In this post, we will cover the most important Excel features and tricks to improve the web analytics productivity.

Tip#1 Correlation Analysis

Web data analysis comes with its own set of data inconsistencies and irregularities that cannot be explained by simple math. Sometimes you may notice that your website bounce rate changes with the day of the week, and sometimes the conversion rate will change with traffic. This happens when one data set (visits) shares positive or negative relationship with another data set (conversion).

Pearson’s correlation is the best way to measure the positive and the negative correlation of data to rule out the data inconsistencies and establish a baseline.

MS Excel 2007 is equipped with Correlation function and can be used to perform a quick analysis.

Let’s assume that we want to see the relationship between the daily visits and the website conversion.

a. Enter the visit and the conversion data on the Excel spreadsheet.

b. Place the cursor on any empty cell in the spreadsheet. This cell will be used to display the Pearson’s correlation coefficient. Press F2 to enter the formula for correlation and type “=Correl” and hit Tab key.

c. Once you hit the Tab key, the cursor will be placed in the bracket, and you will be allowed to select the array data. Select your first data column (avg. daily visits) for the array1 and second data column (avg. daily conversion) for the array2. Close the bracket and then hit the Enter key.

d. The value displayed in the cell (0.963240336) will be the correlation between the avg. daily visits and avg. daily conversion. In this case, the daily visits show a high positive correlation with conversion (greater than zero is positive and less than zero is negative. Zero is no correlation).

Tip#2 Control Limits

We have discussed control limits on this blog before, but I could not resist talking about it once again because it is extremely important. Establishing control limits for your data set allows you to measure the trends in your web metrics effectively.

Your website traffic/conversion/bounce rate can fluctuate due to multiple uncontrollable environmental factors. You could see a spike in traffic due to a viral campaign or see a drop in conversion because of shopping cart errors. In any case, your job as a web analyst is to identify a true trend and eliminate noise from data.

Calculating the upper and lower control limit (UCL & LCL) using Excel will allow you to establish a trend benchmark for your key metrics. Using this data, you can focus on when to take action about the data.

Here are the steps to calculate the UCL and LCL for web traffic data.

a. Enter the ninety day daily visits day on the Excel spreadsheet and calculate the Standard Deviation in an empty cell. (hint: For accurate UCL and LCL calculations, it is advisable to have atleast 90 data points).

Excel Standard Deviation formula = STDEV(number1,number2,..,numberN)

b. Calculate the Mean for the data.

Mean = Average(number1,number2,…,numberN)

c. Finally, calculate the upper and the lower control limits. The control limits can be later applied to the weekly/monthly trend graph.

Upper Control Limit (UCL) = Mean + Standard deviation

Lower Control Limit (LCL) = Mean – Standard deviation

Tip#3 Data Comparison using Vlookup

VLookup is one of the most powerful Excel functions that you can use to match / compare data between two Excel sheets. Vlookup can be used to match/compare the data between either the same or across different Excel spread sheets. The possibilities of using Vlookup function are endless. You can pull data from different sources and populate the fields based on a matching column. For example – data from your CRM solution can be connected to the data from web analytics provided you have one common column (visitor id) between the two spreadsheets.

Here is a short Youtube video that shows how to import value from one spreadsheet to another using Vlookup.

Click here to view the embedded video.

Source: Youtube user smbst58

Tip# 4 Pivot Tables

Summarizing data from a large Excel spreadsheet is extremely difficult when dealing with multiple variables and filters. The excel Pivot Table feature allows you to summarize the data really quickly. The filter functionality of the Pivot table can be used to filter the data for multiple values, i.e. lead type, date, campaign source, campaign medium.

There are two ways to create a Pivot Table in MS Excel. You can either add the Pivot Table on the same spreadsheet or create the table on a new spreadsheet. I prefer creating the table on a new sheet because it is clean and easier to sue. To create the Pivot Table on a new sheet, open the Excel data file, place the cursor on a filled data cell (placing the cursor on an empty data cell will add Pivot Table to the same sheet), click “Insert” tab and then click “PivotTable” button in MS Excel 2007.

