Web Analytics Governance and Metrics Standard
An effective web analytics practice needs proper staffing, management, planning, and diligence. To be effective, a governance committee must be formed, consisting of individuals with specific roles and responsibilities (see table below). With the right resources and clear expectations, the online business can put valuable data into action to achieve higher performance. But, how do you obtain this valuable data?
Data must traverse several stages before it is ready to be acted upon. From visitor generated raw format to the actionable metrics, data must go through processes similar to a typical factory before it’s consumable. Once raw data is sessionized and aggregated, it must go through segmentation and calculation. An analyst then slices and dices the data to find correlations and nuggets of information that is valuable to the business. Data analysis generally produces many findings. With data sharing and collaboration within the governance committee, findings can be pared down to a few high value, high confidence metrics. These will then be communicated as recommendations to the business users.
An online data driven organization usually has many contributors to the decision making process. These data consumers have many sources from which to extract data from. Even though the nature of data will be different for each of these sources (ie. marketing, finance, or technology) there need to be a baseline. A standard for data means having a common denominator, a similar yard stick by which everyone gathers and analyzes data. Some examples include how online visitor interactions are measured, eg. organization wide acceptance of measuring visitors (by cookie, login ID, or session parameter), or what constitutes a page view and does it accurately represent visitor’s interaction with business content, or what method should be used to represent bounced visits. Is it all visits with single page views, or only single page views from a filtered list of IP addresses, or those from “known” marketing programs (SEO, SEM, eMail, banner, and affiliates). The final decision on the organization’s metrics standard will depend as much on the nature of the business, as it does on the individuals in the governance committee. However, once established, everyone’s analysis and findings will be based on these standards. And only then the collective wisdom of the organization wide data becomes far more valuable than any of its single contributor.
An effective web analytics practice needs proper staffing, management, planning, and diligence. To be effective, a governance committee must be formed, consisting of individuals with specific roles and responsibilities (see table below). With the right resources and clear expectations, the online business can put valuable data into action to achieve higher performance. But, how do you obtain this valuable data?
Data must traverse several stages before it is ready to be acted upon. From visitor generated raw format to the actionable metrics, data must go through processes similar to a typical factory before it’s consumable. Once raw data is sessionized and aggregated, it must go through segmentation and calculation. An analyst then slices and dices the data to find correlations and nuggets of information that is valuable to the business. Data analysis generally produces many findings. With data sharing and collaboration within the governance committee, findings can be pared down to a few high value, high confidence metrics. These will then be communicated as recommendations to the business users.
An online data driven organization usually has many contributors to the decision making process. These data consumers have many sources from which to extract data from. Even though the nature of data will be different for each of these sources (ie. marketing, finance, or technology) there need to be a baseline. A standard for data means having a common denominator, a similar yard stick by which everyone gathers and analyzes data. Some examples include how online visitor interactions are measured, eg. organization wide acceptance of measuring visitors (by cookie, login ID, or session parameter), or what constitutes a page view and does it accurately represent visitor’s interaction with business content, or what method should be used to represent bounced visits. Is it all visits with single page views, or only single page views from a filtered list of IP addresses, or those from “known” marketing programs (SEO, SEM, eMail, banner, and affiliates). The final decision on the organization’s metrics standard will depend as much on the nature of the business, as it does on the individuals in the governance committee. However, once established, everyone’s analysis and findings will be based on these standards. And only then the collective wisdom of the organization wide data becomes far more valuable than any of its single contributor.
Business User
Role
- Responsible for budget
- Interface with business analyst
- Acts upon analysis and recommendations
Tools
- High level knowledge
Analysis
- Light analysis
Technology
- High level knowledge
Management
- Budgets and other dept/Org resources
Web Analyst
Role
- Interpreting web data
- finds nuggets of high value information
- Focus on performance and optimization of the online properties
- makes recommendations
Tools
- power user
- can interface and extract data from all tools
- configures tools
Analysis
- Deep analysis
- slice and dices data
- interprets quantitative and qualitative data
Technology
- Good understanding of designs and methods
- Assists on evaluation and recommendations
Management
- Little to no duties
Business Analyst
Role
- Interfaces with business users
- Deep understanding of the websites
- Gathers business requirements
Tools
- Interfaces with tools to extract data
- Designs reporting solutions
Analysis
- Analyzes online and offline data
- Documents requirements
Technology
- Conceptual knowledge
Management
- Some budget and human resource
Developer
Role
- Develops tagging and programming to capture business data
- Interfaces with web analyst
Tools
- Deep knowledge of web analytics tools
- Designs and develops best practices
- Documents technical requirements
Analysis
- Light analysis
- Reviews technical data for optimum online system performance and availability
Technology
- Deep knowledge of the methods and practices
- Makes recommendation on and evaluates new technology
Management
- Little to no duties
Project Management
Role
- Major project owner
- Facilitator and responsible for achieving deadlines
Tools
- High level knowledge
Analysis
- No analysis
Technology
- Understands concepts and main drivers
Management
- Manages major projects
- Overseas all resources contributing to projects
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