Engage 2013 - Integrated Campaign Reporting + MTA
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Transcript of Engage 2013 - Integrated Campaign Reporting + MTA
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INTEGRATED CAMPAIGN REPORTING + MULTI-TOUCH ATTRIBUTION Brandon Ralls Director, Digital Intelligence Lab
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Introduction
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• Agency Perspec,ve
• Analy,cs Consul,ng
• Digital Marke,ng
• Data Visualiza,on
Background
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1) Performance across digital channels
2) Mul,-‐touch aBribu,on (MTA)
3) Integrated repor,ng
4) Implemen,ng campaign tracking
5) Client stories
Topics for Discussion
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How do I begin to understand
campaign performance across
multiple digital channels?
Topic 1: Performance across digital channels
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Digital Landscape
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• Landing page
• Hero image
• Specific CTAs
• Videos
• Whitepapers
• Promotions
• Lead gen forms
• Downloads
• Special offers
Ways to Engage
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Complex Agency Network
Media • Planning • Buying • Trafficking
Creative • Messaging • Asset creation
Development • Site development • Tagging & tracking
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Complex Agency Network
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Complex Agency Network
Challenges • Silos of data
• Disjointed story
• Different cadences
• Different formats
• Difficult to rationalize
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User Behavior
Our Objective Link specific media placements to actions on our site and determine what attributes influence behavior
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Digital Ecosystem
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Topic 2: Multi-Touch Attribution (MTA)
What is cross-channel, or
multi-touch attribution?
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MTA Overview
First Click Last Click Equal Weighted
• Basic approach
• First interac,on receives 100%
• Not accurate representa,on
100% 0% 0% 0% 0% 100% 33% 33% 33% 15% 35% 50%
Low Sophis,ca,on
• Most common approach
• Last interac,on receives 100%
• Not accurate representa,on
• Moderate sophis,ca,on
• Each interac,on receives equal
• Good direc,onal perspec,ve
• Most sophis,cated
• Each interac,on propor,onately weighted
• Most accurate representa,on
High Sophis,ca,on
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Example Scenario
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Example Scenario: First Click
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Example Scenario: Last Click
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Example Scenario: Equal Weight
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Role of Channel
First Touch Last Touch Secondary Touches
Touch type helps us understand role each channel plays:
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Topic 3: Integrated Reporting
How can integrated reporting with
MTA enhance my understanding of
my digital marketing campaigns?
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Decisions
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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?
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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
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Sample Questions
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Topic 4: Implementing Campaign Tracking
How do I implement campaign
tracking to enable integrated
reporting and MTA?
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The World as a Pivot Table
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How Do We Do This?
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Establish a Process
If you aren’t proacLvely capturing data, it won’t magically become available once your campaign goes live.
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Establish a Process
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Campaign Attributes
• Campaign Type: Seasonal Promo,on
• Campaign Name: Back to School 2012
• Campaign Goal: Target college students
• Launch: July 2012
• End: September 2012
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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
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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
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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
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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)
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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?
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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
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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
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1-to-1 Relationship
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Topic 5: Client Stories
How has Webtrends helped
others solve these problems?
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Red Bull Case Study
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Business Challenge
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Solution Overview
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Data Visualization + MTA
Web-based data visualization • Streamline reporting
• Enhance time to insight
• Provide comprehensive view
• Actionable through visualization
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Business Value
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Microsoft Case Study
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Background
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Business Challenge
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Webtrends Solution Webtrends provided Microsoft with end-to-end support through campaign planning, vendor management, and ongoing analysis and recommendation
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Business Value • Unified measurement approach
• Consistency in tagging and tracking
• Adoption of standardized processes
• Automated reporting
• Quick time to analysis
• Actionable insight and recommendations
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Final Thoughts
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Items to Remember
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Questions?
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Thank you Brandon Ralls
Director, Digital Intelligence Lab