Recently in Traffic Analysis Category

I'm sure every web analysts look at site visitors frequently. It is probably the first thing everybody ask and look for any discussion relating to web sites.

I thought I would give a little different perspective on how we typically look at traffic data, using monthly visitors as an example on Z-Chart.

Before diving into looking at Z-Chart, let's quickly go over what Z-Chart is.
Z-Chart is a method of short/long term forecasting by plotting cumulative and moving total figures for any measured value across time on one chart.
There are three lines represented in the Z-Chart:
(1) Current line: It shows the variation for each period
(2) Moving total: Smooths out any seasonal variations
(3) Cumulative line: Joins these and may show progress towards a goal

The name Z-Chart arises from the fact that the pattern on such a graph forms a rough letter Z. Typical application of Z-Chart is on sales figure, but let's see this from web site traffic perspective.

Here is a rough example monthly visitors data from a site with positive growth, and another one with not so exciting traffic growth. Evidently, Z-Chart will tell you if your trend is sucking or not. Sharp positively increased Z (left image) shows some significant growth trend, while sagging Z (right image) shows the site traffic is not doing well as the other.

Note that the Z-Chart could be dissected to remove some of distraction like the cumulative total that gives an impression that the site traffic is growing. (Obviously 2009 data on the right chart is much lower than 2008). The idea of having these two Z-Charts side by side is to show how it would look when two different data are trending differently, and to apply general web analytics approach comparing one segmented data to another. (e.g. overall traffic vs. product page view).

Here is an idea for web analytics. If you can apply overall traffic and compare it against segmented traffic. For example, overall monthly site visitors for one Z-Chart and monthly visits to product pages on another Z-Chart. What does the difference look like? If it looks like the example on this post, then there might be something broken with accessibility or acquisition strategy on product visibility. That raises a question like "why is my product pages traffic are not seeing the same Z shape as overall site traffic?". Then you need to further dissect the chart and data.

There are many charts related postings out there and it is definitely worth reviewing them. You could be dissecting these type of charts in so many ways, and find that detailed insights are not immediately available form this one single chart. Going to leave that expertise to the chart gurus. :-)

What does your Z-Chart show you? Feel free to give me a holla back on twitter @k_irizawa.

Some links on Z-Chart related topics:
http://home.ubalt.edu/ntsbarsh/Business-stat/stat-data/Forecast.htm#rzchartforcat
http://syque.com/quality_tools/toolbook/Line/vary.htm

Very nice tutorial on excel and charting techniques.
http://www.peltiertech.com

One of the ultimate outcome for having a web site is to drive and improve customer loyalty. It is not common for major companies to have customer support site, forums, pages, etc. However, I feel like many companies spend little time measuring their customers' activities on their websites, and optimizing their online strategies for online support and care. Maybe experts are simply not talking or sharing their learnings. (Man, I would love to hear what they got to say.)

After quickly searching on Google, Yahoo! and Bing, I could not find relevant content relating to Web Analytics for Customer Support and Care. Some may blame me that I didn't do a great job searching for such studies and writings, but I am definitely not happy with the results I found on search as of the date of this writing. So I am going to brainstorm an initial roadmap on web analytics for customer support and care sites.

Outcome

Obviously, companies are trying to increase customer loyalty by providing great services, support, and care. From a corporate web site's perspective, there are 3 main goals to achieve in increasing customer loyalty.

1. Reduce support calls & cost.
2. Customers finding the solutions they need help for.
3. Serve relevant solution and care through the site.

KPI - Key Performance Indicators

Support Calls & Cost

• Number of support calls for specific reporting period
• Total support cost for specific reporting period

Customers finding the solutions they need help for

• Number of entry visits to support section by "Support Related Redirect" and "Search Engines"; Increase direct entry to support pages from sources and channels where customers with problems would likely to start from.
• Bounce or Exit Rate on On-Site Search and other initial point of interaction that takes users to list of potential solutions (like FAQ page); Customers will leave (bounce) if the site serve suboptimal results, so it is imperative to measure if your consumers are findings the relevant solutions.

Serve relevant solution and care through the site

• Customer satisfaction score (thru surveys)
• Number of Task Completion and Rate per key interaction pages/points (micro conversions); Identify pages and customer interaction points that tells us the customer experience -- Example: Feeback on Helpful Yes/No, Visits to Email Support Confirmation Page, Reduction in click-thru to contact us (page with off line number), etc.

Strategies and Tactics

I feel like most of the companies are just throwing FAQ pages up and not optimizing the results. However, there are companies out there doing great job in executing the customer support site, and by looking at the analytics tracking code, you can get some sense of understanding on how they're positioning their web analytics tool.

Also I feel like strategies and tactics are executed without having a plan or roadmap. Maybe many major firms do have a clear roadmap, but I don't find many discussion about it. I hear more about measuring conversions, engagements, SEO, PPC, site optimizations, etc.

The critical point for customer care and support from web site perspective other than lowering cost and increasing user satisfaction is; "find-ability" of the solution. Theoretically speaking, customers should be able to find the answer and solution to their questions with ease. Perhaps finding the solutions directly from search, and from both Search Engines and On-Site Search. I think Apple has done a great job at least from the outside (don't know anything about their data). Check out the forums and FAQ pages' title and how they are indexed on search.

Other major firms' site are great source to check and see how you your site's usability compare. In order to avoid subjective views, "Search Engines" are great tool to measure it. Example -- looking at what contents are index using "site:forums.xyz.com" on Google, and checking out their robots.txt files, using google search insights, competitors' twitter account using twitter measurement tools, etc.

Customer Support and Social Media

I feel like I read more and actually find interesting in this Web 2.0 era is Customer Support + Social Media rather than using web analytics to measure and optimize the web site's property.

Here are some articles on Customer Care/Support & Social Media (mostly Twitter)
Comcast: Twitter Has Changed The Culture Of Our Company
HOW TO: Use Twitter for Customer Service
Customer Support via Twitter?

