There is a danger here, the easy use of GUI tools on large amount of data available is tempting and which makes users tempt to use black box methodologies available in the tools to solve their business problems. They mistakingly assume data mining is all about using a tool and running the data on the tool, this can be very hazardous and dangerous as actions are taken on business decisions.

Little knowledge is dangerous while applying powerful models.

Since the underlying logic used for model building in automated tools are unknown (their internal assumptions are unclear). Therefore it is very easy to do it in the wrong way assuming it is the right solution. Such mistakes are still made in companies.

People sometimes might argue that there is always a simpler solution to problems. I am the person who belives in Occam’s Razor, which means simplest explanation is always the best way. This means the interpretation of the model and the final solution should be as simple as possible. However,  method of arriving at solution must be as detail as possible taking every factor, element into consideration. Analysts must not make the mistake of over simplyfying the method and make too many assumptions.

A lot of knowledge workers believe that predictive modeling process can be automated by using tools and statistical software. These software are certainly useful but cannot replace the intellectual  of the analyst.

The processof building the model must be as detailed as possible, it has to tried & tested on various data and measured by various parameters. All possible factors must be considered while building the model.

Therefore Analyst must understand the underlying algorithm , process of arriving score, model design etc.

More on such articles regarding online marketing, data mining, data modeling can be found at http://www.praveenkodur.com/blog

Focus for many companies such as Banks, Insurance companies, Telecommunication companies is to track customer end to end, from the time money spent on the customer acquisition to the time revenue is generated from the consumer for product/service until the customer attrites from the firm. Every activity in the chain must be closely observed to evaluate the true value of customer.  Companies worldwide are creating process to deal with customers  individually.  This can help them devout more attention to customers who are more valuable to the business and let go customers not valuable to business.

Data Mining requires a lot of effort/techniques and focus to centre their business around the customer than a product. Companies have to constantly keep a watch on what their customers are doing, keep in mind their past actions, discover knowledge from their actions (gain knowledge)  and finally use the knowledge cleverly to make decisions to make profit.

However data mining is not always beneficial for the user, consider the fact a model recommends a service to a user instead of the product A. however if the business makes more profit on product and very negligible amount on service. Model recommendations may not be implemented. However it helps in understanding such customers.

Good question to ask is how can a consumer company with large base of customers can individually deal with each consumer. This can be accomplished intelligently by deploying effective technology solutions which is customisable based on data mining models and techniques. Nowadays the customer is the data entry operator who enters data into the system at various points and these are captured by the system.  Consider your bank, your touch points are ATM, Bank Branch, customer care who responds on phone, mail, hard mail & lastly your account /loan/credit card that you hold of the bank. Each transaction records your behaviour which can be an additional knowledge that bank is made aware of, this knowledge can be used by the bank to learn more about you and customise the next interaction or next touch point instance with you.

The transaction system records every instance of transaction of the user enabling the bank to analyse the nature of every transaction and update your profile with rich insights. The knowledge discovery doesnt end here. It needs support of data warehousing system along with extremely good data mining models to be able to take action / make decisions and deal with each customer. More on this will be written in more detail in coming articles.

The blog  http://www.praveenkodur.com/blog/ will be updated with more such analytics, online marketing articles.

Most website users have already used Google Analytics as online visitor reporting tool, however new features like Custom reports / Advance segmentation has upgraded it to an analysis tool. With Google Analytics you can achieve detailed analysis to make well informed decisions for online marketing & Internet business in general.

Some of the new features in Google Analytics are:

Advanced Segmentation: This is a most important feature to segment GA data as per your criteria.

a. Define segments based on any Site metrics, Traffic, Content, E-Commerce or Systems parameters available.
b. Apply these advanced segments on any report to view slice of data as per your criteria.
c. Apply more than one segment, along with overall visits for comparison.
d. Use predefined segments available by default.
e. Understand behavior of users for each segment and differentiate your action for each of them.
f. This feature along with regular expression can identify key pain points & opportunities that can make huge difference to your website.
g. E.g Segment1: Visitors landing on home page and bouncing from site.
h. E.g Segment2: Visitors landing on inner pages.

