web analytics sethu iiml

7/27/2019 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

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