From web analytics point of view, there would be additional KPI assigned to the road map if customer care and support becomes more integrated and practiced via Social Media, but I will hold that conversation for another time.

Going back to many years ago, web analytics initially started from log file analysis to support IT and programmers to help them debug issues on the server.

Recently, I have been working with web developer for one of our new site. It is always nice to be working with a developer who is sharp and with full of interest for web analytics. These developers work so hard to help us web analysts get proper tracking into the site. This article is a bit of a dedication to those who help us analyst get the data that puts bread and butter on our table.

Here are some scenarios I would like to highlight where web analytics will work very closely with IT/programmers and integrate to drive better web site experience for your site visitors. (I only highlighted the things that came up in my mind at the time of this writing, and skipped the obvious part, implementing analytics tag.)

On Site Search

It is common to find more major enterprise to invest in on-site search (or internal search) technology. An example is Google Search Appliance. Obviously, the IT team in your company would be installing this to the server.

Web Analytics analyst should get involved in this, because even if the appliance has some nice data around what people are searching on the site, web analytics application should have standard metrics relating to the search results, and eventually assess behavior data and impact to the outcome (bounces, orders, revenue, and many other interactions generated from on site search).

Depending on the search results and the outcome, web analytics analyst should work closely with the IT in optimizing the appliance, so relevant search results are given to your site visitors. Potentially what you do in this optimization can impact the outcome as well.

Error rate

Launching a new site, replaced shopping cart, replaced old products with new, ending a promo, etc. For whatever reason, there are chances that your site visitors are landing on error page or page showing that the content is not available. Typically the server will send back a 404 error message. That is why it is usually error pages are referred to as 404 error messages.

The majority of Web Analytics applications have the capabilities to track such visits to error pages. Web Analytics analyst should know what is the % of error page served. Hopefully you are aiming for 0%. Understand where visitors are coming from to arrive at the error page, and with what URL.

All this information will help your IT folks to set up a proper redirect, or even get communication started with product/content managers to serve or activate relevant content to replace that error.

This is a great article on 7 Ways Of Handling 404 Error Messages. Checkout what some companies have done to address 404 error messages.

Redirects

Major corporations investing heavily on online/offline campaigns are likely to be setting up redirects to direct site visitors to relevant landing pages. Redirects would most likely be set up by IT, and web analytics would be working with the marketing and IT folks to set up appropriate campaign tags to assess marketing efforts.

It is not only important to assess the campaigns/redirects, but to understand if there were any impacts when redirects were taken down or if redirects' usage has changed (re-using old redirects for new campaign, etc.). Having a transparent communication process in place for managing redirects would be crucial to a success in web analytics practices.

Other Area of Technical Web Anlaytics

There are many other web analytics data that will help programmers and IT folks to understand what system environment the site visitors are in. Some of the metrics are Browser Versions, Operating Systems, Connection Speeds, Flash Versions, JavaScript Versions, etc.

It might be a good idea to sit down with the IT and Programmers before any major releases take place, and review if any upcoming programming or changes in infrastructure could impact site visitors or customers' site experience.

Sharing Results with the Programmers and IT

Programmers and IT folks deserve to know the results, too. When web analytics analyst creates report for managers and key business groups, it would be great to share the results with the technical people as well. I had the privilege to work with smart IT and programmers in the past, and sharp technical folks ask brilliant questions which in many occasions should have come out of marketing managers.

Having a conversation about optimizations and exchanging ideas with technical folks can benefit web analytics analyst in many ways. For example, having their resource to tweak on-site search and increase revenue can definitely make our contribution to business shine.

Just installed your Google Analytics for the first time?
New to Web Analytics?
Did someone tell you to look into design, usability, and path analysis for your first project?

Considering that there are so many metrics and dimensions to deal with, just by tagging Google Analytics tags on every page on the site. Analysis and reporting could get extremely complicated.

What I recommend is to relax and look at the basic metrics, but applying smart segmentations. If you're going to puke before looking at the data, might as well puke after looking at bad data.

I've asked my family's friend to see if I can check out e-commerce data and use it anonymously. So here you go.

Very high level data, including overall site visits (which something we may not care at all). The important thing is to leverage available segments and apply few basic custom segments to better position yourself in a pool of data.

What I did here is applied "Visits with Transactions", "Non-bounce Visits", and "Users who visited the shopping cart, but did not purchase". It is amazing that even a site with average bounce rate of 32%, can have a significantly bad data that is puke-able.

First, visitors adding item to cart was only 5% of all site visitors. I think that's pretty bad, but let's assume that is good. Now, what about only 2% of the shopping cart visitors completing the order (0.1% of all site visitors)?

This pretty much paints the big picture of different level of opportunity pie, and how much qualified visitors you're brining into the site. Is this still good or bad? I don't know, maybe the average order value is super high ($1,000 or more..) and this site is making huge money... but that's something you and your business need to decide and set goals.

Looking at average pageviews with those segmentations (same as pages per visit), it is amazing that visits with transactions are going through roughly 31 pages just to convert. Notice that visitors who hit the cart page, but didn't ordered was 17 page views. That means people who hit the cart and ordered are going through 14 additional pages on average. Definitely some opportunity to optimize the conversion process. What does your data show?

Average time on site shows a similar story, and it is quite obvious that customers are going through some rough experience just to convert.

Just applying simple segmentation to high level data like visits, page views, and average time on site, can give you some very high level, but very insightful data to initiate of some more data diving.

I like looking at this "Map Overlay" within Google Analytics, but I always ask what I can do with this data. Here are few questions that could possibly come up when you look at the traffic from different geo locations:

• Which cities or countries have a great interest in the topics/services/products that you serve?


• How can you reach the potential site visitors in the empty part of the map?


• What is the difference in traffic behavior and performance for people viewing your site from different location?