Custom Reports: This is a user defined report, where you can choose to identify elements in rows & columns in a data table.

a. Choose desired dimension parameters in rows and your desired metrics in columns.
b. Select other sub-dimensions for drilling down the reports. You can select drill down parameter to three levels.
c. Sub dimension chosen will be a slice of data from top level dimension. Since you have the ability to choose any dimensions for both levels, you can get absolutely wonderful segments.
d. E.g : First level dimension can be Geography, drill down to Top Landing pages & Network location.
e. E.g: First level can be Count of Visits, drill down to Traffic Sources, Top landing pages.
f. These reports can be saved, exported, sent to email and viewed anytime online.

Motion charts: Great Visualizing techniques like motion charts are available for users to pictorially view metrics over a time period. You can choose other site metrics as bubble sizes with different colors.

a. You need give Google motion chart API code access to your GA account.

Data Export API: Use Google Analytics API to import data from Google Servers. This is very useful as you can store GA information in your database or use it third party reporting software.

a. Export Data on Dimensions & metrics which can be used in combination for a custom report.
b. Common calculation such as formula for Bounce rate (bounces/entrances), Exit rate (exits/pageviews) and more can be found here http://code.google.com/apis/analytics/docs/gdata/gdataReferenceCommonCalculations.html

Flash & Dynamic Page tracking: Use ga.js new code for tracking dynamic pages with _trackpageview function.

a. Track Videos & various actions like pause, play, stop etc.
b. View Developer Docs present at http://code.google.com/apis/analytics/docs/

User Defined functions: You can configure Google Analytics to store user attributes like Age, Income, demographic, psychographic attributes. The website needs to capture these attributes in first place and using the setvar function in javascript code, you can pass these values to Google Servers. Setvar function overwrites new values for same cookie, to avoid this there is another function called supersetvar, which can be used to append future values to existing ones.

a. You could slice,dice, segment data on Age, Income & custom defined values.
b. View the list of functions which can be used to customized data representation in GA. http://code.google.com/apis/analytics/docs/gaJS/gaJSApi.html

Internal Site Search: Configuring your GA for site search can be done by enabling in main settings panel. You also have to give the parameter which stores the search keywords in URLs.

a. Search Exits, Bounce Rate, User behavior during search, post search and pre-search.

Ecommerce Tracking: You can use GA to store your e-commerce transactions. This is done by enabling e-commerce settings. You also need to place additional code in Thank You! Page to capture the elements of transaction such as price, product name, quantity etc.

a. You can find more info here about installing the Ecommerce tracking. You can even track 3rd party shopping transaction. (can be done by _linkByPost function) http://www.google.com/support/googleanalytics/bin/answer.py?hl=en&answer=55528 http://www.google.com/support/analytics/bin/topic.py?hl=en&topic=11001

Adwords Integration: Integrating Adwords keyword, impression, cost, cpc, clicks metrics on GA will be extremely useful as you can segment, slice, dice cost, cpc, impression via Geography, content, landing pages, visitor behavior, loyalty etc.

a. Adwords optimization is done based on conversion, however using GA we would be able to identify various segments of users such as Visitors doing research, Visitors browsing FAQs, Visitors commenting, browsing etc. Therefore we would be able to attach value to each segment and hence can better optimize Adwords campaigns based on different actions done by users rather than just conversion.

Coming articles will contain more information on GA regular expressions, using Goals, filters and advance implementation on pageviews etc.

This Article is originally available only in http://www.praveenkodur.com/blog/

It is very essential for a financial company to know, which user to target for what product and when. The goal of data analytics and data mining department is to arrive at accurate answers to these 3 questions, (Which User, What Product, When), trust me it is a rewarding exercise for the bank, users and definitely the analytics manager.

The problem is very simple. A customer may have purchased a single product or multiple products from a bank. The company would ideally like if all its customers bought all of its products. This possibility however does not exist, therefore without any targeting model; the company would be wasting money, time and resources by randomly targeting customers for its products.

