Local Search & Web Analytics SMX Advanced London 2011

Local Search & Web Analytics SMX Advanced London 2011 

From Martijn Beijk

10 Promising Free Web Analytics Tools

10 Promising Free Web Analytics Tools

Web analytics is the process of gathering and analyzing your web content’s data in order to glean meaningful information about how your site is being utilized by your users. There are plenty of Web analytics applications out there, and you probably already know the big guns such as Google Analytics, Crazy Egg, and remote-site services such as Alexa and Compete.

We go off the trodden path and explore a few lesser-known Web analytics options. In this article, you’ll find 10 excellent and free tools and applications to help you gather and analyze data about your web content.

1. Piwik

Go to Live Demonstration of Piwik.

Piwik is an open-source Web analytics application developed using PHP and MySQL. It has a "plugins" system that allows for utmost extensibility and customization. Install only the plugins you need or go overboard and install them all – the choice is up to you. The plugins system, as you can imagine, also opens up possibilities for you to create your own custom extensions. This thing’s lightweight – the download’s only 1.9MB.

2. FireStats

Go to Live Demonstration of FireStats.

FireStats is a simple and straight-forward Web analytics application written in PHP/MySQL. It supports numerous platforms and set-ups including C# sites, Django sites, Drupal, Joomla!, WordPress, and several others. Are you a resourceful developer who needs moar cowbell? FireStats has an excellent API that will assist you in creating your own custom apps or publishing platform components (imagine: displaying the top 10 most downloaded files in your WordPress site) based on your FireStats data.

3. Snoop

Snoop is a desktop-based application that runs on the Mac OS X and Windows XP/Vista platforms. It sits nicely on your system status bar/system tray, notifying you with audible sounds whenever something happens. Another outstanding Snoop feature is the Name Tags option which allows you to "tag" visitors for easier identification. So when Joe over at the accounting department visits your site, you’ll instantly know.

4. Yahoo! Web Analytics

Yahoo! Web analytics is Yahoo!’s alternative to the dominant Google Analytics. It’s an enterprise-level, robust web-based third-party solution which makes accessing data easy especially for multiple-user groups. It’s got all the things you’d expect from a comprehensive Web analytics tool such as pretty graphs, custom-designed (and printable) reports, and real-time data tracking.

5. BBClone

Go to Live Demonstration of BBClone.

If you’re looking for a simple, server-side web application that doesn’t rely on third-party services to monitor your data, check out BBClone – a PHP-based server application that gives you a detailed overview of website traffic and visitor data. It supports language localization for 32 languages like English, Chinese, German, and Japanese. It easily integrates with popular publishing platforms like Drupal, WordPress, and Textpattern. Since it’s logfile-based, it doesn’t require you to use a server-side relational database.

6. Woopra

Woopra is a Web analytics application written in Java. It’s split into two parts which includes a desktop application for data analysis/exploration and a web service to monitor website statistics. Woopra has a robust user interface, an intuitive management system that allows you to run it on multiple sites and domains, and even a chat feature so that you can gather non-numerical information by talking to your site users. Woopra is currently in beta and requires you to request for a private beta registration.

7. JAWStats

JAWStats is a server-based Web analytics application that runs with the popular AWStats (in fact, if you’re on a shared hosting plan – AWStats is probably already installed). JAWStats does two things to extend AWStats – it improves performance by reducing server resource usage and improves the user interface a little bit. With that said, you can’t go wrong with just using AWStats either if you’re happy with it.

8. 4Q

A large part of Web analytics deals with number-crunching and numerical data. Raw numbers tells only part of the story and it’s often helpful to perform analytics by way of interacting with actual users. 4Q developer Avinash Kaushik puts it perfectly when he said: "Web analytics is good at the ‘What’. It is not good at the ‘Why’".4Q is a simple surveying application focused on improving your traditional numerical Web analytics by supplementing it with actual user feedback. Check out this YouTube video on how easy it is to set up 4Q.

9. MochiBot

MochiBot is a free Web analytics/tracking tool especially designed for Flash assets. With MochiBot, you can see who’s sharing your Flash content, how many times people view your content, as well as helping you track where your Flash content is to prevent piracy and content theft. Installing MochiBot is a breeze; you simply copy a few lines of ActionScript code in the .FLA files you want to monitor.

10. Grape Web Statistics

Go to Live Demonstration of Grape Web Statistics.

Grape Web Statistics is a simple, open-source application geared towards web developers. It has a clean and usable interface and has an Extensions API to extend and customize your installation. It uses PHP for the backend and you can run it on any operating system that runs PHP.

