Mobile Analytics: Digital Strategies and Measurement Challenges
In this webcast Greg Dowling of Semphonic gives practical advice on…
> Why Mobile Matters > Mobile Measurement > Mobile Strategy
American Marketing AssociationApril 2010
Mobile Analytics:Digital Strategies and Measurement Challenges
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• Semphonic is the world’s largest independent Web analytics consultancy. Founded in 1997, the company has helped leading corporations, government agencies and non-profits achieve measurable improvement in the performance of their web channel. Clients include American Express, Charles Schwab, National Cancer Institute, Nokia, Genentech and Intuit.
About Semphonic
Portland
San Francisco
Boston
New YorkWashington, DC
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AGENDA:
- WHY MOBILE MATTERS - NOKIA MOBILE DATA STRATEGY - MOBILE MEASUREMENT - MOBILE STRATEGY
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WHY MOBILE MATTERS
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Mobile is the most popular and rapidly adopted personal technology in the world.
Why Mobile Matters
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Why Mobile MattersMobile web browsing is experiencing a meteoric rise, but still a small percentage.
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Why Mobile Matters
Net Applications, February 2010
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Why Mobile MattersSmartphones will make up nearly half of all U.S. handset sales by 2011.
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Why Mobile MattersMobile device operating systems vary widely depending on geographic location.
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Why Mobile Matters
Source: Gartner
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Why Mobile Matters
Source: GartnerSource: Gartner
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Why Mobile MattersiPhone users have most applications installed, followed by Android
Nielsen, Q4 2009
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Why Mobile MattersMobile application downloads will double in 2010 to 4.5B with $6.8B in revenue.
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Why Mobile MattersMobile commerce expected to triple by 2013 with 68B in global revenue.
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Why Mobile MattersUS mobile advertising spending to triple by 2013 with 70% currently “doing something”
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NOKIA MOBILE DATA STRATEGY
18 © 2008 Nokia
A history of hi-tech and innovation
• Founded in Tampere in 1865• Finnish Rubber Works Ltd. 1898 • Finnish Cable Works Ltd. 1912 • Nokia Corporation 1966• Electronics began in 1967
19 © 2008 Nokia
A history of hi-tech and innovation
• Founded in Tampere in 1865• Finnish Rubber Works Ltd. 1898 • Finnish Cable Works Ltd. 1912 • Nokia Corporation 1966• Electronics began in 1967
20 © 2008 Nokia
A history of hi-tech and innovation
• Founded in Tampere in 1865• Finnish Rubber Works Ltd. 1898 • Finnish Cable Works Ltd. 1912 • Nokia Corporation 1966• Electronics began in 1967
21 © 2008 Nokia
A history of hi-tech and innovation
• Founded in Tampere in 1865• Finnish Rubber Works Ltd. 1898 • Finnish Cable Works Ltd. 1912 • Nokia Corporation 1966• Electronics began in 1967
22 © 2008 Nokia
A history of hi-tech and innovation
• Founded in Tampere in 1865• Finnish Rubber Works Ltd. 1898 • Finnish Cable Works Ltd. 1912 • Nokia Corporation 1966• Electronics began in 1967
23 © 2008 Nokia
A history of hi-tech and innovation
• Founded in Tampere in 1865• Finnish Rubber Works Ltd. 1898 • Finnish Cable Works Ltd. 1912 • Nokia Corporation 1966• Electronics began in 1967
24 © 2008 Nokia
A history of hi-tech and innovation
• Founded in Tampere in 1865• Finnish Rubber Works Ltd. 1898 • Finnish Cable Works Ltd. 1912 • Nokia Corporation 1966• Electronics began in 1967
25 © 2008 Nokia
A history of hi-tech and innovation
• Founded in Tampere in 1865• Finnish Rubber Works Ltd. 1898 • Finnish Cable Works Ltd. 1912 • Nokia Corporation 1966• Electronics began in 1967
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“Everything came to us in a device that could fit into a pocket”
Convergence
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Connecting
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The Consumer Data StrategyNokia´s future success as a direct to consumer business required efficient and innovative use of consumer data
Nokia needed to develop Consumer Data as a strategic asset
•Engaging consumers to foster a continuous relationship with Nokia
•Developing targeted and relevant sales and marketing efforts
•Developing more consumer-driven services and solutions
Realizing synergies and building up common enablers was key for utilizing consumer data as a strategic asset
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The Consumer Data Situation
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Common language was missing • No common definitions for consumer data
The Consumer Data Situation
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Consumer data was fragmented• Consumer data in multiple fragmented
databases, with limited capability to combine on service wide level
Common language was missing • No common definitions for consumer data
The Consumer Data Situation
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Consumer data was fragmented
Consumer data quality was poor
• Consumer data in multiple fragmented databases, with limited capability to combine on service wide level
• Lack of common data models and data management practices led to poor quality
Common language was missing • No common definitions for consumer data
The Consumer Data Situation
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Consumer data was fragmented
Consumer data quality was poor
Analytics competencies missing
• Consumer data in multiple fragmented databases, with limited capability to combine on service wide level
• Lack of common data models and data management practices led to poor quality
• Need for competent data analyst resources at Nokia far exceeded current levels
Common language was missing • No common definitions for consumer data
The Consumer Data Situation
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Consumer data was fragmented
Consumer data quality was poor
