In this post, let us learn how to create different types of filters.

Excluding internal IPs:

Whenever Google analytics is implemented we start getting data after a minimum wait of 48 hours (if implemented properly). That data comprises of all the visits from external customers, prospective customers, clients and internal customers, as well. The data which appears on the dashboard would be the summation of all the visits from everyone. In order to segregate the internal customers/employees’ data from the main data, filters are created in Google Analytics profile. One of the best practices is to exclude the internal IPs at the time of creating the profile so that visits from internal IP addresses are excluded to provide the correct data from the very beginning.

 The process for creating the filter which excludes the traffic from internal IPs is as follows:

 -First of all, whenever we create any filter, always keep the unfiltered profile to check the accuracy of the filtered profile. Create another profile with the same domain and name it in such a way that if someone else is using that account, they would be able to make out that this profile contains the filters to exclude internal IPs.

 -Once the new profile is created, go to the filters and chose “Add new filter” for profile. Choose the name for the profile and in the next row select “Exclude traffic from an IP address”.

-Once that is done, provide the IP for the all the office space with the help of Regex and then save. Now the data will be filtered and will not contain any visits from internal IPs.

Filters for different sections of the website:

Sometimes, we might have a particular section in the website that is going through some changes which may affect the visits and other behavior on that section. It is also possible that we want to give user access to some other agency which is trying to bring some changes in the website. A default profile in Google Analytics will contain the data for the whole website along with the data for that particular section. In order to maintain the security of the data that is not going to be used by some third party, filters are used.

To do this, a different profile can be created in such a way that profile contains the data for that particular section of the website and stops the data coming in from the rest of the website.

 The process for this is as follows:

 -Go to the “Create filter section” of the profile and chose “Add new filter” for profile.

Filters to stop the data coming from unknown website to your account:

The other day, I was really shocked when I saw a new category in the event section of my website. I tried to remember if I had actually created this kind of event for the website, but could not recollect doing anything like that. Then, I clicked on it to see from which page that particular event was being fired. I copied that URL to the browser and got the biggest shock of the day! That page didn’t belong to the website I was analyzing. It belonged to some other website which is nowhere related to our website.

Given below is the process which I followed to exclude such traffic from unknown sources to my website’s GA profile:

-Go to “Create filter” and chose “Add new filter for profile”. Then give the name of the filter and select the “Custom Filter” from the two options.

-After this, select the “Exclude” option. Then select hostname in filter field and give the host name (with the use of regex) in filter pattern option. And then select “No” for case sensitive. This way any spam data can be stopped from coming in our Google analytics account.

Hope this information will help you set up profiles and filter data according to your needs. All the very best!

There are many types of errors that can happen, but not all of them can be traced with the help of typical web measurement tools alone. Here are a handful of the most common ones that can be tracked:

Website is slow or fails to respond

There are services that specialize in website monitoring and are designed to monitor websites regularly to ensure that they are accessible and the web servers are handling page requests on time. You can setup alerts for reporting errors. Typical web measurement tools usually do not provide adequate support for measuring these aspects, but it is possible to integrate response and availability into your web measurement application to provide a more holistic view of the situation.

Broken Hyperlinks

The most important things to monitor are Broken Hyperlinks. The broken link report should be run every day to look for problems on the website. Sometimes the problem might be from your end and can be easily corrected. Other times, the links might be coming from another site. In this case you can either write to the site owner, asking them to correct the link or put a redirect in place of the broken link, designed to push the visitor along to the right page.

Aborted page views and downloads

Tracking abandoned and interrupted downloads is more difficult than tracking HTTP errors. It requires using web server log files for your data collection because page tags can capture neither incomplete downloads nor the download time. The Microsoft IIS webserver records a server status code of 64 when a request is terminated. Some web measurement tools supply such plug-ins and can track page abandonment rates and incomplete downloads.

Client-side script errors

One of the most frustrating types of errors visitors encounter are Script Errors, the type that prevent links from working, forms from being submitted and result in an overall poor user experience. While difficult to actively measure, creating a strategy for measuring this type of error can explain a great deal about why visitors fail to move from page to page on a site.

It is essential to track errors on site and act upon the data you generate. Nothing is more frustrating to a web visitor than an error message, especially when it is well within your power to prevent and correct problems.