The Pivot Table action box will popup, and the “Table/Range” field will be automatically prepopulated with the table range.

Click “OK” and you will be taken to a new sheet with the Pivot Table.

Pivot Table consists of three sub sections.

a. PivotTable display area – Empty area on the left where the Pivot Table will be displayed.

b. Pivot Table field list – This is the list of the columns from the data spreadsheet.

c. Table customization areas – Table customization consists of four areas -

1. Report Filter: Report filter allows you to filter the table using any column. In this example, you can filter the table by Date, Day, Campaign source and Lead type. Simply, drag and drop the column from the field list to the filter area.

2. Row Labels: This area allows you to add the rows for the Pivot Table.

3. Column Labels: This area allows you to add the columns for the Pivot Table.

4. Values: This is where you can add the amount of the total sales and any other calculation you want to look at.

Once you drag and drop the columns in the respective areas, here is how the final table will look like. You can then easily filter the table by date, day or lead type.

Tip#5 Unique Records Advanced Filter

This is the easiest of all the Excel tricks and one of the most useful. As a web analyst, you will constantly come across multiple visit data for the same visitor in any given period of time. Unique record filter allows you to filter out the duplicate records from the data.

Here are the steps to use the unique record filter to remove the duplicate visitor ids from the sample data -

1. Select the column with the duplicate records (Visitor id)

2. Click the “Data” tab in MS Excel 2007

3. Click “Advanced” in “Sort & Filter” section

4. Click “Unique records only” check box and hit “Enter”.

The final data will only show one instance of the Visitor id.

Hope you enjoyed the post. Please share your thoughts, insights and comments below. Your feedbacks are helping me become a better blogger. Thanks!

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Top 5 Power User Excel Tips & Tricks for Web Analytics Productivity is a post from: Key Web Metrics & Web Analytics Blog

In this post, we will discuss 100% free on and off site analytics tool that can provide you detailed insights about your customers and prospects.

Google Insights for Search – The only tool on the web that allows you to predict the future traffic volume of keyword and location based insight. You can use insights to identify the keywords that are trending down and will virtually become extinct and keywords are new and growing faster.

A super cool feature “secret” feature of insights is it can sometimes be used to identify investment opportunities. You can quickly compare real estate markets in Florida and Texas and identify better performing markets.

Quantcast – A pretty cool tool that provides quick demographics and traffic estimates on most websites. The key usage for the site is to find the right audience for marketing. Quantcast collects the log data from the websites that participate in their measurement program. The data collection is based on third party cookies.

Compete – Compete is a top competitive analysis tool that allows you to spy on your competitor traffic and search analytics. The traffic estimates are far more accurate in comparison to Quantcast. Their data collection method is based on daily browsing activity of their panel of 2 million panelists.

Compete’s search analytics data is fairly usable, and you can instantly get the share of the search visit for any keyword.

Twitter Analyzer – Measuring twitter conversations has become extremely important for every organization. Twitter analytics provides great details on the offsite customer / visitor behavior. Twitter Analyzer is a must use extremely powerful Twitter analytics tool. It not only measures the growth rate of your follower and friends but also provides detailed measurement of chats, popularity, reach, links, hashtags, follower geo location, groups and more.

Bit.ly – Bitly was originally designed as a url shortener but it is now commonly used for real time click tracking and campaign measurement. Bitly is the hottest social media url shortner and campaign tracking tool. One of the coolest features of bit.ly is it allows the tracking of competitor campaigns.

To perform a competitive analysis simply find your competitor’s bit.ly url from Twitter search or Facebook pages and type bitlyurl+ in your browser window. Voila! You now have real time insights into your competitor’s campaigns.

Google Ad planner – Google Ad planner is similar to Quantcast. but it offers additional data like ‘audience interest’, ‘keywords searched for’ and sub domain level tracking.

Click here to view the embedded video.

Admob Mobile Analytics – Google recently acquired Abmob, a company that is specialized in mobile ads and analytics. Admob analytics allows the user to install code on their mobile website and get detailed analytics reports. Users can instant access all web analytics reports like visitor location, mobile device types and time spent on the mobile site. The analytics package is completely free because the company makes money by selling ad space on mobile sites.