Using a little sophistication of data mining techniques, we would be able to build a targeting model or a response model on customer base. A response model is a predictive model which estimates the future behavior of a given customer even before it occurs. Even with a fair amount of accuracy it can be very useful for company in saving majority of costs in various departments/channels. There are various types of data available for analysis like demographic, behavioral, psychographic / attitudinal. The above data can be very useful in data mining methods, however the cost, usefulness and expertise to store / retrieve data has to be assessed and judged.

Giving an example: A customer has savings account in a bank, based on the information given to the bank along with account status and history, we could target her as a prospect for a personal loan product based on a logic / algorithm.

The logic / algorithm could be as simple as if a customer from metro with account balance of Rs 1,00,000 or more for over 6 months should be a prospect for home loans Rs 20,00,000 or personal loans over Rs 3,00,000. This is a simple example; however it could be a complicated neural network or logistic regression model.

Cross Sell Models: A customer of a product A, is a likely prospect for product B if his account activity positively predicts likelihood of purchase. Target model has to predict purchase of product B.

Up Sell Models: A customer can be targeted for higher segment product in the same category based on his account status and demographics. Normal saving accounts customers can be sold for Premium segments customers, if his account balance is over a period of time.

Deep Sell Models: A customer can be sold more of same product based on his need. Target model has to predict his need.

These target models are also called response models that only predict the purchase behavior of a customer for a given product. This model is ineffective as the cost of randomly targeting a customer for product is LESS THAN cost of targeting using predictive response model.

The main reason is because of below limitations of traditional response model

A) All customers behave in two ways: Purchase or DO NOT Purchase

B) Behavior of customers during absence of any marketing activity.

C) Maximum lifetime value to be derived from customer is unkown, this will result in underselling or selling lower value products when higher products could have been sold.

IF these issues are taken care of by strong statistical modeling then loss making response model can be made profitable.

The original article was found on http://www.praveenkodur.com/, Copy rights are reserved.

Disclaimer: These are my personal views and not a view of any organization or body.

The idea of this blog posts and future blog posts is to identify problems in web based business and how analytics can help solve it?

Blogging and Blogs

You have a small blog and spend considerable amount of time updating it, also have spent some money in creating and putting it up live. Measuring the success of a blog is not just pageviews, subscribers and unique visitors count.

ROI of a popular blog can be huge, if you have rich content and have active RSS subscribers. You don’t need a resume. Every popular blogger gets job offers regularly flowing into his email. Above this you have created a brand for yourself. This is a huge economical benefit considering the money and time you spend on make your blog active. If you have a great blog then you have separate brand and identity for yourself.

Small Scale Business Online

Concentrating on search engine marketing, seo, affiliate marketing to generate profitable visitors to site is fruitful. This is the cheapest form of advertising online. You have control over spends and will be able to monitor your ROI. Set up Google Analytics or any other analytics tool which will help you look at the visitor information.

Conversion University from google is very helpful in optimizing the website for higher conversions and sales (http://www.google.com/support/conversionuniversity/bin/answer.py?answer=77123)

Small scale business must focus their marketing efforts cleverly around geo-locations to get maximum return from marketing & advertising. The site must clearly offer maximum benefit & response to their end users as promised in their USP. Most sites initially work on small set of customer base and keep them satisfied at all circumstances.

These companies are ecommerce sites, shopping sites, travel agent sites that are looking to sell products to their websites’ visitors. They should target at long term steady and consistent growth not looking to achieve instant traffic hoping to dramatically increase page-views and visitor count hoping make revenue quickly and grow faster.

Large Businesses Online

There are various large online website who advertise heavily online & offline for the purpose of promotion. The spend a big amount of money with an objective to increase visitors, page views hoping to increase brand value. It is unwise to spend money on marketing, advertising without looking at the actual value it adds to their users (customers).

Increase in page views and visitors may not proportionally be related to increase in revenue and profit. There are definitely smarter ways to reduce cost of marketing & advertising without impacting the bottomline.

