1. INTEGRATED CAMPAIGN REPORTING+ MULTI-TOUCH ATTRIBUTIONBrandon RallsDirector, Digital Intelligence Lab
3. Background • Agency Perspec,ve • Analy,cs Consul,ng • Digital Marke,ng • Data Visualiza,on
4. Topics for Discussion1) Performance across digital channels 2) Mul,-‐touch aBribu,on (MTA) 3) Integrated repor,ng 4) Implemen,ng campaign tracking 5) Client stories
5. Topic 1: Performance across digital channelsHow do I begin to understandcampaign performance across multiple digital channels?
6. Digital Landscape
7. Ways to Engage • Landing page • Hero image • Specific CTAs • Videos • Whitepapers • Promotions • Lead gen forms • Downloads • Special offers
8. Complex Agency Network Media • Planning • Buying • Trafficking Creative • Messaging • Asset creation Development • Site development • Tagging & tracking
9. Complex Agency Network
10. Complex Agency Network Challenges • Silos of data • Disjointed story • Different cadences • Different formats • Difficult to rationalize
11. User BehaviorOur ObjectiveLink specific media placements to actions on our site anddetermine what attributes influence behavior
12. Digital Ecosystem
13. Topic 2: Multi-Touch Attribution (MTA)What is cross-channel, ormulti-touch attribution?
14. MTA Overview First Click Last Click Equal Weighted 100% 0% 0% 0% 0% 100% 33% 33% 33% 15% 35% 50% • Basic approach • Most common • Moderate • Most sophis,cated approach sophis,ca,on • First interac,on • Each interac,on receives 100% • Last interac,on • Each interac,on propor,onately receives 100% receives equal weighted • Not accurate representa,on • Not accurate • Good direc,onal • Most accurate representa,on perspec,ve representa,on Low High Sophis,ca,on Sophis,ca,on
15. Example Scenario
16. Example Scenario: First Click
17. Example Scenario: Last Click
18. Example Scenario: Equal Weight
19. Role of ChannelTouch type helps us understand role each channel plays: First Touch Secondary Touches Last Touch
20. Topic 3: Integrated ReportingHow can integrated reporting withMTA enhance my understanding ofmy digital marketing campaigns?
22. Key Areas to Focus• AUDIENCE: Who you are sending? • CHANNELS: Where you are sending them from? • CREATIVE: What are they seeing that is driving their response? • CONTENT: What do they do when they land on your site? • ACTIONS: What content drives con,nued ac,on?
23. Sample Integrated Report • Channel performance • Top ﬁrst touch channels • Top last touch channels • Average touches • Average latency • Touch distribu,on • Paths to convert • Role of channels
24. Sample Questions
25. Topic 4: Implementing Campaign TrackingHow do I implement campaigntracking to enable integrated reporting and MTA?
26. The World as a Pivot Table
27. How Do We Do This?
28. Establish a ProcessIf you aren’t proacLvely capturing data, it won’t magically become available once your campaign goes live.
29. Establish a Process
30. Campaign Attributes• Campaign Type: Seasonal Promo,on • Campaign Name: Back to School 2012 • Campaign Goal: Target college students • Launch: July 2012 • End: September 2012
31. Audience Attributes• Gender: Male • Age: 18-‐24 years old • Geo: In the United States • SituaLon: Going oﬀ to college • ObjecLve: Looking for a new laptop • Focus: Focused on portability vs. processing power • Desire: Want something cool and cu`ng edge • Digital Space: Highly engaged in social media • PlaVorm: Highly engaged on mobile
32. Media Attributes• PlaVorm: device where user is exposed to media • Channel: types of media you buy • Publisher: sites where users are exposed to media • TacLc: method for delivering media • Placement: name of the ad that is displayed • CreaLve type: method for delivering message • CreaLve size: size of the actual placement displayed • CreaLve name: version of the ad displayed
33. Site & Content Attributes• LocaLon: where on the site the ac,on takes place • Category: the general category of the ac,on • Name: the actual name of the ac,on • Type: the type of ac,on performed
34. Webtrends Tags• Base JS tag: standard tag for Webtrends Analy,cs that generates a log entry • WT.mc_id: Webtrends campaign ID (used to capture media placement IDs) • WT.tsrc: Webtrends traﬃc source parameter (used to capture organic sources) • WT.z_loc: Custom tag (used to track where on the site an ac,on occurs) • WT.z_cat: Custom tag (used to specify the category of ac,ons) • WT.z_name: Custom tag (used to specify the name of an ac,on) • WT.z_type: Custom tag (used to specify the type of ac,on)
35. Media Metrics• Spend: how much am I paying to get my message out there? • Impressions: how many eyeballs are exposed to my message? • Responses: how many people are compelled by my message? • Response Rate: how eﬃcient is my media at ge`ng people to respond? • Cost per Response: how much does it cost me to get a visit to my site?
36. Web Metrics• Visitors: unique number of people who came to your site • Visits: number of sessions on your site • Bounce Rate: % of people who landed on your site but did not engage further • Visits per Visitor: number of ,mes people return to your site • Return Visit Rate: % of total traﬃc who come back to your site • Visit DuraLon: length of an average session on your site • Views: number of pages rendered on your site • Views per Visit: average number of pages rendered in a session • Conversion AcLons: number of engagement ac,ons performed • Conversion Rate: rate at which engagement ac,ons are performed • Cost per Conversion: cost of driving a user to engage • AOV (if ecommerce): average size of an order placed on your site
37. Linking Systems Together • Aligning media IDs to WT.mc_id enables integra,on • Several dependencies to ensure process works as expected o Ability for agency to pass media ID value used by ad traﬃcking tool as value in Webtrends parameter o Standardiza,on of naming conven,ons in the lookup o The ability for agency to provide campaign lookup ﬁle
38. 1-to-1 Relationship
39. Topic 5: Client Stories How has Webtrends helpedothers solve these problems?
40. Red Bull Case Study
41. Business Challenge
42. Solution Overview
43. Data Visualization + MTA Web-based data visualization • Streamline reporting • Enhance time to insight • Provide comprehensive view • Actionable through visualization
44. Business Value
45. Microsoft Case Study
47. Business Challenge
48. Webtrends SolutionWebtrends provided Microsoft with end-to-end support through campaign planning,vendor management, and ongoing analysis and recommendation
49. Business Value • Unified measurement approach • Consistency in tagging and tracking • Adoption of standardized processes • Automated reporting • Quick time to analysis • Actionable insight and recommendations
50. Final Thoughts
51. Items to Remember
53. Thank you Brandon Ralls Director, Digital Intelligence Lab