Open Site Explorer – Open site explorer is the best link analytics and seo metrics tool on the planet. The free version allows you to download data for up to 1000 links. You can perform advanced seo competitive analysis and compare data between two sites. Data can be exported in CSV format for further segmentation and pivoting in excel.

Pear Analytics – Pear Analytics offers a complete SEO scan of your website and provide insights on how you can optimize your site for search ranking. The analytics engine is powered by some of the most popular search ranking factors. The software is capable of identifying 404 issues, title and meta issues, css and missing sitemap issues.

Google Analytics – The #1 free web analytics tool is becoming the biggest competitor to enterprise analytics. With new features like mobile tracking, advanced analysis tools, and analytics intelligence more businesses are thinking twice before investing in paid solutions.

Google analytics recently added asynchronous tracking that loads the analytics code in the backend improving the site load time.

Hope you enjoyed the post. Please share your thoughts, feedbacks and comments on what you think are some of the top analytics tools.

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It is interesting that web analytics is all about data but very fewer infographics have been created on web analytics concepts. Here are some of the most popular web analytics and seo infographics.

#1. Unica Anlaytics – The top in the category of the web analytics infographics, this Unica infograph explains the web analytics process and how use it for campaign optimization.

Source: http://lp.unica.com/infographic/

#2. UXD Stress Fields – A super cool way to show how tech, web development and business decision makers can work together. Web analytics cannot operate in a silo, and it is absolutely important to connect your tech and web development team with the business analyst.

Source: http://informationarchitects.jp/the-spectrum-of-user-experience-1/

#3. SEO FAQs guide – This highly popular seo infographic can be used to learn the basics of search engine optimization in few minutes. Kudos to the designer who has incorporated the small on and off page optimization nuances with such clarity.

Source: http://www.datadial.net/blog/index.php/2010/04/13/seo-in-pictures-our-seo-infographic/

#4. Actionable Analytics - Here is a simple display of web analytics measurement framework. The designer has captured all the facets of buying cycle and connected it with the web measurement strategy.

Source: http://actionable-analytics.com/2009/07/how-to-build-a-digital-measurement-framework/

#5. Google’s Analytics - A dark humorous way of showing how much data Google captures through different analytics measurement techniques. Google Analytics is the most widely used analytics software and is one of the key tools of Google’s data capture portfolio.

Source: http://smashingcrunch.com/images/fear-google-true-power-of-analytics-user-data-infographic

Original Source: Onlineschools.org

Please share your thoughts, insights and comments below.

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Bing being a key competitor to Google is not different atleast algorithmically as far as the ranking factor goes. There are striking similarities on the criteria used for ranking between Google and Bing.

TLD Extensions – Top level domains with .gov and .org extensions have the highest possibility of ranking higher in both Google and Bing. The most interesting part is .org is rated higher to rank than .com and it is quiet surprising.

Tip – Grab .org extension for your site and build a community on that domain or redirect to your .com domain.

Keyword in Domain – A website with target keywords in the domain name has the highest correlation with rankings higher on search.

Here is a quick example of my blog ranking higher in search because of the keyword in the domain.

Tip – Buy domains with your target keywords and build micro sites with unique content on those domains.

Keyword in subdomain – Sometimes it is harder to get a keyword rich domain and another alternative is to go for a keyword filled sub domain. Data shows that Google gives some important and Bing does not factors this in their SERPs ranking.

Tip – Stay away from creating too many subdomains to gain higher ranking in search. Create sub domains only if you feel it is required from user point of view.

On page keyword usage – Both Bing and Google ranking analysis data show a small correlation between on page keyword usage and ranking. Alt image is useful to search ranking in some cases, and so is putting keywords in the url.

In the example below, the website webhostingsearch.com has the word “dedicated server hosting” 10 times on the page in comparison to webhostinggeeks.com (3 times) and it still ranks lower. The reason is webhostinggeeks.com has over 2000 unique links to the page and webhostingsearch.com has only 246 unique links to the page.