If you want to know how to measure these type of errors, then go ahead and read the blog “Tackle those Website errors”

To answer this question, let me put forward few of the advantages I have had using this amazing tool.

Omniture SiteCatalyst Report Builder from Adobe is called an ‘Intuitive tool’ for a reason.

-Even though both ExcelClient and Report Builder do the same kind of work, ExcelClient fails when the data table that needs to be pulled out is huge.

-Report Builder is a must have addin to your excel if you are using Omniture SiteCatalyst as its features are completely customizable in all aspects, say selecting options or linking it to the Excel Cell.

-All the reports that can be seen on SiteCatalyst UI can be obtained from Omniture SiteCatalyst Report Builder except the fallout report. And most importantly the report can be scheduled by automatically updating the data before delivery.

So now let’s learn how to create or rather convert, your existing ExcelClient template to Report Builder format.

Please follow the process given below:

Step-1 Open the already created ExcelClient Template.

Step-2 Once the file is opened; you will get the following window.

So here you go, now you have your ExcelClient Template converted to Report Builder. As simple as that!!!!

Depending on whether you are using web server log files or page tags for collecting traffic data, there are different methods to capture errors:

1. Using log files as a data source

Web server log files record page requests with errors and successful page requests in the same way. But you can find out the difference by seeing the HTTP status code that is recorded along with the request in the log file.

Some of the most frequent HTTP protocol status codes are:

200 – Successful hit; the request was fulfilled

302 – Redirection. The data requested actually resides under a different URL

401 – Unauthorised request.

404 – The server has not found anything matching the given URL

503 – Service unavailable. The server is currently unable to handle the request

2. Using Page tags as a data source

Many hosted application vendors have custom error page codes that can be used to specifically capture errors, provided there is no specific JavaScript error on the page. This strategy usually requires that you have a custom error page (usually a 404 or “File Not Found” page that can be coded).

3. Client-Side JavaScript errors

Page tags cannot detect all types of errors directly because the problem does not by default trigger an event. Placing a page tag on a custom error page and passing the error message in a custom variable will record the incident for you and make the error information available to your reports.

One way to do this is to use page tags and error handlers in your scripts. For example, in JavaScript you can specify an ‘OnError’ handling function for your document. In OnError, you can send additional information via the page tag to a custom variable.

The following code can be used to build a list of client-side errors which can be passed to your web measurement page tag:

<SCRIPT>

‘Specify how JavaScript can handle any client-side errors’

Window.onerror = myOnError

‘Define arrays to capture the error messages’

msgArray =  new Array()

urlArray = new Array()

lnoArray = new Array ()

‘when an error is discovered, build an array of messages, urls and line numbers’

Function myOnError (msg, url, lno) {

msgArray[msgArray.length] = msg

urlArray[urlArray.length] = url

lnoArray[lnoArray.length] = lno

return true

}

‘Build a string that can be sent to the data collector’

Function sendErrors() {

Var ErrorList=””

For  (Var i=0; i < msgArray.length; i++) {

Errorlist = errorlist + urlArray[i] + ‘l’ + lnoArray[i] + ‘l’ + msgArray[i];

}

‘

‘Call to the page tag/data collector goes here!’

‘

}

</SCRIPT>

Depending then on how your particular web measurement application works, you’ll replace the ‘Call to the page tag/data collector goes here’ line with an image request (or whichever strategy your vendor recommends) that will send the string generated in the errorlist to a custom variable that can be examined later.

So here were some tips to deal with the most common types of errors. We hope this helped you. If you have any suggestions or want to share other types of error capturing techniques, please feel free to comment below.

If you are guessing that am going to tell you about the benefits of having a Facebook Fan page, then you are wrong. I’m sure all the enterprises already own a Facebook page and have a fair share of fans. They constantly update the page with status messages, photos and videos. The posts get tons of likes and comments. You are familiar with Facebook insights and must be doing a regular report about the volume of new fans, likes and comments etc.

But does this mean all your fans are constantly engaging with your page? Do you know what your fans like or dislike?

A simple way to answer all these questions is to run a multivariate test on all your posts. Multivariate Test is a process by which more than one component, that determines the success of a post, can be tested.

Before we start, determine the metric that will determine the success of your post. I strongly recommend that you use ‘Feedback rate’. Feedback rate is the number of comments and likes per impression. ‘Impression’ is the number of times your post has been seen on your wall and the news feeds of your fans.