Let’s talk about it.

What Web analytics software do you use, and why? Do you have any extensive experience in using any of the above application? Share it with all of us in the comments!

Source: 10 Promising Free Web Analytics Tools

Web Analytics: Google vs. Yahoo

Google Analytics & Yahoo Web Analytics Comparison

The last 12 months have seen the Google Analytics (GA) product evolve into a serious contender for a do-it-all product for most businesses, a period that has also seen Yahoo! get serious with analytics through the purchase of the not-so-well-know European product called Indextools - the decision by Yahoo! to make the Indextools product free with a rebrand into Yahoo Web Analytics (YWA) has turned the free market into a rich, dynamic, competitive space that’s seeing incredible product innovation.

Insightr Consulting are certified in Google Analytics through the Individual Certification programme as well as being a pioneer member of the Yahoo Web Analytics Consultant Network (YWACN). Our clients use a mixture of Google Analytics, Omniture Site Catalyst and Yahoo Web Analytics, with the majority of new businesses adopting either GA or YWA. In Singapore where we are based (and indeed across Asia) budgets for analytics are not as formalised as they are in markets like the US and Europe, so free tools are very popular here.

This article is the outcome of over 5 weeks work carrying out a feature by feature comparison of the Google Analytics and Yahoo Web Analytics products - a project that required a large overhaul after Google announced new features on the 20th October (more examples of the product innovation we’re seeing). Yahoo Web Analytics is still a largely unknown product to business and analysts alike as the product is only available through the YWACN or via Yahoo! advertising sales teams - this comparison should give you a pretty good feel for what you’re missing.

As our friends at Yahoo would say, this is perhaps an unfair comparison - as Indextools always liked to think of the old product as 80% of Omniture at 10% of the price. They weren’t wrong. In fact as an Omniture Site Catalyst user for over 7 years (how many of you can recall SC7?) the Yahoo offering is in many ways more powerful than Site Catalyst; especially when it comes to ‘advanced’ features such as segmentation which for Site Catalyst are only available with an additional “Discover on Demand” license.

Some of you will disagree with our analysis, and particularly with our scoring system - we’re hoping that the comparison is a thought starter and something that will lead to your consideration of the YWA product as a tool worth considering. We feel the scores are fair based on our usage of products and the way our clients will use them.

So, here’s the presentation - it’s best if you view it in full screen otherwise the screenshots will be too small. We apologise for the low quality of some of the screenshots - this was required to keep the file size down. It’s also a long document, over 50 pages - but that’s because both of these tools are powerful and are feature packed! We hope you enjoy it and get value from our work:

If you like the look of Yahoo Web Analytics, and in light of the fact that you’ll need to go through a Yahoo! consultant to get access we’re offering a Google Analytics to Yahoo Web Analytics migration package for a fixed US$2,500 project cost. Here’s what we’re offering:

Insightr: The ultimate comparison between Google Analytics and Yahoo Web Analytics; http://j.mp/2wenKg

Advanced Filtering in Google Analytics

Advanced Filtering in Google Analytics simplifies narrowing down data in the reports table by allowing threshold filters to be created. Instead of creating standard profile filters or weeding through rows and rows of data, Advanced Filters can be created on the fly for any report.

Here is another in-depth look at one of our recently announced new features: Advanced Filters (or Advanced Table Filters), written by the excellent team at LunaMetrics, a Google Analytics Authorized Consultant.

For the daily user, Advanced Filters may be the most useful new feature of the bundle of new features, in terms of streamlining your actual process once you access a report and are actively doing analysis. They are found at the bottom of the table in any report. As a habitual poweruser, I've been clamoring for it for years, and it has made my process so much simpler. It's the equivalent of replacing a screwdriver with a powerdrill.

You no longer need to export your data to slice and dice it to see your desired subsets. Now, you can set a filter while looking at a certain report to get the information you want, without having to exit and create a filter or advanced segment. Within seconds, you can whittle down a massive data table to look at a subset that is important to you.

One example already given in this tutorial video is to show just the keywords that have a low bounce rate (less than 30%) and that referred at least 25 visits. Right away, you've found high value and high traffic keywords. We're using this feature almost every time we look at a data table in a report. It makes you feel much more command over your data.