External links - Having a small number of links from multiple websites is 10x better than having a large number of links from the same website. Websites rank higher if they have diversity in link sources and there is a high correlation for this in both Google and Bing.

Tip – Diversify your link building strategies to multiple avenues. Build social links along with content links and viral links.

Length of url – Data shows that shorter urls rank higher in search than longer urls.

Tip – I have seen that blog links with longer url tend to rank higher in search, and clearly Google and Bing have different set of rules for different types of sites. This could be because blog links are generally longer. It is ok to have longer blog post links but keep your website links short because it helps users remember the url easily.

Anchor text – The number of unique links with anchor text influence the ranking of a website. Having anchor text diversity is as important as the link diversity.

Please share your thoughts, insights and comments below.

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#1 Web analytics is accurate – Web analytics is all about direction and insights. It is funny that we are still worried about the accuracy of analytics reports. We can spend days arguing with the marketing and sales managers on why the reports are accurate even though we all know that web analytics can never be accurate. Instead of focusing on this let’s start focusing on insights.

All web analytics reports are directional and getting insights is the key to web analytics success. Focus on direction, build trends, and apply statistical significance to the trends to get meaningful takeaways.

#2 Site Visitors delete cookies – It is extremely important to understand the difference between the first and third party. First party cookies are cookies from the host domain i.e. your domain. Top analytics tools (Google Analytics, Omniture, Coremetrics, WebTrends) all install first party cookies in order to measure the repeat visitors. The deletion / block rate for first party cookies is atleast 50% lower than the third party cookies.

Having said that, studies have shown that web analytics software cookie (first or third party) will be deleted no matter what. This is the truth about the tag based web analytics industry, and we have to accept it. This does not mean that we should stop trusting the reports and ignore them. The analytics reports are power packed and actionable because it can provide you insights if you follow the direction. As mentioned above the directional aspect of web analytics is unmatched.

So, stop worrying about cookie deletion rate and focus on the trend.

#3 Users disable Java scripts – A major myth that goes around the market is about the blocking of the java script and thus prevent the execution of analytics tags. Java is an integral part of web and disabling java on the web browser can limit the accessibility to a large number of services on the internet.

Still not convinced? Here is a good study conducted by few developers showing why only 3-5% of the users disable java scripts.

#4 Google Analytics data for search ranking - Google analytics data is not used by Google to evaluate search rankings. Here is a quick video from Matt Cutt’s (head of Googles webspam team). In this video, Matt debunks the myth about Google using GA data for SEO or search ranking.

Click here to view the embedded video.

#5 Data addiction = actionable insights – Are you lost in data collection, integrations, and data obsession? If you are a pro analyst then you know that data dump, web integrations, data warehouse are critical issues. Please don’t get carried away by data addiction and focus on analytics priorities. Ask yourself “what is the most important and high priority task / project for you in next 5 days/ 5 months.?” Is it business growth insights or painstaking integrations? Is it few key recommendations to your management or never ending analysis?

I agree, analytics integrations can sometimes make your job lot easier but in most cases integrating your CRM and analytics tool is painful. Use excel reports and MS Access for connecting the dots. Leave the integrations for your web developer and business intelligence teams.

#6 Analytics code hampers site performance – I cannot deny that java scripts can increase the web page load time. However, there several options available to minimize the code impact on the site performance.

1. Open a Google webmaster tools account. Google has recently added a cool web performance measurement tool in the webmaster tools. It is the only free tool that measures your site performance relative to other sites on the internet and displays your historical performance in a trend line.

2. Install Yslow and Google page speed Firefox plugins. These plugins can instantly provide you detailed reports on how you can improve your site performance.

3. If you are using Google analytics then switch to asynchronous tracking. Asynchronous tag allows the browser to continue loading the web page while the tag is loaded in the background. This decreases the page load time.

4. For other analytics solutions, limit the use of onclick function to reduce server call connections. Tag only those pages that can provide insightful and actionable data.