A few parameters that you could consider to compare are:

1. Time: What is the time of the day that your posts get most visibility and engagement?

Pages like Starbucks and NYTimes would probably get a lot of fans that engage with their page in the morning whereas fan pages that let you book tickets online would get more engaged fans in the evening.

2. Day: Do your fans ignore all the messages posted on Monday because they are too involved in planning the week ahead or do they miss all your updates during the weekend since they are busy spending quality time with their family and friends offline?

3. Length of the post: Do your fans like your post when it is long or short? Determine the length of each post and plot them against your feedback rate and find out yourself!

4. Category: Which category of posts do your fans enjoy? To determine this, first you need to categorize your posts according to the theme of your post. Is your post about an announcement of an upcoming event, information about an exciting offer or is it update about upcoming features? What are these guys interested in hearing more about?

5. Demand response: This is the most important parameter that you should look at. Do your fans respond to the posts that demand response? The whole point of having a Facebook page is so that the company gets to know their fan base up-close. So first determine if your fans are responsive enough. Determine if they answer a question you’ve posted, upload a pic of them holding their favorite product of your brand, and participate in the contest that you organize. If they do not then there is some serious problem with the way you communicate your point.

You could have as many parameters you want that will help you determine the best way to engage your fans. Please note that there could be limitless combinations but defining the best way would help you reach your goals faster.

The actor in the ad, that I spoke about in the beginning, says “I’m always on Facebook! Where else would I be?”  Your fans are also always on Facebook, do your best to grab their attention!

Well the solution to this can be as simple as just closely monitoring your Google Analytics data. This data can help you lessen your expenses when you are bidding your keywords in Google Ad words.

Let me show you how this can be done:

1. Begin by logging in to your Google Analytics account.

2. Go to ‘Traffic Sources‘ and run the ‘Keywords Report‘. Since we are concentrating on reducing the PPC cost lets concentrate only on the Natural Keywords report.

3. Did you know that long keywords can reduce the cost you’re spending for PPC Ad’s?

Though long keywords are not ‘Branded Keywords’ directly, they are parametrically attached to the ‘number of visits to the site’ and ‘cost efficient’ and hence can be considered for bidding.

Now let me show you how this can be done, we all know how powerful REGEX is when used with Google Analytics. So use this RegEx to get the longest or Average length Keywords.

RegEx: ^s*[^s]+(s+[^s]+){3,4}s*$

So the above RegEx gives the results for keywords with words 3 to 5.

Example: “Google my list” or “Google my name list”.

4. Now I would be interested to have a look at Keywords with minimum 3 – 5 words.

If I am interested in keywords with 4-6 words then the RegEx will be ^s*[^s]+(s+[^s]+){4,6}s*$

Now, let’s see the result for keywords with 3-5 words in them.

Now all we have to do is to make the best choice about which keyword we must bid for more search engine traffic. And the keywords in the list clearly suggest that they are not going to cost more. Therefore, biding on these keywords can reduce your PPC cost.

To test the regular expression, you can go here.

So then, Enjoy Bidding!!!

But now this gap is almost filled by the introduction of QR codes, seen by most of us in magazines, newspapers, TV commercials etc.

QR code or “quick response” is the code which can be easily scanned by mobile devices and quickly direct the person to the required website. This code helps in accessing the resource instantly. This way we can measure how offline campaign is leading traffic to online platforms.

But how will we attribute the visits coming from QR code to a particular website? It is as simple as campaign analytics and be easily done using URL builder, provided by Google for Google analytics users.

Here are some steps which will help us track visitors through QR codes:

1. To make a QR code one has to provide a URL, which the visitor will visit after scanning the QR code.

2. Once the Landing URL is fixed, now it’s the time to append the query parameter to that particular URL. For this we’ll use the Google URL builder tool:

(In the above example, the QR code will be generated for webanalyticsindia.com)

Google URL builder will ask for the above shown fields to be filled. Fields like source, medium and campaign name are mandatory to fill.

Here the source will be Newspaper and the medium ‘QRcode’, hence the campaign name-‘WAI QRcode campaign’.

Once this is complete, the tool will provide the URL with query parameters.