• Biggest question is "What can you do to leverage this geographic data and increase your reach and increase site traffic?"

Before I look at these questions individually, I think geographic data is useful even if you're targeting users within your local area. Why? Because I think internet gives you the opportunity to grow your business/services/content beyond your local area, and learn from others outside of your local area.

Also just a piece of advice, if you're willing to serve your site to specific region you might want to consider the following strategies.

1. Use Google Webmaster Tools and set your "Geographic Target" in the settings.


2. Leverage country specific domain.


3. Obviously, use language specific to the region you want to target.

Now, back to my main questions and my insights surrounding it...

Which cities or countries have a great interest in the topics/services/products that you serve?

I came to learn that in past few days or weeks, my site had the most traffic from the city of London, and San Francisco came in second. I knew that UK is going wild with their interests on web analytics, and it definitely supported traffic to my site. However, people from San Francisco had lower bounce rate with higher pages per visit. This is where I had to drill down and try figuring out the "why" part.

So the point is, if your site is serving content that is readable to other countries, and traffic outside of your country is supporting your site's objective (buying, reading, registering, etc.), then geographic data becomes very important. If people in London is reading more content on my site, and supporting great outcomes, then maybe I need to act by writing in UK English style.

What does it look like for your site? Is the traffic from other countries significant enough to consider enhancing/adding sites targeting to those visitors?

How can you reach the potential site visitors in the empty part of the map?

Looking at the BLUE box that I circled within the map, I am thinking those countries should be considered in serving content to potentially acquire higher traffic/readership. Why those parts of the map in the entire world? Well, China (Mandarin), India (Hindi), and South America (Spanish) are the top languages that make up the top 4 languages (including English). These three languages (population of native speakers) combined is 2.7 times higher than the number of English speakers. Some may argue, there are more population in other countries where there are more households with connection to the internet. So it is not only the number of native speakers, but looking at their connectivity to the internet and interests to the subject served from your site is more important.

This is where you need to leverage "Language" metrics, where the data captures the preferred language that visitors have configured on their computers. Why do you need to look at this metrics? Well, it could be the English speakers with English language preference visiting your site from Asia, Europe, Africa, or South America.

Back to the original question, if you're trying to reach the people in other region it is important to target regions with high potential to generate the desirable outcome based on population, language preference, internet connectivity, interest to site's topic, etc. Let's leverage these geographic and language data from your web analytics tools!

What is the difference in traffic behavior and performance for people viewing your site from different location?

Earlier, I've mentioned that site traffic from London performed differently from visitors from San Francisco. The difference in metrics is the key in taking necessary action to optimize your site. If you're targeting a specific group of people from specific region, but you're not getting a great site performance as other regions, then it is time for you to dig and drill into your web analytics application to find out what is going on.

Maybe it is time to open a site or add content in other language catering to users outside of your local area.

What can you do to leverage this geographic data and increase your reach and increase site traffic?

Based on the precious geographic and language data provided by web analytics application, it is time to think through and take actions based on your actionable data/insights.

Here are some ideas and possible actions you can take (including the points stated earlier):

• Create/add sites or content catering to people other than your local region. Example) Start a site written in Chinese, Hindi, Spanish, etc.


• Take advantage of Google Webmaster Tools to geographically target your site in search.


• Take advantage of domains specific to certain countries. Example) .jp, .us, .nl, .eu, etc.


• Add or optimize your content to serve increasing interests from other regions.


• Participate in search campaign (PPC) and target based on geographic location and language.

Hopefully, I was able to make you re-think about geographic and language data, and stimulate your interest in looking into opportunities to expand your site's potential across the world.

Being able to segment your site traffic by different dimensions is very important in the world of web analytics. If your web analytics software can't do that... think twice about it. Not only twice, if you can't segment your metrics, then maybe it is time to dump it and at least use Google Analytics for free.

I've listed out some of my favorites and ideas for applying segmentation. You'll see that a lot of the segmentation would be Segmentation A vs. Segmentation B, because the majority of segmentation would need to be applied so that you can compare to another data set. You can always compare to overall site data or even average for a specific time range.

Here are some examples of segmentations that could potentially assist your analysis.

• New visitors vs. Returning Visitors
• Direct vs. Search vs. Referring Sites
• Converted vs. Did not convert
• Registered vs. Not Registered
• Advocates vs. Non Advocates
• Branded Search vs. Non-Branded Search
• Loyal Visitors vs. Non-Loyal Visitors
• Users who put items in shopping cart but DID NOT purchase vs. Users who Purchased
• Engaged Audience vs. Not Engaged Audience

Multi-level Segmentation
Once you set up your segmentation and execute you analysis, you will get more curious about deeper segmentation. Let's call that multi-level segmentation.

Here is an example. Say you set up a segmentation analysis around new and returning visitors. Then it'll be wise to look at the difference between these two segmented groups by the search keywords they used to arrive at your site. Let's classify these groups as non-branded keywords and branded keywords.

It will look like this...
New Visitors vs. Returning Visitors broken down by branded terms and non-branded terms. Multi-level segmentation like this is do-able with careful implementation in Google Analytics. Other analytics applications do have such capacity to handle such segmentation so please consult with your vendors and their knowledge base.

What makes multi-level segmentation nice to look at, is that it allows you to zoom into a specific group and learn the difference between one segmented group to the other.

In the image above, non-branded terms had higher traffic than branded terms under returning visitors segment. However, what if it was the other way around (branded terms referring higher traffic from returning visitors segment)??

That means you must have done something great to promote your brand, so that retuning visitors are using your brand name in their search.

Ultimately, you'd probably want your direct and returning traffic to increase continuously right?? Well, that is another multi-level segmentation for you.

Direct - new vs. returning
vs.
Non-Drect - new vs. returning

Other than Omniture SiteCatalyst, WebTrends, Coremetrics, HBX, and Google Analytics, there are other possible web analytics tools to consider for your web analytics needs. And they are free!