I read about many large advertisers in US & worldwide who have decreased spends on search marketing as it has become unprofitable after a certain limit. They have found search engine optimization, social media marketing ways more effective to gain relevant traffic to their websites for increasing their sales.

Measuring ROI through every channel and making them profitable is very essential and must be the key factor

EXAMPLE:

The traffic to my blog has constant traffic from social media sites like stumbleupon and other social network sites. Few days it has huge spikes of about 2000 hits in a day from stumbleupon alone, totally free traffic.

Blog attracts about 16% of overall traffic from social media sites of which 48% contribution is from Stumbleupon alone.

The cost of promotion on stumbleupon is consuming few hours of time in writing rich useful content and building a network of bloggers, friends & general users. Comparing this with search marketing campaigns, same amount of traffic might have costed me few thousand dollars.

Never be afraid to use new format of media, content for promotions such as Videos, Apps, Images, podcast, audio files, flash files etc. It is just a new form of content by the underlining principle of promotion remains the same.

Reading:

Measuring ROI from SEO : http://searchenginewatch.com/showPage.html?page=3625973

Measuring ROI from Social Media Marketing: http://www.pronetadvertising.com/articles/measuring-the-roi-from-social-media-marketing.html
This Article is originally found on http://www.praveenkodur.com/blog/

1. Emails Marketing campaigns with no referral tracking

2. SEO traffic has no referrals in some analytics tools

3. Traffic from Bookmarks.

4. A Viral Marketing Campaign

People who take advantage of direct traffic:

Domain name purchasers, typosquatters, cybersquatters whose intention is to purchase a domain name with typo mistake of popular brand, hence hoping to generate traffic. For more information please visit SEOmoz

Affiliate Marketers, Adsense money makers whose main intention is to make money through arbitrage.

Tracking Direct Traffic

Tracking Radio Ads and offline advertising internally: Some advertisers advertise their brand in Radio and give out the URL such as “http://radio.example.com” which is 301 redirected to URL “http://www.example.com/xyz.php?trackingcode=number”. This way the impact of advertising on the channel can be tracked. This will help in comparing the effectiveness between

1. Two different Ads..

2. Impact on other channel due to advertising on this channel and its co-relation

3. Same Ad performing differently in different cities, regions, geographies.

4. You could further extend to record Page Views, Time on Site and other details..

Google has launched tracking of Adwords audio campaigns in Google Analytics..

Below is an Interesting Example of my blog: The search engine traffic, referral traffic to my blog can be easily analyzed and explained as they are fairly straightforward. SEO, Referral traffic analysis requires no expert, even a layman can understand if they look at Google Analytics Report. However, the interesting part is the Direct Traffic Analysis, which initially I failed to understand until a few months back, hence I have decided to share this analysis in this Direct Traffic post.

Traffic Details

Traffic Share – Medium Wise

Direct Traffic User Details

What can we analyze from the given data?

What Google Analytics says?

1. 13.97% of users are direct, how are they finding my blog even though there is no offline Ads, no TV Ads, no Radio Ads whatsoever?

2. 49.37% of Direct Visitors are new visitors. How could this be explained?

3. Blog has 80.38% bounce rate (for direct visitors) which is high Can we figure out where the problem lies? What is wrong with the site?

4. Average Time by Direct Visitor is 41 seconds. This is a time taken for glancing a webpage, not even reading it.

This means half my direct visitors are new, they glance the page in 41 seconds and most of them leave without doing anything. Not sure how they are finding my site. They mostly visit 1 page of my site and bounce off the site like it was yuck.

Google Analytics does not give any details apart from the above.

Analysis from the above data

The direct users are landing on inner pages of the site. Its very unlikely they are typing the entire URL in the address bar…These Direct Users must be from RSS feeds, bookmarks.

Another data to look at is number of comments.. I get about 12-15 comments in a day most of which are junk and some genuine ones.

1. Users could be clicking on blog posts on their RSS feeds and land on specific page.. They then read and/or post a comment and leave the page.

    

   This is the reason for bounce rate being so high. The users read the blog post and leave; hence bounce rate is not relevant figure to look at.