#7 Unique visitors are absolutely unique – Your unique visitor reports are not really unique. It varies depending on the time frame you are looking at. You will have different data for hourly/daily/weekly/monthly unique visitor reports because of the way unique visitor is calculated. Using visits report with new and returning visitor segment will provide you more insights that you can ever imagine from unique visitor reports.

#8 Time on page is accurate – The time on page can only be calculated if the web site visitor navigates to another page on the same website. What this means is you will never be able to figure out how much time a web visitor spent on the last page of the website. Stop worrying about the time on page metric and focus on conversion and task completion. A task completion could be clickling the link to the next page, subscribing to RSS feeds, clicking the buy now button or anything that page is motivating the users to do.

#9 Free Analytics = Enterprise Analytics – Investing in paid analytics solution is not a bad decision atall. You might have been motivated by someone on why you should never pay for analytics. The truth is far from accurate. Google Analytics is one of the best free tools out there, but it does not provide enterprise level capabilities that are required for advanced business analytics.

Here are the top 5 reasons why paid enterprise solutions win over free solutions-

1. Support – Paid solutions comes with support hours so you don’t have to spend time fixing analytics issues.

2. Custom Metrics – Paid solutions allow you to create custom metrics on the fly. You can create your own task completion and conversion metrics.

3. Multi-dimensional Timeline – Advanced solutions like Omniture Discover and Coremetircs Explore allows you to compare data from more than two time segments. Google Analytics can only provide two dimensional timeline comparison.

4. Analytics integrations – Web integrations become easier with the enterprise analytics provider because of their partnerships with email, crm, live chat and other service providers. Usually they provide integration hours or detailed documentation.

5. Campaign Attribution – Enterprise analytics providers store all the data on the data warehouses. The data can be accessible anytime and both first and last click is captured in most cases (depending on your settings). You can use this data to design a campaign attribution dashboard and allocate funds efficiently.

#10 Dedicated web analyst is not required – Paying $100K to your enterprise web analytics provider and expecting them to provide you all the answer is not going to work. Web analysis is the core of online marketing and without proper analysis and recommendations your business could come to a dead end.

Even though I love enterprise analytics I cannot stress enough that a dedicated analytics team is a must. Intelligent recommendations may be the future of web analytics but without an expert eye to decipher data and implement recommendations you won’t get results.

Hiring a web analytics expert is more important than investing in paid analytics tools and services. Period!

Please share your thoughts, insights and comments below.

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1. Super Local Marketing

Currently, being called as mobile + social is a uqniue way of advertising locally. This new advertising channel will allow the local advertiser to measure the effectiveness of their campaign all the way to physical action i.e visit to a local restaurant / coffee shop to make a purchase.

Google is trying hard to make local advertising more effective. Using data from public reviews is useful, but it still does not provide physical conversion measurement.

Facebook is getting ready to announce the intelligent social ads that could potentially be a breakthrough in local advertising. The concept opens up a whole new way of looking at conversion data and yes it definitely is not going to be your traditional GA goal conversions. It definitely opens up new web analytics measurement possibilities.

2. New Ranking Algorithm

This one seriously aims at Google’s age old core competency – The ranking algorithm. Google has always used links as the core of its ranking algorithm and its page rank metric was developed using link data. However, it is interesting to note that not all links were created manually.

Facebook has decided to go a step further and exploit web user data for calculating website rankings. It is currently testing a new feature that will take the Facebook share button functionality to next level.

The new button will include a feature called “like”. At the frontend it might look like a cool new way to express your feelings about a website but at the backend it will send data to Facebook servers using Facebook connect. This data will go through a series of mathematical calculations and the system will decide the new web rank / site authority.

3. Facebook Analytics

Waging a war against Google should not be limited to search. Google has an endless list of useful products and services and Facebook is ready to battle on all front.

Facebook Insight might be another major announcement at the F8 summit. The concept of data capture is similar to the web analytics solutions where the data is shared through an image beacon file. This allows developers and users to measure events triggered during an API call.

Do you think that Google should be worried about these new features?

Please share your thoughts, insights and comments below.

