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Digital Analytics Compared to the Network Effect

Introductory presentation on Digital Analytics for Social and Digital Media communities of practice. Covers basic principles of digital analytics, Robert Metcalfe's Law of the potential value of networks, and three levels of analytics maturity.

Eric Hansen

on 21 April 2016

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Transcript of Digital Analytics Compared to the Network Effect

Eric Hansen
Sr. Product Manager, Analytics
What is Digital Analytics?
Introduction to Analytics
Larger Network = Larger Value
What is the Network Effect?
Metcalfe's Law: The Network Effect
Think about how you apply the principles of measurement, refinement, and optimization.
Getting Started: The Magic Three of Media
The first step:
Establish the goal you want to measure before starting, not as an afterthought.
Collecting the right data at the right time
Analytics "Good" Practices: Measure
Analytics & The Network Effect
Measuring, Refining, and Optimizing Results
Taking it to the next level:
Recognize secondary drivers and opportunities to improve.
Distill insights from the data
Analytics "Better" Practices: Refine
Practices: Optimize
The ultimate state:
Iterative improvement
Own Your Part in the Visitor Journey
Create a Case Study
Think about and present on a recent content project you worked on:
Measurement and reporting data on digital properties (i.e. websites, mobile apps, videos) that answer the following questions:
Who - audience information about visitors
What - the content consumed
Where - geo-location and visit path on the site
When - time of day, day of week, and duration
How - traffic sources and technology
Twitter: @ehansen9
LinkedIn: /in/ericandrewhansen
What does an Analytics team help solve?
Strategy - what should you measure?
Implementation - how do you collect the data?
Reporting - what are the results?
Attributed to Robert Metcalfe, the potential value of a network of communication devices is proportional to the square of the number of connected users.
Where do we see the Network Effect?
Telephone networks, computers connected to the Internet, the number of users in a social network...
...and in Analytics, too!
Dimensions can represent individual nodes in a network of data, and Metrics can represent the communication that occurs throughout the network.
Proactive analysis and segmentation of the data can lead to incredible insights about the success
or failure of any content. Example tools include:
Filtering, Breakdowns, and Segmentation
Ratio analysis (i.e. average page views per visit)
Anomaly detection to guide investigations
Whether you focus on acquisition through social media, engagement through user experience design, or ultimate success metrics through product management, leverage analytics to inform and inspire the part you play in the visitor's journey.

Conversion Funnels
Fallout Reporting
Contextual analysis
How many people were reached by your content?
How many clicked-through?
What portion of visitors are new vs. returning?
How often (if ever) do visitors return?
How long do visitors engage with your content?
What metrics indicate engagement?
Did you measure it?
Did you refine it?
Did you optimize it?
Make analytics planning part of your content creation process,
just an afterthought.
Identify the primary business requirement(s) of the site or application. All measurement activities will focus on measuring drivers and desired outcomes described by those business requirements. Common focal points for content & media include:

Return Frequency
Time Spent

Results at this level focuses
on just the raw numbers and trends.
Full transcript