3. This is the last step and here the URL created above has to be submitted to a QR code generator. This will create the Code which can be added to the offline campaigns. Some of the sites which can be used for generating the QR code are:

http://qrcode.kaywa.com/

http://goqr.me/

http://delivr.com/

(sample QR code)

Once the code is created and is printed in the newspaper, the data can be easily seen in the Google Analytics account of that particular site. It will be under the ‘Traffic Sources’ section under the name of ‘All Traffic Sources’.

On clicking the ‘All Traffic Sources’, the data can be selected on the basis of ‘Medium’ or ‘Source’ and hence the visits can be easily attributed to the QR code campaign.

It is as simple as that

At the end of each campaign, the stakeholders are drowned with reports from marketing, sales, merchandising and campaign managers. They are flooded with all kinds of metrics like CTR, CPC, visits, video views, photo uploads, discount coupon downloads, Facebook fans, Twitter mentions…. the metrics and reports are never ending and none of them tell you in plain simple language if your campaign was a hit or not!

‘Measurement plan is a document that states all the metrics that determine the success of a campaign.’ Simply put, a measurement plan acts as a target or even as a benchmark (if you have run similar programs in the past) for your campaign.

Here is an outline of what a measurement plan should ideally contain:

Overview of the campaign:

It is a good practice to include a brief overview of the campaign. Give your audience the benefit of doubt and include the purpose of the campaign and how it works. Digital agencies usually make a campaign management manual that can help you with this step. It could also include important dates and milestones of the campaign.

Visitor Flow:

To measure the success of a campaign you need to determine the action taken by the visitor or consumer that is intended or anticipated. It should include all the steps that the visitor would follow, right from the source to the goal. This helps determine the stage where there were maximum drop offs and accordingly fix the problem.

Tracking Methods:

You’ve defined the flow of the visitor, but how can you determine the drop off without measuring each stage effectively? Determine all the tools and tracking mechanisms that you would use: Google Analytics tags, email vendor tracking, Dart tags etc.

Indicative Metrics:

Determine the metrics that would indicate if a process is not working to your advantage. E.g. click through rate, email open rate, CPC etc. If you are spending a lot of dough on a display advertisement and the CTR is very low, you would know that something somewhere is wrong. You could then check if the banners are delivered properly or see if the page you’ve chosen to advertise isn’t very popular and then apply fixes.

Success Metrics:

These are the metrics that determine the success of your campaign: ROI, conversion rate etc. It is important to have an agreement beforehand with the stakeholders and clients about these metrics.

Frequency of Reporting:

Decide the frequency and the layout of reporting to keep everyone updated about the progress of the campaign. You could decide on daily snapshots, weekly highlights report and detailed monthly reports, before the final wrap up depending on the duration of the campaign.

These are the key components which need to be put in place before we roll out a Measurement Plan. We hope it will be helpful for you. If you think there can be more, please do share with us by leaving a comment below.

I am sure this question would have crossed through many of our minds too. Due to several reasons, data collected by javascript and cookie creation cannot be 100% correct. There can be many possibilities here.

Before knowing this let’s clear up on some basics:

-What is Google AdWords Conversion Tracking and how it works?

Google AdWords Conversion Tracking is a block of javascript code that is placed on a page of your website where you want your visitors to ultimately land. This can be a “Thank You” page that a visitor sees after they fill out an inquiry form, or a “Receipt” page that a visitor sees after they buy something from your Online Store. When a visitor lands on a page with Conversion Tracking, a cookie is placed on the visitor’s computer and data is sent to a Google AdWords server, registering this conversion and then assigning the credit for the conversion to the proper keyword, ad, ad group, and campaign.

-What is a Goal in Google Analytics and how it works?

A Goal in Google Analytics occurs when someone visits a page that has been defined as a Conversion Goal in a Google Analytics profile. The idea behind which page(s) to select as a Goal in GA is identical to choosing which page to place AdWords Conversion Code on. Google Analytics also requires its regular tracking code to be present on that page in order to record a Goal Conversion. Upon entering your website, up to five cookies are set on a visitor’s computer, whether they reach your Goal Conversion page or not. GA takes the number of visits to your Goal Conversion page(s), and simply does the match throughout its reports.

Now let’s get back to the question of why AdWords and Analytics Conversion numbers differ?

