web analytics sethu iiml
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Sethuraman Janardhanan
2011
Web Analytics : A Primer
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Agenda / Tracker Page
Web Analytics and Advantages
Web Analytics process
Metrics Used in Web Analytics
Analytical Benefits
Some Web Analytics Demo
Web Analytics Tools
Search Engine Marketing (SEM)
Search Engine Optimization (SEO)
Social Media Analytics (SMA)
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What is Web Analytics
Web Analytics refers to the process of collection, measurement and
analysis of user activity on a website to understand and help achievethe intended objective of the website (Increase conversion etc)
Advantages
Evaluate visitor behavior according to your business goals
Lower customer acquisition cost
Improve customer satisfaction, retention and loyalty
Increase conversion levels
Improve the design and processes of your website
Track and analyse the effect of your marketing campaigns
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How Web Analytics Process works ?
Web site
Decision
Maker
Log files
100 90 80 70
Generate Insights
Visitors
Log TransactionsResponse
Request
All Stakeholders
(Sales, Product, IT Teams)
Web
analytics
tool
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What kind of Metrics are Used ?
Bounce Rate The instances of visitors entering and leaving the same page.
Click Through Rate Usually used as banner ad success. It is number of clicks/
number of impressions.
Conversion An activity which fulfills the intended purpose of a website like
buying a product, filling up a form or subscribing to a newsletter. Conversion rate
is the percentage of visitors who successfully convert.
StickinessA websites capability to retain visitors, measured as number of
pages visited per session and time spent on website
Session Duration Average amount of time that visitors spend on the site each
time they visit.
Depth / Page Views per Session Depth is the average number of page views a
visitor consumes before ending their session.
Frequency / Session per Unique visitor It is calculated by dividing the total
number of sessions (or visits) by the total number of unique visitors. It can
measure degree of loyalty
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What are analytical benefits ?
Areas Advantages
Online Traffic Analysis How do people get to my website ? (Sources: Direct, affiliates, search engines)
Where do your visitors/customers come from ? (geography/websites/search etc)
Which are the most popular paths taken on your site?
On which page or section do your users spend the most time?
How engaged are your users on which pages or sections?
Where do they spend most time and to where do they return most often?
At which time of day do they visit your website?
Where are your drop-offs or increases in traffic and do they appear across all metric?
Visitor/Customer
Behaviour
What kind of visitors convert on your website ?
Is it possible to segregate and study visitors based on various behavior patterns ?
Can I segment my online buyers/visitors ?
Is it possible to recommend customers with new products or offers ?
Is there a pattern in purchase behavior of your customers ?
Can I track my loyal customers
Who are people doing fraud activities on my website (fraud detection)
Path and conversion
analysis
(e-commerce specific)
What are the most popular and profitable paths taken through your website?
What are series of steps or pages for a visitor to reach the final objective, like filling up a form or
purchasing a product.
What are the drop-offs at each level ?
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What are analytical benefits ?
Areas Advantages
Campaign Analysis &
Search Engine
Marketing/Optimisation
Which campaigns generate the biggest increase in visitors?
Which campaigns result in the most engaged visitors?
At which time of day would your online campaigns be most effective?
Which search engines and which keywords drive most traffic?
Which keywords should you bid for in paid search?
Which phrases and words work best on which search engine?
Which partnerships send the most referrals to your site?
Which referral/affiliation schemes generate the most valuable customers?
How do you do RoI analysis on different types of internet campaigns (banners, PPC, affiliate marketing etc)
Usability and Site
Reconstruction
Is the content of your site engaging? How many pages are viewed in a session?
Are users returning regularly to view new content?
Which pages and sections are the most popular and could be streamlined for increased ROI?
Which browsers and operating systems does your website need to work with?
Can you optimise your website according to the connection speed your users have?
Should you introduce more internal links to keep visitors on your site longer?
Offline Web Measurements
(text mining)
Can I know Buzz about new products in markets ?
Who could be my potential audience for my campaign ?
What people think about my brands (social networks/ blogs etc)?
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Demo : Homepage Statistics
July 4 Weekends
6.3%
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Demo : Record Descriptions
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Demo : My Goal Conversion Funnel
User visits or uses materials remotely!
User enters site after Google Search
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Few Web Analytics Tools
Google Analytics
Click tracks
Omniture (HBX)
Urchin
Statcounter
WebTrends
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Social Media Analytics (SMA)
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What is SMA ?
Social Media Analytics are tools used in the measurement of activity
within social media spaces from around the web.
They can be used to measure conversation, engagement, sentiment,
influence and other social media specific attributes.
Social Media Analytics tools are used to monitor conversations on
blogs, social networks, video views, ratings, and favorites on videosharing networks, and an array of other activities in other social media
destinations.
The main uses for social media analytics tools are for brand monitoring
and brand audits to provide insightful information for brands looking to
participate in social media and already in the space. Most recently,
Social Media CRM tools also fall into this category, such tools are used
in blogger outreach and community outreach to manage relationships
with key influencers.
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Few examples of SMA
The most popular social media platforms right now include
Facebook and MySpace (social networks)
LifeHackerand Mashable (blogs), Twitterand Tumblr(micro-blogs)
YouTube and Veoh (video sharing networks)
Flickr(image sharing).
Last.FM (personal video discovery), Wikipedia (reference), and
SecondLife (virtual reality).
Sentiment Metrics and Measurement
Analysis on social networks like FaceBook, Orkut etc
Analyzing the opinions on Blogs
Website Analytics
Measuring activity on the social media websites
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Blogsphere
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The Blogsphere
The new way to communicate
Millions of text articles posted daily
From all over the globe
A wide variety of topics, from sports to politics
Forms a huge repository of human generated content
A high volume temporally ordered stream of text documents
Challenge: discover persistent chatter
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BlogScope
Live blog search and analysis engine
Tracking over 13 million blogs, 100 million posts
Serves thousands of daily visitors
Visit: www.blogscope.net
Nilesh Bansal, Nick Koudas, blogScope: A System for
Online Analysis of high Volume Text Streams, VLDB
2007, Demonstration Proposal
Nilesh Bansal, Nick Koudas, Searching the
Blogosphere, WebDB 2007
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Persistent Chatter
Apple iPhone January
2007
Jan first week: Anticipation
of iPhone release
Jan 9th: iPhone release at
Macworld
Jan 10th: Lawsuit by Cisco
Jan third week: Decrease in
chatter about iPhone
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Keyword Clusters
When there is a lot of discussion on a topic, a set of keywords
will become correlated
Elements in this keyword set will frequently appear together
These keywords form form a cluster
Associated with time interval
As topics recede, these cluster will dissolve
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Stable Clusters Apple iPhone
Persistent for 4 days
Topic drifts
Starts with
discussion about
Apple in general
Moves towards theCisco lawsuit
Note: All keywords are stemmed
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Why Stable Clusters
Information Discovery
Monitor the buzz in the Blogosphere
What were bloggers talking about in April last year?
Query refinement and expansion
If the query keyword belongs to one of the cluster
Visualization?
Show keyword clusters directly to the user
Or show matching blogs