Here are three more interesting uses of the new Advanced Table Filtering:

Looking for specific non-branded keywords

Sometimes, it helps to see keywords that contain a certain word or phrase, but exclude the brand name. Taking a company called DeLallo Italian Foods, for example. If I wanted to see all the keywords that contain the word Italian food but exclude the brand name DeLallo, I could easily use the advanced filters for this. Previously, I would have done this using regular expressions in the filter:

Filter Keyword: containing ^(?=.*italian food)(?!.*(delallo)).*

No more! Now, we don't need to do this! Now, it is so easy with the advanced filters. Just filter for Keyword containing Italian food and excluding DeLallo.

And presto! Your report is updated. And, at any time, you can edit this filter to further refine it, or delete it altogether.

Landing Pages, Sorted by Bounce Rate

Has this ever happened to you - you're looking at your Top Landing Pages report, and you sort by bounce rate, only to have a bunch of pages with 1 entrance clogging the top of the report? With advanced filters, you can filter out those pages with a low number of entrances to get a better look at which landing pages with significant traffic have a high bounce rate. All you have to do is filter by Entrances greater than 50 (or whatever threshhold floats your bounce-rate-boat).

Top Content, Sorted by $ Index

Another similar use for sites with e-commerce or a goal value enabled is when you're looking at the Top Content report, sorted by $ Index. What you're trying to find are the pages that have the highest value - those that are viewed during a visit that results in a conversion. Again, it's common to get a lot of pages at the top that have a low number of pageviews.

First, it helps to filter out those pages that have a low number of pageviews. But once you do that, you'll likely see the pages with the highest $ Index are pages of your shopping cart or checkout process. We can filter out these pages with the advanced filters too - just add a new condition below your first filter that excludes pages that contain the word cart (or checkout, etc.) in the URL.

These three examples give you a taste of Advanced Table Filtering for your analytics, but they just scratch the surface. Once you explore your own analytics, I’m sure you’ll find many more uses of this flexible and powerful new feature. You'll really notice it's use when you find you're happily lingering for 5 extra minutes, using this new interface feature to easily gain insights and ask questions that would've taken you an hour before and possibly a data export. Pure wizardry. :)

Courtesy: Google Analytics

Differences in web analytics systems

Differences in web analytics systems (TNO report)

One of the presentations was the research TNO in the persons of Almerima Jamakovic, Bart Gijsen and Martijn Staal has to "differences in Web Analytics. One of the presentations was the research TNO in the persons or Almerima Jamakovic, Bart Gijsen and Martijn Staal has to "differences in Web Analytics. The subtitle is: Facts, myths and expectations." The subtitle is: Facts, myths and expectations. In this article the slides of the presentation and a summary of the findings. In this article the slides of the presentation and a summary of the findings.

Main conclusions:

• Differences between measurements of web show (for a good implementation) over long periods of constant, but vary by site. Differences between measurements of web show (for a good implementation) over long periods of constant, but vary by site.


• For web, a maximum percentage difference between measurements of different packages. For web, a maximum percentage difference between measurements of different packages. This is good guidelines to ensure the reliability of web and checking implementation. This is good guide lines to ensure the reliability of web and checking implementation.


• Dart and STIR data, both absolute and trends hardly comparable. Dart and STIR data, both absolute and trends hardly comparable.


• The explanation of all the causes of the differences is very complex, because differences usually result from a very large number of causes. Explaining all the reasons for the differences is very complex, because differences usually result from a very large number of causes. Attention should be paid to advance the accuracy of the implementation of the packages. Attention should be paid to advance the accuracy of the implementation of the packages.

Summary: (from TNO)

Differences in web regularly lead to questions about the reliability of the data. The migration to another package, the 'coincidence' Comparing the statistics with data from other packages and Settlement advertising can thus give rise to much discussion.

TNO in cooperation with Blue Mango, Click Value, Maximum and Netprofiler investigated the reliability of web. The migration to a different package, the 'coincidence' Comparing the statistics with data from other packages and advertising Settlement can thus give rise to much discussion. In cooperation with TNO Blue Mango, Click Value, Maximum Netprofiler and research into the reliability or web.

Important questions to what extent differences were real and acceptable, the reliability of the web for a specific implementation of statistics to assess. Important questions to what extent differences were real and acceptable, the reliability of the web for a specific implementation of statistics to assess

Project Approach: Differences In Web

A solid basis to understand the differences to last year by Stone Temple through the Shootout report. In collaboration with online marketing experts of Blue Mango, Click Value, Maximum and Netprofiler TNO started in the second half of 2008 a project to further detail the differences and measurement of the web to understand and a picture of the reliability of the data. In collaboration with online marketing experts of Blue Mango, Click Value, Maximum and Netprofiler TNO started in the second half of 2008 a project to further detail the differences and measurement of the web to understand and a picture of the reliability of the data. The approach is comprised of two types of studies. The approach is comprised of two types of studies. First, several large Dutch websites statistics data with STIR and Dart analyzed. First, several large Dutch website statistics data with STIR and Dart analyzed.

