics – Organize in a way more relevant to editor
  11. 11. Data Integration: Samples
  12. 12. Data Integration: The Results • Click-through and revenue generation quot;Links We Likequot; $ RPM $ doubled within a month $ Revenue Per 1000 Impressions $ • Vastly outperformed Google AdSense • Plateau occurred once editor ran out of obvious insights • Down economy has presented an ongoing challenge with click-through conversion • Continue to outperform AdSense • New optimization reports have greatly 19 26 /3 0 7 4 1 /1 /1 /2 /3 improved workflow, saving hours of work 10 9/ 9/ 10 10 10 10
  13. 13. Future Plans • Currently producing daily corporate scorecard leveraging WebTrends APIs – Populating key WebTrends metrics in to IB data archive – Automatically pulling data out of archive in to report • Next steps with DAP tracking – Integrate data in to rules based engine leveraging APIs – Completely automated optimization and performance reporting
  14. 14. Lessons Learned • Maximize custom report & calculated measured capabilities • Don’t try to solve every reporting need in the UI • Investment in APIs integration has a rapid payoff
  15. 15. Email Integration Delivering Precise and Relevant Marketing Messages
  16. 16. Audience Participation • How many of you track the effectiveness (conversions, visit duration..) of your Email Campaigns? • How many of you integrate Analytics data (Conversions, Visit Duration..) with Email Data (bounces, sents..)? • How many of you send targeted/remarketing email campaigns based on behavioral data?
  17. 17. Level 1 - Insight • Campaign Tracking: Allow users to easily see the email campaign response data in WebTrends • Make decisions based on performance
  18. 18. Level 2– Comprehensive View • Email partner campaign metrics “sent”, “bounced” and other metrics alongside WebTrends stats • Make BETTER decisions with comprehensive insight
  19. 19. Level 3– Taking Action • Targeting/Remarketing –Provide email partner visitor lists based on predefined/custom segments • Drive performance (lift) with precise and relevant messages based on behavioral data Report DB WebTrends Data Scheduler ODDB Email Partner Analytics (SFTP)
  20. 20. Example Remarketing Analytics Report
  21. 21. Data Scheduler Setup
  22. 22. Data Schedule Details
  23. 23. Data Scheduler Setup Example
  24. 24. Taking Action Prerequisites • WebTrends Product – Analytics. Yes Analytics! • Data Scheduler – SFTP • Custom Reports • Dedicated Profile – OR – Marketing Warehouse • Named Queries • NOTE: Best if requirements involve Score, complex queries or significant scale • Data Capture – Visitor ID (Obfuscated recommended) – Conversions or other remarketing criteria tagged
  25. 25. CRM Integration Similar Approach as Email Remarketing Report DB WebTrends Data Scheduler CRM ODDB Analytics (SFTP)
  26. 26. CRM Integration • Data augmentation and enrichment of web behavior at the VISITOR level • Enable actionability around contact/lead opportunities for sales and/or marketing • Provide insight into other areas of focus (interest or concern) that a lead or contact may have – X-sell/up-sell opportunities – Support/Cust Service issues • Acquistion is only part of the puzzle, focus on the 'understand, maintain & grow' areas of the customer relationship.
  27. 27. SFDC Example – Summary and Detailed Insight
  28. 28. Other Examples of Data Access/Integration Scorecards/Dashboards • Data Warehouse Feed • Top searched terms on Site • Top viewed products on site • Most viewed/emailed Articles • Partners (ForeSee Results, Optimost…) • • Tell us about your data integrations on the developer community – developer.webtrends.com
  29. 29. Keys to Integration Success Understanding both systems and data points. • Define a starting point / objective and stick to it. • Pilot and plan for iteration • Document and cross departmental collaboration • Executive buy in •
  30. 30. New REST based Web Services What are the new analytics web services? • These new services augment, not replace, current ODBC and Web Services technology. Even easier to use • Allow for trending capabilities • Make it easy to integrate into Excel • Increased performance • Provide developer support (examples, documentation, community) • Public Beta • Begins Tue April 7 • Developer site, http://developer.webtrends.com
  31. 31. To receive a copy of this presentation, text E1 and your email address to 88769. Leave a space between the keyword and your email address. EX: E1 sally@webtrends.com To rate this presentation, text WTdata and your rating on a scale of 1 to 5, 1 being fair and 5 being excellent, to 88769. Leave a space between the keyword and your rating. EX: WTdata 5 WebTrends and John DeFoe and Tom Masterman Internet Broadcasting Engage Text powered by
  32. 32. QUESTIONS? Tom Masterman John DeFoe Director, Research & Metrics VP of Solution Services Internet Broadcasting WebTrends tmasterman@ibsys.com john.defoe@webtrends.com Engage Text powered by
  33. 33. Appendix Engage Text powered by
  34. 34. Appendix
  35. 35. Web Services REST Interface Easily composed URLs that allow users to access data as XML, JSON or Excel formats Example: https://server/v1/profile/Zedesco/report/KeyMetricsSummary?period=2008.m01&format=xml
  36. 36. Methods get report data for period retrieves report data for a given profile for a given time period get report definition returns the report definition for the given report ID list reports for profile lists the reports defined for a profile list profiles provides a list of profiles for an account list profile time periods returns the time periods for a given profile
  37. 37. Report Parameters format JSON, Excel, or XML period Time period of interest, expressed as year, month, day or trend length measures Measures to return dimension The report dimension name (for example, page) search String within a dimension name; returns only rows containing that string range Number of rows to return totalsonly Set to true to return totals only
  38. 38. URL Builder Prototype New REST format foundation of creating a app like a “URL Builder”. Example, “List Profiles” is a request, “List Reports” is a request, “List Measures”, etc.

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