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Unique Visitors

The first one is one of the most talked about metric: “Unique Visitors”. Unique visitor has been called by various names in different analytics package. Some call it absolute unique visitor and others like to call it hourly/daily/yearly/decade/centuries unique visitors (see below you guessed it right . Quite honestly, it does not matter what you call it by definition a unique visitor is a “statistic describing a unit of traffic to a Web site, counting each visitor only once in the time frame of the report.” (courtesy: wikipedia.com)

Key benefits

This metric helps building rapport with your field sales team (because it is so common no kidding).

The second benefit is it allows building cool reports like hourly/daily/weekly visitors that you might rarely use.

Third benefit is your websites unique visitor number could change if you change the date range. You will have a different unique visitor value for day/week/month/yearly unique visitor. What is the point of using a metric that creates confusion instead of providing insights?

My advice is to use visits metric report with new and returning visitor segment instead. This will provide you more information than any form of unique visitor report can.

Overall bounce rate report

Bounce rate can be the coolest metric only when you apply it to the right report. Overall site bounce rate report is total waste of time because it will not give you any directional data. It might be a good metric to tweet about if you have nothing else to say.

You could be getting a low bounce on your worst performing pages / campaigns and high bounce on the high converting pages.

Bounce rate can be super charged if you apply it to the right reports. Most Google Analytics reports have bounce rate as one of the default metric.

Apply bounce rate to get most actionable data from the following reports-

1. Keywords report – Keywords report provide insights on what keywords are driving targeted traffic to your website. Our goal is to identify the keywords with higher conversion and high bounce rate (40% or more). The default view of the keywords report in Google Analytics will not provide both the bounce rate and the goal conversion rate metric in the same screen. The trick is to export the excel version of the keywords report. This report will provide the conversion and the bounce rate data side by side. Find out the landing pages for these keywords and test multiple landing pages.

2. Top Landing page – The top landing pages report can be segmented into paid vs non paid search traffic. High bounce paid search landing pages are low hanging fruits. Find out all the high bounce pages for paid search campaign and divert the traffic to more relevant pages after successful split testing. Similarly, identify the organic search landing pages with high bounce rate and add relevant content.

Time on Page

Time on page metric could have been the best metric to measure content effectiveness only if the time on page calculation was done correctly. The time on page can only be calculated if the web site visitor navigates to another page on the same website. What this means is you will never be able to figure out how much time a web visitor spent on the last page of the website.

So, what should be the most productive and insightful way to measure time on site related data? Quite honestly, just stop being obsessive about the time on page metric and focus on the conversions instead.

Here are some questions that you need to ask yourself -

1. Does this page have a high bounce / exit rate?

Yes

Identify the paid search keywords with high bounce and divert this traffic more relevant pages.

No

Great

2. Is the page a key driver to the path to conversion?

Yes

Great. Drive more traffic to this page.

No

Identify the paid search traffic landing on this page and divert it to better performing pages. Optimize the page by addding relevant content to this page. Drive relevant paid search traffic to this page.

3. Is the page located at the right place in the site architecture?

Yes

Great.

No

Move it to a better location on the website and 301 the old url to the new page.

Do you agree that these three reports / metrics are the worst metric? Please share your thoughts, insights and comments below.

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In this post, we will discuss the end to end integration of Google Analytics (GA) with Instant Service (IS) live chat solution. Integrating a chat tool with an analytics solutions can provide you all the chat conversion data in the analytics reports.

Instant service (IS) is one of the fastest growing live chat solution and their default setup does not capture on page data. You will not be able to identify the pages, campaigns or referral that lead to chat. Instant service reports will only provide you with the post chat start data. Interestingly, the chat solution is designed for quick and easy analytics integration.

Step#1. Requirements

GA provides three options for custom variables i.e. page-level, session-level and visitor level. We will be using three GA session-level custom variables and trackpageview function for the integration. Session-level custom variable will allow us to track chat metrics per visitor session. There are no special requirements as such on the IS software except you will need admin level access to your account.

Step#2. Metrics / Events Setup

We will be tracking the following events & metrics inside of GA through this integration.