If you're starting a blog or site for your company, but don't have that money to buy enterprise solution, you're most likely to use Google Analytics because that is like the standard for free web analytics tool now a days (because it is well known).

Check out the following list of applications, some of them could be a great tool to supplement your current web analytics application.

Woopra
Woopra is based on Java, and has both desktop and web service to monitor the metrics. Woopra has a unique feature that allows you to chat with your user and acquire non-numerical information.

*image from woopra.com

Other selling points of Woopra is Live Tracking, Rich User Interface, "Real-Time Analytics", "Lightning Quick Data Drilldown", "Visitor and Member Tagging", "API" and "Real Time Notifications".

Currently Woopra is in close private Beta.

For more info go to Woopra.com

Piwik
Piwik is an open-source web analytics application based on PHP and MySQL. What is great about Piwik, it has a "plugins" mechanism that allows various extension and customization. If you're a developer, you could probably make one your self.

What is good for some people or business is that Piwik's data is stored in your server/database. So you own the data. The user interface is customizable, which is probably something similar to Google Analytics dashboard. Piwik fans, you can correct me if I'm wrong.

For more info go to Piwik.org.

Yahoo! Analytics
Did you know Yahoo! had an analytics application?? Well, Yahoo! acquired IndexTools, and that became Yahoo! Web Analytics. It is an enterprise site analytics tools that provides data in real-time, with powerful tools and dashboards.

4Q Iperceptions
Big credit to @Avinash, 4Q is used by my site, and it has given me a lot of insights that are qualitative. It answers the "Why" part of your web analytics questions. It is an awesome tool gather your user feed back and their satisfaction with your site.

Check out my article about 4Q: Results from 4Q Iperceptions Survey | Measuring User Satisfaction

FireStats
FireStats is free for non-commercial usage, and FireStats costs 25$ per installation for commercial usage.

What I like about FireStats is that it is very simple. And visibility on your source agents and IP is a pretty nice feature. Apparently FireStats got great APIs so if you're a hands-on person, definitely might want to try it out.

Snoop
Snoop is a desktop based application that runs both on Mac and PC. Tagging is done in a similar fashion to Google Analytics, pretty simple and straight forward. Great feature of Snoot is the "Name Tags" to easily identify exactly who your visitors are. It works by associating information to username, e-mail, account ID, etc.

Other great web analytics tools
MochiBot: It is a free analytics tool designed for Flash assets. For those flash heavy sites, it might be a good choice to try MochiBot by simply adding few lines of ActionScript code in the .FLA files.

JAWStats: Server-based web analytics application that runs with AWStats. If you're happy with AWStats, then you'll probably like JAWStats. Benefits of JAWStats are easy installation and rollback, and doesn't interfere with AWStats. It has an easy dashboard manipulation.

A lot of analyst do run several web analytics applications. Example, for me, I run Google Analytics and 4Q Iperceptions. You definitely want to understand and research the benefits of each applications' features before implementing everything (unless you're obsessed with installing web analytics).

Make sure that you understand what data you need and the pros and cons of each web analytics system, even Google Analytics.

I sat in a meeting that went over the survey results going over the new site that relaunched back in 2008. As I've mentioned on my previous posts on 4Q Iperceptions, acquiring qualitative insights are powerful as measuring traffic on your site.

The survey firm utilized the ACSI (American Consumer Satisfaction Index) which is a method developed by University of Michigan to measure consumer satisfaction. Although the new site scored higher than the old site, it was really interesting to look at what aspect of the new site contributed higher score.

Design
The new site scored higher in user satisfaction when it came to the design. The old site was so old, I'm sure no matter what you did, it would have scored higher. Measuring user satisfaction on site design is pretty interesting because how the site looks could totally affect page views and bounce rates on the site.

Navigation
Extensive amount of efforts were put into the the navigational elements of the site. Users felt the new site provided ease of use and better navigational experience. So the satisfaction index was fair. However, the site is about recipes, and it does not provide the best navigational experience there because the internal search and recipe search functionality were confusing in terms of design.

The search box was shared with internal and recipe search, and users had to select the proper tab to fulfill their mission.

From web analytics stand point, it was obvious that users were confused because the terms users entered into the box were recipe related for both internally searched terms and recipes searched.

Content
What is unfortunate about the new site is a lot of the recipes on the old site was taken out (Don't ask why...). Therefore a lot of the users who referred to the new site for the recipe from the old site did not find the recipe they wanted to acquire.

Web analytics showed higher referrals and direct entries to the home page, because users visiting the old recipe that no longer exist on the site would get redirected to the home page. That caused higher bounce rate on the home page as well.

Summary
The survey analysis showed overall satisfaction of the new site was supported by the new design. Fresh design with easier navigational experience contributed to fair level of satisfaction. The caveat is that there are design fatigue when users start to get use to the site. So it is likely that your user satisfaction with design will go down, if they keep on revisit your site.

It is imperative to take actions in delivering the changes required to increase your user satisfaction. These actionable insights acquired quantitatively and qualitatively allow you to decide that actions you need to take. Also forecasting how your site visitors will feel and consume content will give another sense of what you need to do.

Once, you make your changes, measure and assess your data again. Your satisfied users will likely to return to your site, and become your advocates. Good luck!!

You might have encountered this situation when reporting your metrics report.
Your client or internal marketing managers saw the number of Pages per Visit (or Pageviews/Visit) increased or decreased, and they'll come asking rather that is good or bad.

* Pages per Vist = PPV

First of all, if you're getting a reaction to changes in PPV, that's probably better than getting no reaction or comment. However, it is important to come to an understanding with your counterparts that PPV could be a powerful metrics depending on how you look at it.

To me, it is quite useless if you just site there and look at this metric go up and down, and claim it as good or bad without any context or a goal.