 

2. Users visit one page and leave, therefore the Average time spent calculated is wrong. Google can only track time correctly if users visit more than one page.The reason being that when a new page is requested from the server then the log files records the time at which the new page was requested from server by the same user.The difference in time at which the page 1 was requested and page 2 was requested is calculated as time spent on the site. So, consider a example when a single page was requested then time spent by user on that page is cannot be determined. Hence average time here is the time spent on site by the users who browsed more than 1 page divided by the total number of users who visited the page.

 

3. Users are finding the blog through blog search engines, blog directories and other blog sites.
   1. They subscribe the RSS feed after which they click on blog posts in RSS Feed.
   2. Users may be finding the site through Book-marking sites, Social media sites add it to their own bookmarks, where users directly find the link to inner page of the site.

Direct Traffic is the most targeted traffic, as these visitors really read the content on your website.
Most returning visitors return through Direct Traffic, especially when you are not advertising offline. They are ideally the best source for returning visitors, hence business can sell their content easily.

This Article is Originally found at praveenkodur.com

Copyright @ 2007 Praveenkodur.com

In Search Engine optimization the cost incurred are mainly is on effort, time, agency cost/employee cost. While as in Search Engine Marketing, the costs are Advertising cost(which is CPC, CPA, CPM etc) and the cost of time/effort.

It is necessary to track the value derived from Visitor Engagement on the site and revenue generated,

Visitor Engagement Tracking

Visitor engagement depends on objective and size of the business,

1) Defining Visitor Engagement depends completely on the content present on your web site.

a. On a Shopping site: Engagement has to be product sale, product search etc..

b. On a Blog: It is the number of comments posted, subscribing RSS feeds, Average time spent on the site, No of page views per visit can be engagement metric.

c. On a Corporate Business Site: People might just visit to pick up telephone number, address of the business. Therefore none of the metrics work.

d. On a News Site: It is number of subscription RSS,Email. It is again time spent on article, number of comments posted, no of page views per visit.

e. On a Forum site: Registrations are a value.

f. Software Downloads Site: Number of downloads are a value.

2) Getting Users to Subscribe your RSS feed is a value. These users will read your content more than repeat visitors. It shows the measure of content popularity.

3) Users favourite the page, site in social bookmarking sites, social network & media sites like Digg.com, Reddit.com, Del.icio.us, stumbleupon.com is also a value provided by SEM traffic.

4) If Links to your blog post increases from SEM traffic, due to people positing your link elsewhere in answers etc, then it is a big value..

5) Users might land on specific detail page pick up the phone and dial the number given on page. Measuring telephone call rate is necessary.

6) For smaller business getting targeted traffic to their website is a value, since it adds to brand building etc.. if not sales..

7) For larger websites, brand is already in place, hence traffic which has a direct effect on revenue is more of a value than mere traffic from.

If the mode of revenue generation is advertising then attracting just traffic, might be worth

For small shopping sites setting up ecommerce tracking is very useful and necessary

This can be done by using the option present in Analytics Settings à Profile Settings àEdit. Give details of Currency, decimal places etc.

Tracking Ecommerce Transaction through Google Analytics

Once you opted Ecommerce tracking, you must edit the receipt page, which is the page after transaction, install a script into this page passing the order value into the Analytics system. Google has provided a comprehensive material on setting up ecommerce transaction.

For other business they need to monitor, track the objective of SEM campaigns. If not the engagement of the visitor on the site.

Optimizing SEO, SEM Campaigns

1) Generally Specific Keywords have higher conversion rate but are lower in volume

2) It is important to add as many new specific long tail keywords as possible…it need effort in research on new keywords on regular intervals.

3) The Head of the keyword list is pretty much fixed with little variations but more effort has to be made in making the tail longer…..that is where maximum effort and time as it can change the ROI of the campaigns.