This analysis worked under other Agis, Ilse Media, typhoon, Univé Insurance and TNO them. This analysis worked under other Agis, Ilse Media, typhoon, Univé Insurance and TNO them. For additional insight into the differences and the causes of these differences, are second in a closed environment testing of different website packages Web executed. For additional insight into the differences and the causes of these differences, are second in a closed environment testing of different website packages Web executed. In the closed environment, the traffic was regulated and variables such as the click, IP addresses and browser types adjustable. In the closed environment, the traffic was regulated and variables such as the click, IP addresses and browser types adjustable. The kits have been tested in the closed environment are Google Analytics and Webtrends Sitestatstext. The kits have been tested in the closed environment are Google Analytics and Webtrends Sitestatstext. In addition, the data analysis of some sites also HBX parcels and Speed Trap included including Dart and STIR data. In addition, the data analysis of some sites also HBX parcels and Speed Trap included including Dart and STIR data.

The differences between measurements of packages on a website are constant

The analysis shows that the measured values by various website statistics packages often very different. The direction and extent of the trends for the number of visitors, visits and page views appear to be highly negotiable. The direction and extent of the trends for the number of visitors, visits and page views appear to be highly negotiable. This means that the differences between the packages remain constant over longer periods. This means that the differences between the packages remain constant over longer periods. But although the differences between measurements show constant, this difference is not the same for each site. But although the differences between measurements show constant, this difference is not the same for each site. A statistical package on one site structurally higher values than package B, there is another website just to give lower values. A statistical package on one site structurally higher values than package B, there is another website just to give lower values. Important reasons for this appear to lie in the content and structure of the website. Important reasons for this appear to lie in the content and structure of the website

What degree of difference is real and acceptable?

An important conclusion from the research is that the analysis shows that the values of Web measurements are normally distributed. In addition, the analysis that the distribution of statistics from well-configured software is an upper limit to be specified. In addition, the analysis that the distribution of statistics from well-configured software is an upper limit to be specified. These statistical properties of concrete rules of thumb for 'acceptable' or 'real' disorders. These statistical properties of concrete rules of thumb for 'acceptable' or 'real' disorders. This allows website (statistics) managers simply the reliability of the implementation of web check by the percentage differences between the packages to compare with the number of packages that you use. This allows website (statistics) managers simply the reliability of the implementation of web check by the percentage differences between the packages to compare with the number of packages that you use. Failure to meet the guidelines, then this practice implementation errors or incidents which significant differences occur. Failure to meet the guidelines, then this practice implementation errors or incidents which significant differences occur. This control is used for both large and small websites because research shows that the number of visitors, visits and page views a minor influence on the results. This control is used for both large and small websites because research shows that the number of visitors, visits and page views a minor influence on the results.

Check here the reliability of your web

The websites to which two or more packages are being used is relatively easy to determine whether statistics are well implemented. In addition, it is worthwhile for websites with 1 package for an additional (free) package like Google Analytics to implement this control can do. In addition, it is worthwhile for websites with 1 package for an additional (free) package like Google Analytics to implement this control can do.

For the reliability check, the following guidelines:

• Decide on the basis of statistical data on a weekly or monthly level for a few periods the percentage difference in visits, visitors and / or page views between the packet containing the highest and the package with the lowest value.


• Select the table row with the number of packages that you have running on your site


• Is your rate fixed for several periods greater than the percentage in the column "Max-Min deviation rarely greater than", it is likely that the implementation of the WA so different packages (eg a set of tags are not all webpages) that the interpretation of the data is incomparable. Is your rate fixed for several periods greater than the percentage in the column "Max-Min deviation rarely greater than", it is likely that the implementation of the WA so different packages (eg a set of tags are not at all webpages) that the interpretation of the data is incomparable. Late in this case the implementation by the ICT department or you look Analytics Agency, or consider an audit. Late in this case the implementation by the ICT department or your Analytics Office look, or consider an audit