Analytics competencies missing
Consumer data & insights were not part of business processes
• Consumer data in multiple fragmented databases, with limited capability to combine on service wide level
• Lack of common data models and data management practices led to poor quality
• Need for competent data analyst resources at Nokia far exceeded current levels
• Consumer data not consciously in the scope of developing and operating a service or innovating new business models
Common language was missing • No common definitions for consumer data
The Consumer Data Situation
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Consumer data was fragmented
Consumer data quality was poor
Analytics competencies missing
Consumer data & insights were not part of business processes
Marketing activities not guided by common principles
• Consumer data in multiple fragmented databases, with limited capability to combine on service wide level
• Lack of common data models and data management practices led to poor quality
• Need for competent data analyst resources at Nokia far exceeded current levels
• Consumer data not consciously in the scope of developing and operating a service or innovating new business models
• Lack of common marketing campaign tracking and optimization principles and practices
Common language was missing • No common definitions for consumer data
The Consumer Data Situation
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Consumer data was fragmented
Consumer data quality was poor
Analytics competencies missing
Consumer data & insights were not part of business processes
Marketing activities not guided by common principles
• Consumer data in multiple fragmented databases, with limited capability to combine on service wide level
• Lack of common data models and data management practices led to poor quality
• Need for competent data analyst resources at Nokia far exceeded current levels
• Consumer data not consciously in the scope of developing and operating a service or innovating new business models
• Lack of common marketing campaign tracking and optimization principles and practices
Common language was missing • No common definitions for consumer data
The Consumer Data SituationConsumer data NOT regarded as an asset
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MAKING THE HARD DECISIONS
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PeopleProcessTools
Nokia Mobile Data Strategy
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People
Nokia Mobile Data Strategy
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A special working group with the charter and the resources to address Nokia’s Consumer Data issues.
NOKIA Vision: To Become a Consumer Driven Internet Company.
CDI Program Vision: Consumer Data Is An Integrated Part of Nokia Business.
CDI Mission:1. Build Consumer Data Into a Strategic Asset2. Communicate In-Depth Consumer
Understanding 3. Utilize Consumer Data Effectively By:
• Engaging consumers to have a continuous relationship with Nokia
• Developing targeted sales and marketing efforts
• Developing more consumer-driven solutions
• Operating in direct-to-consumer businesses and uplifting mobile advertising business
Consumer Data & Interaction Program
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Purpose:• Lead the Services wide consumer data initiative
and enable fact based decision making• Improve the speed and quality of customer
relationship management and product development
Accountability:• Consumer data strategy implementation• Analysis and cross promotion capability based on
user data• Services level dashboards, Learning Agendas,
and Optimization PlansCommon definitions
Results
Analysis
Services Intelligence & Analytics
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PeopleProcess
Nokia Mobile Data Strategy
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Acquire Engage
Retain Convert
What % of the target audience did the service reach?Where does the traffic come from?What is the cost ?
Are we getting users to interact with the service?Are we building their trust?What is the cost ?
Are visitors performing the actions that will lead to our success?Are these actions making our business successful?What is the cost ?
Are we building loyalty?Are the users converting again over time?Are the users recommending our service?What is the cost ?
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the user experience
Acquire Engage
Retain Convert
What % of the target audience did the service reach?Where does the traffic come from?What is the cost ?
Are we getting users to interact with the service?Are we building their trust?What is the cost ?
Are visitors performing the actions that will lead to our success?Are these actions making our business successful?What is the cost ?
Are we building loyalty?Are the users converting again over time?Are the users recommending our service?What is the cost ?
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Unified Nokia Standard
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How did we document KPIs?
Business goals & resources used to achieve these goals
Definitions of the AECR events specific to the service
KPIs, Metrics & Funnels used to measure these goals
List of all the data needed to populate the KPIs, Metrics & Funnels
Campaigns specific KPIs & Metrics
Goals
KPIs, Metrics & Funnels
AECR events
Data list
Campaigns
Unified Nokia Standard
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How did we document the Reporting Plan?
Lists all the dashboards and reports to be delivered
Describes the detailed specifications of each and every dashboard and report listed
List all the users access rights for access to the online versions of the reports
Dashboards
Access rights
Dashboards details
Unified Nokia Standard
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How did we document the Implementation Plan?
Unified Nokia Standard
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How did we document the Implementation Plan?
Unified Nokia Standard
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How did we document the Implementation Plan?
Unified Nokia Standard
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How did we document the Implementation Plan?
Unified Nokia Standard
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How did we account for cross platform visibility?