4) Competitive keywords are always costly and extra effort can change CPC minimally…

a. However the efforts has to be done on Landing page creation..

b. Small changes in conversion rate by new landing page optimizations can dramatically increase ROI

5) Constant Generation of long tail keywords and new keywords are always the key…

6) Using different landing pages for each set of keywords is very good

a. Domain name keywords can be landed on home page

b. Category Specific Headings can be landed on respective section on the site

c. Product keywords or Specific keywords must be landed on inner most pages of the site or respective product pages.

7) Make sure your website ranks for all brand terms including the misspellings of your domain name etc..

a. This can be done by creating a page with list of all misspelled keywords

Using Misspellings can be a great way of generating low cost traffic…but remember there can be 2 types of users typing misspellings

a. Users who accidently typed a misspelling, will most likely click on “Did you mean – Correct Spelling”

b. Users who are uneducated or illiterate,

So you need to decide on keeping such keywords based on the quality of traffic you generate

9) For Large Websites tracking of every keyword to last metric of calculating business ROI is essential…For example:

a. Banking website could track the number of savings accounts, number of loans applied per every keyword along other details such as location, amount of loan, income of user and other other quality measurements which will help determine the quality of keyword.

b. This will help them to make a decision of increase bid rates, adding more same kind of keywords etc..

10) Track phone Calls, If you are running a Click to Call Campaign then provide the keyword which generated the call to call center executive. After the call process collect the feedback of the user and measure the business quality of the keyword, which is again fed back into the Adwords campaigns.

Copyright  of  this article is reserved by praveenkodur.com

Analysis of Analytics data begins with a given underlining problem or a query.

Avinash Kaushik’s blog, which contains wealth of Web analytics information, is a must read for every one in this field.

1) Identify the objective of analysis. Define the problem.

A) To Improve Campaign Performance

i) How to increase conversion rates

ii) Which pages have higher pageviews, lower bounce rates and why?

iii) Which geolocation, keywords bring most loyal visitors?

iv) Can you retarget your new users?

v) Which referral sites gives low cost per acquisition? why?

B) Where to spend more money?

C) Where to reduce spends?

D) Which content/product is highly popular? Why?

E) Do you need to add more content, if yes, how often? which category of content?

F) Why is my market share going down?

2) Segmentation of Users: Divide your users into different segments based on your business objectives

A) Identifying visitors based on amount of time they spend on your site

B) Identify users based on length of time on site.

C) Identifying users based on frequency of visits to your site

D) Identifying users based on depth of visits/ number of pages viewed

E) Identifying users by repeat purchases on your site

F) Identifying users by gender

F) Identifying users by geo-location

G) Identifying users by value of purchase on your site.

H) Any additional segment valuable to your website.

Determine the segments most critical to your business, you may also give weights to each segment, for example returning visitors who visit once every 2 days may be the most critical segment for your website. You should be able to find data on above segments and cross-segments.

In a travel site may be returning visitors every month making a purchase may be very valuable. In a shopping site a new or returning visitors who visit more than one page on the site may be more valuable than returning visitors browsing just one page. In an Adsense site the important metric to be looked into is the depth of each visit irrespective of visitor being new or returning.

Based on your business, you need to segment the group of visitors to be monitored for better targeting of your marketing communication.

3) Segmentation of your Market. Based on your competition, quality of users on the site, determine various segments useful for business.

A) Segmentation based on Product Demand.

B) Segmentation on seasonal factors

C) Segmentation based on competition on certain product, geolocation, service.

Web Analytics is used for below main purposes.

1. To keep a watch on regular Metrics of the site on a day-to-day basis.
2. Provide required information to Marketing Team, and other teams.
   1. To increase performance of Online Marketing Campaigns
   2. To identify, segment users visiting your site.
   3. Traffic Sources and amount of marketing effort needed on each medium
   4. Identifying medium for each segment.
3. To find evidence for occurrence of particular event/action. To help in creating better content in the website.
   1. Identify geo location of each segment of users visiting your site.
   2. Identifying content viewed by each segment of users.
   3. By identifying Top exit pages, Top bounce rate on pages.
   4. Average Time spent by users in each page.