Web site's goal and objective

Depending on what you're trying to accomplish with your web site, how you look at every metrics and KPI's would be different. In terms of PPV, what would be your bottom line?

How do you want your PPV to look like when you put your site's goal into consideration?

Case #1: Let's say you're going to run a mini-site to acquire site registrations, and attempt to market to those registrants later. It turns out you'll need a minimum of 3 pages to complete the registration process. In other words, reach the confirmation/thank you page.

Then ultimately, you'll like to see your PPV on this mini-site around 3~4. Obviously, if your PPV says 2, then people are probably not reaching the confirmation page. Time to look at the conversion funnel !!

Case #2: For news related site (like NYT, WSJ, Reuters, etc.), you can see PPV in many different ways. Because it is highly likely that these sites are monetizing through CPM based media ads, from that stand point, they may want to acquire a lot of PPV as much as possible. In that case, high PPV would be nice, but it is also important to assess different levels of PPV by various news categories.

If they're promoting related articles through artificial intelligence tool (IA, predictive modeling, etc.), then that will be another area where they would want to see multiple PPV as well. Setting goals for PPV by verticals or by different micro-objectives within a site would become important as well.

Translate that analysis and educate your users

From analysis stand point, each analysts are probably well educated enough to measure different level of PPV by looking at different dimensions (by source, site sections, etc.). However, your insights would need to be translated to others, so that they don't limit their views on PPV on one flat number in one dimension.

P.S.
I've encountered a site where PPV dropped 50% after the site relaunched, and it was due to multiple reasons, which was mostly attributed to better site design. It was a little challenging to translate to others that this "decline" was good. What's your story?

The term "Qualified Visitors" is a word thrown around a lot by marketers and analysts. To me, it is something that has to be defined by you and your business.

To give you a better sense of what it would mean to you and your site in context of web analytics, qualified visitors are site visitors that you identified as a desired target or lead.

Depending on your role and how you definite the business objective/goal of your site, qualified visitors could mean differently.

For example, if you're a webmaster, your qualified visitors could mean those who didn't hit the error pages. If you're a sales/acquisition manager, then number of leads or registrations acquired through the site could mean qualified visitors.

Now, the objective of this article is to explain how you would assess and analyze that qualified visitors, and obtain that percentage of qualified visitors on your site. This is what you need to do:

Create a visitor segmentation on your analytics tool

You need to understand what makes your traffic qualified, and come up with a rule so you can bucket those visitors into this segment.

Define a time frame for your data

This is important, because you'll be able to gauge your qualified traffic's trend against different seasons, marketing efforts, etc. The trend in both raw values of your qualified traffic and percentage of qualified traffic against different time frame will give you a well rounded understanding to the traffic trends.

Take the ratio between qualified visitors to overall site visitors

This is pretty straight forward... Not sure why I even highlighted this section...

So eventually, if you successfully segmented your traffic and capture all the necessary data, you'll be able to arrive to a chart like this. (This chart is based on some random data made up by myself)

In this case, it looks like the site acquired higher qualfied traffic around summer. Setting up a benchmark around overall average would be great start to see if the site is acquiring qualified traffic during a specific month.

Also if you can call out the marketing initiatives, you could probably contribute your efforts against the acquisition of your qualified traffic as well.

So this was a quick and simple method to gauge and assess your site visitors who falls under your rule of "Qualified Visitors". If you have any other ideas to obtain such insights, please feel free to share that with me.

I would like to say thanks to those who completed the 4Q Iperceptions survey that I've implemented on this site in August '08.

So far, there were 27 users who have completed the survey that asked:

1. Based on today's visit, how would you rate your site experience overall?

2. Which of the following best describes the primary purpose of your visit?

3. Were you able to complete the purpose of your visit today?

4. What do you value most about the [company] website? (asked when answered yes on Q3)

5. Please tell us why you were not able to fully complete the purpose of your visit today? (asked when answered yes on Q3)

The results that came out this survey was very insightful and powerful. I was able to get better insight to the qualitative aspect on how this site is performing beyond numbers from Google Analytics.

Here is what I felt after using this wonderful tool.

1) I was glad to see the overall satisfaction score in the Green. Fu~.

2) Avinash is right, there are people out there who care, and are willing to give feedbacks.

3) User comments were a bit hard to find, because you need to click on the underlined %s, but it was one of the most powerful part of this survey, which is hearing users' raw comments. (I recommend downloading the csv file to see the comments in better view)

4) I've learned that my readers were happy with the content on my site, but it seems like a lot of them are looking for research related content. I guess I need to be more conscious about that aspect of needs, and potentially share more data centrics research. I'll do my best!!

5) I was surprise to find quite a few users selecting "Ask an expert" for their primary purpose of visit, but I have to say my site is not doing well in providing a clear communication path to myself (I only get few direct contact...).

6) Although we can set the survey's invitation rate, it'll be nice to have a setting so that the survey (participate in survey yes/no) would show up after a user visit the second page. This probably has to do with usability more than any other reason.

7) One thing I would recommend is to increase the time range of downloadable CSV file. Since we're able to select 7days to 6 months worth of data in the report, it'll be nice to have an option to download 6months worth of data in one CSV file as well.

Overall, I am very happy with this service, I think the implementation was strait forward (copy and paste the javascript code), and it was very simple to get an insight to your user satisfaction score including their comments. I highly recommend this service to anyone who is running a site or blog, and obtain an eye opening results.

Note: You can control the rate of invitation, and control the looks of the survey as well.

Here is the actual visual of my 4Q Iperceptions result:

It has been a while since the web has evolved as a strategic business channel. Websites are viewed by the organizations as the key revenue driver and the most efficient way of attracting and retaining customers. Studies have shown that online retailing will grow over the years and a large percentage of the online retailers will be profitable regardless of the retail category. Thus, the emergence of the web as an integrated business channel has increased the significance of Web Analytics. Through the tool of Web Analytics, we can increase the online e business revenue. It is useful for all types of websites, especially E-commerce sites. The goal of the e-commerce sites is to buy some good or services online.