• Invitation offered – Number of times the chat popup was offered to your site visitor.
• Invitation accepted (proactive chat) – Number of time the chat was accepted by the visitor.
• Invitation declined – Number of time the chat was declined by the visitor.
• On page chat clicks (requested chat) – Number of time the chat was started by clicking a chat button on the website
• Referring url (IS_referrer) – Referring url of the chat visitor
• Page name (IS_pagename) – URL of the page where chat started.

Step#3. Code and scripts Installation

To begin with, you do not have to be a programmer to write the codes for this integration. Below is the list of all the codes you will need to capture the data.

a. URL parsing scripts – These are php scripts that allow you to capture the referring url and page name for any page on your website. The captured data is stored in variables and later copied into GA custom variables when chat events are triggered. These scripts should be added anywhere between the <body></body> area on each webpage or inside the include file.

b. Reactive Chat script (capture click based chat data) -The script below when added to the website will allow you to capture reactive (click based) chat data in GA. When a web visitor clicks the chat button the clicks will be registered as a page view in GA.

Notice how we are passing the page name (IS_pagename) and referring url (IS_referrer) to GA custom variable. This will allow us to link the web data to the chat metrics.

c. Proactive chat script (capture popup based chat data) – The proactive chat codes should be added in the custom java script section of IS admin console.

Step#4. Reading Anlaytics Reports

Allow 24 hours for Google Analytics to populate the reports. You will be able to see the data in the following reports.

1. Top content Report

Apply filter page containing = chat to see how many times the invitations were offered, accepted and declined. Using page = page name custom segment you will be able to see the chat performance for each page on your website.

2. Custom Variables

Custom reports will provide you all the referring url data associated with each chat event. Using referring url and page name you can optimize the chat popup rules to maximize performance and improve the chat conversions.

Please share your thoughts, insights and comments because it really helps me write more effectively.

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Here is a quick snap shot of all the beta release to date. Feel free to share your comments, insights and thoughts to improve this free web app.

Beta 1.3 – Released 3/17/10

* Full support for Omniture Analytics
* Bug fix with certain pages not being scanned for Google Analytics
* Few small bug fixes

Beta 1.2 – Released 02/28/10

* Added excel download option for download reports
* Added email delivery option for getting reports delivered by email once the scan is complete

Beta 1.1 – Released 02/22/10

* Frist beta release with support for 5 analytics software (Google, Omniture, Coremetrics, Yahoo and web trends)

Web Analytics Scan Update is a post from: Key Web Metrics & Web Analytics Blog

What if there was a way to find what part of the content on any given page is consumed? What if you can generate a report that shows if your headline and first paragraph are able to drive visitors to read the next part of the content?

Omniture recently announced a cool new plugin for their SiteCatalyst analytics tool. This plugin allows users to view the percentage of content viewed on any given page vertically.

The plugin is totally free for current SiteCatalyst customers. You can find the plugin code on the Help -> Supporting docs -> Implementation -> Plugins section of SiteCatalyst help section.

Here are step by step instructions on how to install this plugin.

#1. Add a new traffic/property variable.

Admin -> Report Suites -> Edit Settings -> Traffic -> Traffic Variables

#2. Set the new s.prop value to the percentage page viewed function. This variable will record the percentage of the previous page viewed.

#3. Create another s.prop traffic variable. This variable will be used to store the previous page value. Adding this variable will allow us to combine the page name with the percentage page viewed value metric.

#4. Prepare the code for implementation. This is how your final code should look like.

#5. Copy the code in the s_doPlugins() function located in the “Plugin Config” area of the s_code.js file.

(Click here to download the code file)

#6 Finally, copy the following code in “PLUGINS SECTION” area of the s_code.js file and allow SiteCatalyst to populate reports. You should see two new reports inside the Custom Traffic section.

(Click here to download the code file)

Here is a quick screen shot of how the final Custom Traffic report should look like.

Please share your thoughts, insights and comments because it really helps me write more effectively.

Measuring Content Effectiveness with Omniture SiteCatalyst is a post from: Key Web Metrics & Web Analytics Blog