Unified Nokia Standard
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PeopleProcessTools
Nokia Mobile Data Strategy
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Vendor Evaluation ProcessCriteria for Evaluation• Ease of implementation• Traditional tracking• Mobile tracking• Reporting capacity• Analytics capacity• Business user usability• Analyst usability• Data export• Data import• Administration• Information security• Data storage• Legal
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Vendor Evaluation ProcessCriteria for Evaluation• Ease of implementation• Traditional tracking• Mobile tracking• Reporting capacity• Analytics capacity• Business user usability• Analyst usability• Data export• Data import• Administration• Information security• Data storage• Legal
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Vendor Evaluation ProcessCriteria for Evaluation• Ease of implementation• Traditional tracking• Mobile tracking• Reporting capacity• Analytics capacity• Business user usability• Analyst usability• Data export• Data import• Administration• Information security• Data storage• Legal
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Vendor Evaluation ProcessCriteria for Evaluation• Ease of implementation• Traditional tracking• Mobile tracking• Reporting capacity• Analytics capacity• Business user usability• Analyst usability• Data export• Data import• Administration• Information security• Data storage• Legal
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Omniture Suite for Web Analytics Data Warehouse for Centralized Consumer Data Management
Tool Selection
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Omniture Semphonic
Mobile StandardTechnical Support and Review
Best PracticesImplementation Support
Fixed Web StandardAECR Framework Integration
Implementation Design and Support
Consulting Partners
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MOBILE MEASUREMENT
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Platform Limitations• JavaScript is often not present or enabled• Cookies may not be allowed or may be very short-lived• Browsers are non-standard
Carrier Limitations• Some carriers aggressively strip HTTP headers so you
don’t get everything you’d expect• Character limits on image requests limit the amount of
information you can pass
Integrated Applications• Apps are significant part of mobile
Measurement Challenges
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Measurement Strategies• There are four common Mobile Measurement Strategies
• JavaScript tagging as per the fixed web
• Server-side image requests
• Wire Line Capture
• API Collection & Insertion
• Each has some advantages and each has some significant disadvantages
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JavaScript Tagging
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Server Side Image Requests
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Wire Line Capture
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API Collection & Insertion
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Potential Pitfalls• Unique Visitor Identification
• Cookies are often problematic• SubscriberID sometimes stripped and unavailable.• Consider ‘waterfall’ or ‘hybrid’ methodology
• Robots and Spider Detection• JavaScript solutions won’t work in most mobile scenarios• Mobile traffic DOES HAVE significant robotic presence
• Mobile Applications• Early integration with development• Map data to fixed and mobile web• More rigorous testing required
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So what did Nokia do?
• Image Tags for Mobile
• XML Data Insertion API for Mobile Apps• 1st Party Cookie for fixed web, Subscriber ID for Mobile Web,
application identity (UUID) for mobile apps.• Capture visitorID method (Subscriber ID, cookie, UA & IP) and
Device Type as variables• Use of obfuscated Nokia Account ID to create a cross-channel
view for fixed web, mobile web and mobile applications.• Separate report suites for each channel with different keys –
insertion managed by automated rules.
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MOBILE STRATEGY
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• Get S.M.A.R.T with mobile
Mobile Strategy
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• Get S.M.A.R.T with mobile
Mobile Strategy
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• Get S.M.A.R.T with mobile
Mobile Strategy
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Strategy
Measurement
Analysis
Reporting
Tactics
Mobile Strategy
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Strategy Assess your ‘Mobile Readiness’o Determine product suitabilityo What are your objectives?o What is your commitment?o What is the ROI?
Mobile Strategy
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Measurement Define a ‘Measurement Plan’o Establish KPIso Tie KPIs to business objectiveso Evaluate enablement optionso Assess technical limitations
Mobile Strategy
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Analysis Establish intelligent ‘Correlations’o Appropriate dimensionso Fixed web vs. mobile webo High value taskso Integration with offline data
Mobile Strategy
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Reporting Make strategic information ‘Obvious’o Leverage data visualizationo Allow for data interactiono Appropriate level of detailo Automate where possible
Mobile Strategy
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Tactics Generate ‘Actionable Insights’o Let data define actionso Enhance segmentationo Channel optimizationo Leverage experimental design
Mobile Strategy
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Summing Up
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Summing Up
Determine your ‘Mobile Readiness’
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Summing Up
Determine your ‘Mobile Readiness’ Define a ‘Measurement Plan’
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Summing Up
Determine your ‘Mobile Readiness’ Define a ‘Measurement Plan’ Establish intelligent ‘Correlations’
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Summing Up
Determine your ‘Mobile Readiness’ Define a ‘Measurement Plan’ Establish intelligent ‘Correlations’ Make strategic information ‘Obvious’
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Summing Up
Determine your ‘Mobile Readiness’ Define a ‘Measurement Plan’ Establish intelligent ‘Correlations’ Make strategic information ‘Obvious’ Generate ‘Actionable Insights’
Thank you!Email: [email protected]: @gregdowling
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