Companies that have online business and offline business can use web analytics as a tool to integrate both types of business. Web Analytics applications can also help companies to measure the results of their traditional print advertising campaigns. It does not make sense to spend money on offline advertising without knowing the percentage of return we get as a result of our advertisement campaigns. For all those who were worried about how to track your offline business campaigns, here is the right solution. Web Analytics will help you out of this situation. We can measure and analyze the effect of our advertisement through Web Analytics. Here are certain ways to increase your revenue by integrating both online and offline business.

The key to integrate online and offline business is tracking your offline campaigns through link tagging. You can measure the offline advertising success exactly the same way as you measure online advertising success through this method. For this, you have to tag the links in your offline ads with the campaign variables used by your web analytics tool. For link tagging you need not put some archaic URL in your offline advertisements. You have to put some simple easy to remember URL in your offline advertisement. The best practice is to create a custom URL or a custom landing page. It will work better than attaching the campaign variables to the URL that you place in your offline advertisements.

When a customer looks for the advertised custom URL or custom landing page, then you should do a page redirect. It will help in tracking the variables. This process helps you to tag your offline campaigns like your online campaigns. In the same web analytics report now, you will be able to view the traffic and conversion for both of your online and offline campaigns. An important thing to note here is that if you publicize your custom URL in other places, then you will end up in driving the traffic that was not generated from your offline campaign. This will naturally reduce the results you want to get.

Example
You can use a friendly URL that is easy to remember http://www.xyz.com/promo, and use a redirect to output a URL with query parameters that are consumable by your analytics tool. Here is an article containing some examples to track campaign through Google analytics.

Web analytics reports help you to know whether your campaign has worked out or not. It will help you to analyze the major pitfalls and will give you a clear idea of how to improve your business, both offline and online. The greatest advantage here is that the steps taken by you will be entirely based on practical data and not mere guesswork.

Custom URLs are also known as vanity URLs or friendly URLs. They are catchy versions of the old, long, boring URL, which makes it easy for the customers to remember. It is the user-friendly version. You can make use of the help of Google URL builder to set up such URLs. It is useful when you have specific offers for your visitors. Unique URLs will lead to the specific landing page that has the offer.

The next best practice for integrating your offline and online business is to use redirects. It is a way to point URL A to URL B. The best method of redirect is using a "301 redirect". All that the redirect tends to say is that the page you are looking for at the URL A is at the URL B. 301 redirects are heavily used in SEO to make sure that when you rename your URL doesn't affect your page ranking in search engines.

From the market level view of your Web Analytics reporting you can infer whether your particular ad is affecting a particular market. It means that your products are better selling in those markets if they have a high correlation of website metrics .You can improve your business in other less performing markets by changing your marketing strategy according to your web analytics report.

It is also a best practice to run an ad words campaign alongside with your offline campaigns in order to capture the customers who search online in reference to your offline ad. Include keywords in your ad words campaign like the themes or phrases used in your offline ad. This will definitely increase ways to integrate and promote your site through offline channels.

Analysis and insights based on web analytics, are much more than just providing numbers. To get a broader view on web analytics, traditional practice of web analytics has grown beyond analyzing log file data and provide metrics (unique visitors, page views, referrals, etc.) to segmenting visitors, measure engagement, execute A/B or multivariate test, and optimize.

With so much more metrics, analysts are able to dig into the data and provide deeper insights and recommendations. Apart from behavior analysis, today's interest goes beyond what visitors have done on the site, but answering the question of user satisfaction becomes even more prominent.

Traditional method to answer such question is to conduct a survey. Surveys are extremely valuable as users are willing to share their opinions about your site, service, products, etc.
Surveys could be highly intrusive, and you definitely don't want to bother your site visitors with short attention span.

Reading Avinash's blog, I've learned that he has collaborated with iPerception, and introduced 4Q which is a free survey solution that provides a simple scorecard on how happy your site visitors are. It is based on four key questions that are critical in surveying the satisfaction of your users.

1. How satisfied are my visitors?
2. What are my visitors at my website to do? In other words, what is the purpose of your visit to the site.
3. Are they completing what they set out to do?
4. If not, why not? If yes, what did they like best about the visit to the site?

What I like about this survey is that it is customizable. You can change the logo, selections of questions, adjust survey invitation rate, etc.

When visit session ends on the site and you get some kind of survey request, feel free to enter it (Yes!, on Zoommetrix.com!). It is coming up because I'm trying it out. If I get any insights, I'll definitely revisit this post and notify my findings. (I'll also give my feedback to Avinash as well)

Related Links:
How to Measure Customer Satisfaction with Web Analytics

4Q by Avinash Kaushik + iPerception

When analyzing a site, you may be segmenting your site traffic according to its sources. Looking at new vs. returning visitors and segmenting its metrics will give you great insights to which type of visitors are more engaged with your site.

Google Analytics has a powerful segmentation feature that allows you to slice and dice new and returning visitors in various ways. Some of the options are Visits, Pages/Visit, Avg. Time on Site, Goal Conversions, Conversion Rate, Bounce Rate, % New Visits, and Per Visit Goal Values.

Here is an example screen shot of what it can tell you when you take your visitor type and slice it into several metrics.

I like this because in this example, it shows me that this site's returning visitors are highly engaged in terms of page views per visit, avg. time on site, and bounce rate. Assuming this is a blog site, it totally makes sense because returning visitors are probably your core users/readers.

Within this specific time frame that the data is pulled, the new visitors may have not converted to returning visitors yet. So additional metrics you would want to look at is the "recency" metrics, to see how long it took for new visitor to become a returning visitor.

