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Critical Web Metricsto Measure & Manage

Adrian Teh, Feb 2012

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Glossary: Measure your growth, retention, engagement, effectiveness & influenceSite Metric Type For What Formula

Viral Co-efficient Index (V)

Growth Measure the growth rate of user base Average invites X (New users/Average Invites)

Conversion Rate (%)

Effectiveness Measure effectiveness of site to get visitors to achieve a goal or call-to-action in a given time period

(# of goals achieved / Total unique visitors) X 100

Returning Visitors Rate (%)

Retention How many people come back to your site more than once

(# of returning visitor visits / Total visits) X 100

Frequency Engagement Measures how often people return to the web site # of visits / Total unique visitors

Time on Site Engagement Reflects how much time people spend using your application

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Daily Active Users Retention Reflects what % of your user base comes back each day. This is a key engagement metric because it signals high engagement, as it only includes registered users who visit each day.

(# of registered user that comes back each day / Total registered users) X 100

Social Metric Type For What Formula

Facebook Daily Active Users

Engagement Total users that has commented, liked, visited or posted content on your page each day

Facebook Analytics

Klout Score Influence 0 to 100 ranking that estimates your degree of influence within Twitter 

Klout.com

Email Open & Click through rate

Effectiveness Measure effectiveness of email marketing # Email Opened / # Email Sent# Unique clicks / # Email Opened

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High growth with low retention & engagement rate is like “pouring water into a leaking bucket”

Cohort Analysis Helps measure user engagement

over time. It helps UX designers know whether user engagement is actually getting better over time or is only appearing to improve because of growth.

In a user engagement cohort analysis, we group people based on their join date. The people who joined our service in January make up the January cohort, the people who joined in February make up the February cohort, and so on.

We then investigate how each cohort stays engaged over time, comparing the cohorts against each other to make sure that the people who joined in February are more engaged than those who joined in January, for example.

Helps to separate growth metrics from engagement metrics, because growth can easily mask engagement problems.

Sources• http://andrewchenblog.com/2008/09/08/how-to-measure-if-users-love-your-product-usin

g-cohorts-and-revisit-rates/• http://52weeksofux.com/post/646711369/cohort-analysis-measuring-engagement-over-ti

me

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