Segment Visitors based on the value they provide to your business, then create Goals and work to attaining those goals along with strong measurement techniques.
Identify visitors who are valuable and loyal, customize services for them…

Find out which content on your site these each segment of visitors actually view and how long.

1) Understand the needs of your users’ who visit your website.
A) Understand the needs of each segment of users..
B) Determine the content each of your segment browses
C) Even remote need of small percentage of users must not be ignored. It might help you in creating new products which could get more such visitors back to your site.

2) Provide required information to Marketing Team, and other teams before finalizing strategies.
This would help them assess the amount of effort required on external advertising and internal optimization. Read more about Marketing ROI on Avinash’s Blog.

If you would like to grow your visitors by 100%, then push marketing can do it by 20% & pull marketing can get you remaining 80%.

Reading some of the Best Web Analytics Blogs is must read for anyone in this field, some of them are:

1) Web Analytics Demystified
2) Conversion Rater
3) Occam’s Razor
3) Web Metrics Guru
4) Analytics Guide

End of Article …………….

Copyright of this article reserved by praveenkodur.com.

Most online businesses which operate online perform competitive intelligence analysis tracking competitor products, websites, traffic through various tools available both free & paid.

There are very few companies which analyze the link structure of competitor websites. In an offline scenario, a company is always aware of its competitor’s reach & various business links.

Competitive Link Analysis

This is actually a process of identifying various websites which link to your competitor’s website. Analyzing these websites based

A) Theme of Content containing the link

B) Freshness of links,

C) Frequency of new link addition,

D) Number of links from each domain

E) Network Structure of Links

Advantage of Link Analysis

A) Insight into Competitors’ Online Strategies

B) Complete picture of some sources of traffic of competitor’s sites, referral traffic.

C) Competitors Business Links, Business Partners, Online Alliances.

D) Get insight into competitors’ online promotional activities.

E) Find out why your competitor is ranking in Organic Search?

F) Identify new methods of Content Promotion, Link Building.

G) Find new forums, answers programs where your target audience is active.

H) Find sites which are mostly talking about your industry, business.

I) Include these links in Custom Search Engines, so that you perform niche search or filtered sample size to perform your search.

Tools Required for Link Analysis

Build software which can find backlinks of any website,

a. Retrieve content from webpages that contains the link. Like Title Tags, Meta, Headings etc.

b. Compare different Urls.

c. Group Urls based in Location, IP addresses, theme of content.

d. Get Page Rank of the Urls,

e. Categorize Urls based on Domain names, Org sites, education sites. Etc.

f. Categorize Urls Based on number of pages present on that domain, i.e group urls based on small sites, big sites.

g. Ability to split Urls to extract just domain names.

h. Filter domain names, unwanted Urls.

i. Given a Keyword or a Phrase, your software should be able to find maximum occurrences of this phrase on these set of links, as anchor, as content.

Read my further posts on link analysis …..

Copyright of this article is reserved by praveenkodur.com

In present day online industry there are numerous players such as companies, agencies, individuals, consultants & others who are coming up with innovative ideas technical as well as commercial in the online medium to make an impact to the end user’s life.

However, the one area where the online industry is lacking & the community needs to put its act together is creating a strong, robust, reliable, widely accepted analytic system which gives the both the end user as well as the community a benchmark to measure & evaluate the effectiveness of a website in the online market.

The presently available tools such as Alexa and comScore are both unreliable as sometimes it is found that they contradict each other while rating a website

There are numerous instances where Alexa and comScore ratings have been doubted by various people:

1) Matt Cutts on Alexa
2) Peter Norvig on Alexa
3) Business Blogs on Alexa
4) WebmasterWorld on Alexa
5) Alexa can be injurious to your wealth
6) Can you trust Alexa?

The point is the main motive behind installing an alexa toolbar is to drive up the ratings. The comscore figures are also seen are far away from the real numbers.

With use of new technologies such as AJAX, calculation of page views becomes even more complicated for the analytical tools.

My belief is there is enough room for any new company to enter and provide real value to end user, companies & other players in the online industry.

Copyright of this article is reserved by praveenkodur.com