When you have high percentage of new visitors and recency of 0 day, that means your site is not doing well in acquiring returning visitors. In that case, there are various communication methods you may consider to acquire returning traffic. Such as, newsletters, SEM, Direct Mailing, etc.

I've picked up an interesting article from Fortune Magazine regarding what makes Google News worth so much to Google when there are no ads.

Basically, free products offered from Google helps driving traffic to their search, and tie users into a broader Google ecosystem. This is a similar concept to creating micro sites for any web sites out there trying to market their site, products, or services.

The great question that comes out of this is, how valuable is that micro site or sites that refer traffic to your site? Is it the level of traffic that refers to the site for increased exposure and awareness, or is it the conversion and quality of traffic that is brought to your site?

What makes Google's model so great is that, each site connects in a form of "relevancy". Google News is relevant to Google search because people who read a news article may get more curious about certain topics or content, and they'll go off searching (likely through Google).

Same logic may work for you site, when you're trying to leverage referrals from others. So in order to maximize the value of referring traffic to your site, you need to understand if you're acquiring the right kind of users. Knowing the content you serve through your web site, are there any gaps between the interest of the users, and the relevancy between the other sites and your site?

It becomes more critical to understand this, especially if your visitors are bouncing away or even paying for that traffic acquisition (money going out). When you test your metrics through analytics, look at the key metrics (page / visits, bounce rate, conversions, etc.) by referring domains. Search engines aren't the only traffic acquisition method, and quality referrals from other sites could produce valuable outcome. It can broaden your site's ecosystem.

NOTE:
Obviously, there is really not much you can control when people are linking to you site on their own will, but assessing and optimizing the referrals could be done if it's within the reach of your control like:

- Micro sites
- adjusting content
- adding content
- buying ads on other sites

According to Jakob Nielsen (usability guru), web users are getting more selfish, and leaving a site quickly. Apparently, there are two reasons to this.

1) Site designs have become better, but users have become accustomed to the online environment.

2) Improvements in search engines are taking users directly to a page or destination inside a site. In 2004, about 40% of people visited a homepage and then drilled down to other pages, but in 2008, only 25% of people travel via homepage.

You've probably heard this over and over, but every sites are unique in different ways. So from web analytics stand point, it is always recommended to test. Test, Test, Test!!

Following processes and metrics should help you gauge user engagements from search.

- Learn your analytics software, and segment your users by organic and paid search. Gauge the % referrals from these sources.
- Evaluate the exits, bounce rates, entry pages, etc. Compare these with visitors from search against traffic from other sources.
- Test against different site versions and different timeframe. Your research and optimization will give you valuable learnings. You can find out if Dr Nielsen is right or not.

Original article from BBC
http://news.bbc.co.uk/2/hi/technology/7417496.stm

Unlike transactional websites, non-transactional websites don't have transactions on the site making it difficult to understand the value of the goal. Conversions for non-transactional websites could be anything from consumer registrations, newsletter sign-up, survey answered, etc.

I guess every analysts have their own way on deriving the formula and $$$ values for this. Maybe understanding the following points would make it clearer to derive the value. Note that the value of the goal discussed here is the $$$ value to be assigned to the conversion that occurs on the site.

1. Understand the action required to achieve the goal
Is it the "Contact Me" goal? or "Sign Up" goal? Understand what it is you're trying to associate to the goal.

2. Evaluate how often the visitors who reach the goal become customers
Come up with the percentage that you can use to associate with that conversion and closing the ultimate goal. Example, out of those people who converted (registered, sign-up, contacted, etc.) on the site, what percentage of those people you can convert to sales. (if not sales, then possible alternatives could be "reach back", "become a partner", "send e-mail/mail back", etc.)

3. Assign $$$ value to each of that conversion after accomplishing the site goal
Determine the average transaction of that sale mentioned in (2). Once again, if not sales, what do you think that value is to be able to "reach back", "become a partner", "able to send e-mail/mail back", etc.

4. Derive the value
Multiply (2) by (3). For example, 10% of people who printed the coupon online (site goal), and your average transaction of that coupon after redemption at market is $10, then $1 would be the value of the goal for "printed the coupon" on your non-transactional website.

Another example, 10% of the people who registered to the site came back later to login, and download a pdf document that probably would worth $5, you could assign $0.50 to the "website registration" goal.

I hope this helped you to start thinking about trying to assign $$$ to your non-transactional site conversions and able to accomplish better decisions to your site optimization.

High bounce rate is an indication that your site is not providing the value visitors were expected, resulting in single access to a page and leaving the site. Web analyst would always say to lower the bounce rate, and some would say to aim less than 50%.

I've always noticed that blog contents tend to have a higher bounce rate than contents that tends to be static (typical non-blog like pages or sections). In my wife's blog/site, I noticed that bounce rate was much higher than her static contents.

Insights
I've segmented the blog section and the static section (main section describing about her site, profile, etc.) by new visitors and returning visitors.

I came to notice that types of visitors were pretty much equally split (50-50) in terms of new and returning visitors for both sections. Looking at the bounce rate broken down by new and returning visitors across those two sections.

- The bounce rate for the new visitors in blog section was 120% higher than the returning visitors in the blog section.

- The bounce rate for the new visitors in the static section was 40% higher than the returning visitors in the static section.

The bounce rate for new visitors would most likely be higher than the returning visitors. The learning is that the new visitors for blog section/site, the bounce rate tends to be higher.

Possible Reasons
1) Users reading the blog tends to read and leave and probably come back to read again on other time. Good metrics to use to analyze this are the recency and loyalty metrics.

2) Visitor sources for these two section may vary and stickiness for the source to content sections trending differently.

3) Expectation of visitors when entering the blog section and static section may vary. Possibly due to typical difference in designs, navigations, ads, etc.

I hope this would help you in finding the next step in the analysis of the bounces. Don't give in lowering that bounces!