Following are some reasons:

-Cookie Deletion / Cookie Blocking Habits:

Depending on a user’s browser settings, they may be blocking the AdWords Conversion tracking cookie and not blocking the Google Analytics cookies, or vice-versa. One of the major differences between AdWords and Google Analytics is that AdWords cookies last for 30 days where as Analytics cookies last for 6 months to 2 years! This of course means that if a visitor converted 31 days after clicking on an AdWords ad, the conversion won’t be reported in AdWords but will be counted in Google Analytics.

This presents itself as an issue for companies that tend to have a long purchase cycle with people taking longer to consider their buying decisions. In case of Invalid Clicks, the goals that are reported in Google Analytics may be filtered out when they are imported into your AdWords account. This is due to Google’s Invalid Clicks Technology.

-Script Location on Conversion Page:

Because these are two different scripts, there is a possibility that one script will “execute before the other script has a chance to execute. This usually happens before a user closes their browser or leaves the page.

-Different Servers:
The Server that processes AdWords Conversion tracking is a different server from the one that processes Google Analytics data. So, much like the case with Script Location, one server may have finished receiving information but another server may have not finished receiving information before a user leaves the website or closes their browser.

-Certain Google Partner Websites:

Some of Google’s Search Partner websites (where your ads may appear) cannot have their conversions tracked with the AdWords Conversion tracking script. However, if you’ve coded your URLs for Google Analytics, you will still see a Conversion for “google / cpc”.

-AdWords credits conversions for clicks (Conversions: 1-per-click) whereas Google Analytics credits them as visits:

Google AdWords tracks ‘first touch’, if a user searches for a query and clicks on your PPC advert to go to your website but does not purchase at that moment and returns after a week, AdWords will register the conversion back on the first date and attribute the sale to AdWords.

Analytics on the other hand tracks ‘last touch’, which means that if a user were to perform a search, click an ad, visit the website, leave, then come back a week later, Analytics would attribute that search to organic or other sources, unless they did a search and clicked on that ad again.

This will not be a problem if the majority of visitors placed an order on the first visit, but if you have many visitors who order at a later date, this can present an issue and a big discrepancy can arise between the two tracking systems.

So these were some of the reasons why it’s almost impossible that Adwords conversions and Analytics Conversions will match. As for the answer to the question “Which one is correct?” The answer here is both of them. There is no concrete answer or rectification method available. Both AdWords and Analytics data is considered 100% accurate!

So here was our take on this query. If you have any views about these questions, please do share with us!

Most of the analytics tools give us the data we require, but consuming it on Excel is even better.

Omniture Excel Client helps you get your data on to your Excel sheets by a click of a button. Yes, it’s one powerful Excel addin which can pull data from SiteCatalyst on to your Excel.

What’s the benefit of this? You can access your data just by building data set blocks for one time and use it whenever you want by just refreshing the data set. Also, you can have direct interaction which means you need not edit the data block to change any filters.

So how do you make your Data Blocks dynamic?

1. Have all the data feeds for input predefined on the excel sheet, this helps us to use the tool effectively and enhance the dynamics.

2. Once you have all the required inputs for your Dashboard, start building the Data Blocks.

Follow the steps given below:

Step-1. Select the Report Suite

Step-2. Select the report you want to view, define the metrics and set the date range for the data

How to set a ‘Date Range’

Step-3.  Now we are at the final step to view our data. Just give a name to your data block and insert it into a Worksheet

You just need to wait till the Query is executed and you’re done! This is how the report will look, based on your request

Some pointers about using Excel Client

You can change the report dynamically by changing the predefined filters and Date Range, once you have changed the necessary input feeds. You can click on either “Refresh Worksheet” or “Refresh All”.

Refresh Worksheet: This refreshes all the requests on the Active worksheet.

Refresh All: This refreshes all the requests on the Workbook.

One major disadvantage in using Excel Client is timeout. This happens when the request is too huge or large amount of data needs to be pulled into the Excel.

Do you think this will wreck your process, no not at all? The Timeout Error occurs only when we try building it in our Environment. So why don’t we build the request within SiteCatalyst and have it mailed to us. Interesting isn’t it?

Let see how this can be done.

After you have logged-in to your Excel Client you will have many options to play around with. Let’s concentrate on “Publish”

Once you click on the ‘Publish’ button the following screen appears:

Now click on the ‘Send’ button. Within seconds the report will reach your mailbox without any problem!