Dart and STIR data are not comparable

In addition to an examination of the web for some sites, the Dart and STIR data examined. In addition to an examination of the web for some sites, the Dart and STIR data examined. The assumption that these data are not comparable with the web data, is confirmed by the investigation. The assumption that these data are not comparable with the web data, is confirmed by the investigation. Because there are other objectives and analysis methods used are the absolute data and trends little or limited comparable. Because there are other objectives and analysis methods used are the absolute data and trends little or limited comparable

Causes of differences in WA packages

In the closed test, a number of causes further. Basis for this was a non-exhaustive list of causes: Basis for this was a non-exhaustive list of causes:

By pre-established traffic on some of the outer world shielded webpages result, there was more insight into the different ways of measuring the WA packages. This revealed that the packages largely the same work, and therefore in principle should give the same numbers. This revealed that the packages largely the same work, and therefore in principle should give the same numbers. The differences that still occur seem to be partly caused by the failure count of page views by Webtrends when using the back arrow in your browser.

The differences that still occur seem to be partly caused by the failure count of page views by Webtrends when using the back arrow in your browser. In addition, none of the packages are able to traffic comes from webbots full filtering. In addition, none of the packages are able to traffic comes from webbots full filtering. In general we find that the deviations are mainly caused by the large number of relatively small causes. In general we find that the deviations are mainly caused by the large number of relatively small causes. Explaining all the reasons it is very complex, so the focus has to go to a good implementation of the packages. Explaining all the reasons it is very complex, so the focus has to go to a proper implementation of the packages.

Yahoo! Web Analytics

Yahoo! Web Analytics is an enterprise site analytics tool that provides real-time insight into visitor behavior on your website. With powerful and flexible tools and dashboards, Yahoo! Web Analytics helps online marketers and website designers enhance the visitor experience, increase sales and reduce marketing costs.

FEATURES & BENEFITS

EXECUTIVE DASHBOARDS

View key performance metrics within customizable executive dashboards.

• Customize your dashboard with the metrics, benchmarks and gauges that meet your specific needs and preferences.
• Quickly set goals, track progress and identify danger points.
• Each person and role within your company can have their own dashboard.

CUSTOM REPORTS

Tailor your reports with the Custom Report Wizard.

• Add categories to pre-defined reporting items, so your reports match the way your business is organized.
• Use custom fields. For example, if you have a travel website, you could track according to travel destination, length of stay, price ranges, or ticket type.

ADVANCED CAMPAIGN MANAGEMENT

Track and optimize your marketing campaigns.

• Measure cost-per-click (CPC), cost-per-impression (CPM), cost-per-acquisition (CPA) and return-on-investment (ROI)-and adjust your budget if necessary.
• Organize your reports by hierarchical categories you determine.
• Analyze your campaign results according to the categories you define.

REAL-TIME SEGMENTATION

Analyze how different groups of visitors respond to different variables on your site.

• See how visitors react to different campaign landing pages, page layouts, calls to action, and more - then optimize your pages and offers.
• Identify your best visitors and use that information to find more of those visitors.

LIVE COST ANALYSIS

Compare search engine price information to help keep revenues in check.

• Take advantage of Advanced Live Cost Analysis that collects data from Yahoo!, Google and MSN, and integrates it with the revenue earned on your website.
• Measure the ROI of your paid search campaigns, keyword by keyword.
• Resolve inconsistencies between Yahoo! Web Analytics data and your Paid Search reports.

MERCHANDISE REPORTING

Identify purchase patterns to help promote profitable products.

• Track the products - and product combination's - your customers purchase, add to their carts, and preview.
• Create reports that reflect cancelled orders or changes to order amounts by sending API requests to the system.
• Upload product costs to calculate overall campaign profitability.

SCENARIO ANALYSIS

Analyze visitor paths to reduce customer drop-off.

• Track visitor behavior through multi-step processes, like purchases or form submissions, and troubleshoot popular paths to improve task completions.
• Redefine a process and the changes apply to historical data too.

COMPARATIVE REPORTING

Compare reports from two time periods, side-by-side.

• Learn how your website performance develops from month to month.
• Bookmark reports and use past results as a benchmark for improvement.

ADVANCED PATH ANALYSIS

Get in-depth insight into visitor navigation around your site.

• Identify popular paths through your site - viewing user paths as branched, hierarchical maps.
• Drill down on branches to follow visitor movements down to a single visit.

MARKETING WORKFLOW MANAGEMENT

Enhance your site monitoring and report management capabilities.

• Monitor events that affect your website, such as site changes, holidays or system outages.
• Create custom email alerts to notify you of changes to website performance.
• Improve communication with colleagues by sharing notes on reports and dashboards, and color coding report results to easily identify irregularities.