According to Google Analytics help, Bounce rate is the percentage of single-page visits (i.e. visits in which the person left your site from the entrance page). Bounce rate is a measure of visit quality and a high bounce rate generally indicates that site entrance (landing) pages aren't relevant to your visitors.

Bounce rate can be calculated from site level and individual page level.

Individual Page Level: Bounce rate is the ratio of visitors who enter the site from that page and leave without going any deeper, to the total number of visitors who enter the site through that page. Basically, it is single page visits / total entries to the site through that page.

Site Level: Bounce rate is calculated as single page visits / total site visits.

The question typically asked is what is the industry standard of bounce rate? I would say it would depends on the site, industry, the mix of media and campaign that is running, how that landing page is served, etc.

According to a suvey studies, following are the min and max of the bounce rate for certain categories.

eCommerce: Min 14.3%; Max 68.0%
Product Information: Min 3.2%; Max 50.0%
Lead Generation: Min 5.2%; Max 81.0%
News/Media: Min 25.0%; 81.4%
Branding: Min 22.0%; Max 70.1%
Other: Min 13.0%; Max 85.0%

Additionally, you should be thinking about the types of campaing running at that time of measuring the bounce rate, too. Typically, PPC campaigns have higher bounce rate than traffic from organic search. Therefore, making sure that your campaign's landing page are optimized and customized to address the bounce rate issues are important.

Bottom line, keep your bounce rates low as possible.
- Start off by making a goal to reduce worst pages below 60% and aim below 50%.
- Look at your highest converting path, are the bounce rates low for those entry pages?
- Optimize your landing pages if possible. Look into the keywords that brought traffic to the entyr pages.

Following screen shot is an example from Google Analytics, it could be a good point to start off your analysis to give you insights to landing pages and bouce rates.

One of the metric I like to monitor in Google Analytics is segmenting the keywords user searched to enter the site, sort the data by visits, and break it down by pages per visit.

This is a great view to show what keywords visitors are using to come to the site and understand which keywords generate traffic. Additionally, the pages per visit will show you if your content provided to those visitors who used the keywords to enter the site, generated interests to view other pages.

Following image shows the output from one of the site I personally manage.

For Example
Let's say visitors that came to the site with a phrase "Visitor Behavior by Keyword", and it was the most popular keyword yielding 1,000 visits. However, if the pages per visit was only 1 page, that is not really a good result, especially if the site is encouraging visitors to read various contents.

Then you might want to use this as a starting point to observe what the entry pages are for this phrase, and evaluate the bounce rate on the entry pages. With this analysis, you might come to learn the issues on those landing pages causing visitors to bounce.

One of the most important aspect of web analytics is to measure traffic sources to the site.

Then traffic sources can be broken down in to two types of visitors; new and returning visitors. Is it important to segment your site traffic by the acquisition sources and majority of the site analytics tools should be able to breakdown the new and returning visitors within the reporting timeframe.

Once you're able to determine the contribution by the sources, understand how prominent those sources and the site is attracting returning visitors, you should be able to make a smarter decision in allocating your money for traffic acquisition.

Following figure shows the new and returning visitors broken down by the acquisition sources.

The number of visitors is a vague metric when it comes to understanding if your site visitors are qualified or not. Since not all visitors are created equal, how do we determine if your site is getting a qualified traffic to your web site?

The answer will be determined by what you consider as success within your web site's goal. In this entry, I would like to look into this by approaching the non-transactional site. Note that unlike transactional site, a lot of the focus to depict qualified visitors for non-transactional sites would be to focus on the process rather than the actual metrics applied.

Non-Transactional Site
In non-transactional sites, it is not that easy when you are trying to depict the qualified visitors. Since in non-transactional sites, visitors aren't required to complete any transaction, therefore, analyst won't be able assign dollar amount to metrics to determine if the visitors were qualified or not. High-level breakdown of point of interests to determine types of qualified visitors in non-transactional web sites would be listed below.

The number of visitors is a vague metric when it comes to understanding if your site visitors are qualified or not. Since not all visitors are created equal, how do we determine if your site is getting a qualified traffic to your web site?

The answer will be determined by what you consider as success within your web site's goal. In this entry, I would like to look into this by approaching from transactional site.
Non-transactional site will be posted shortly in near future.

Transactional Site
In transactional sites, qualified visitors are easy to depict, and easy to analyze the qualified visitors. Since assigning dollar value to your metrics can be done easily, analyst can work within that context of qualified visitors better than non-transactional site. Such example would be assigning your revenue or costs to your KPI's and analyze your ROI. In this entry we are more interested in determining qualified visitors from higher level.

High-level breakdown for you to determine different types of qualified visitors in transactional web sites would be listed below. It will allow you to understand your visitors so that you can allocate your time, budget, and set up strategies to shift your visitors into visitors who convert.

There are huge difference in measuring transactional website and non-transactional site. Transactional website involves hard dollar signs attached to the web metrics. The conversions are pretty straight forward since you can directly link revenues or number of items sold to web metrics to make actionable decisions. However, in non-transactional website, there are many challenges in defining what is good visitors behavior.

Through the use of web analytics, you can benefit from the process of collecting, collating, and analyzing a website's activity. Web analytics measures what aspects of a website are working succesfully towards a particular business objective.

There are many visitor data that could be collected. Such data are "Page View", "HIT", "Visit", "Unique visitor", "Repeat Visitor", "New Visitor", etc. These metrics can be used to extrapolate some very complex behaviors.

Analytics solutions would utilize the collected data to measure if a predefined action is fulfilled by a visitor. Sush fulfillment by a visitor is called "Conversion". Conversions can be defined in various way depending on your website's objective. Typical conversion would be:
Visitors convert to paying customers
Visitors signing up for newsletter
Downloading a white paper
Have certain amount of impression for a web page
Register for updates

Understanding the website traffic data would be the key to understanding your visitor behavior, and eventually helps an ecommerce owner to improve their online business.