- Are you working in an agency and have lot of clients to handle?

- Are you marketer who has to keep optimizing pages for better conversions?

- Are you a designer who doesn't know user behavior but wants to design a page with that stickiness factor?

Then here is a list of check you should always use. A list of rapid checks on a landing page, which you can do within 60 seconds, and can give your opinion about it. There are more checks than these, which you can do later. But these are some checks you shouldn’t proceed further without, and you can do it really fast! We call it The 60/6 Check. The 6 checks you can do in 60 seconds.

Here we go!

1. Tagline

Tagline is the most important thing to explain the business in fractions of a second. A good Tagline will explain the business to a first time visitor in a snap!

Example:

Learn, Share, Improve your conversions today. Anyone would know what is it talking about. ABtests.com is a website where you can see uploaded A/B test on website pages, Share your own tests and Learn from it. Is there any simpler way to convey this?

Check – It should be crisp, and simple to understand. Explain the business in one liner.

2. Headline

The Headline is related to a particular page of a site. How a headline differs to a page from Tagline is, The Tagline talks about the entire website as a product, while the Headline has to explain the Purpose of a particular page. Especially, for a Lead generation page, or a Download page, sometimes, a Headline change can boost the Conversion rate by unbelievable amount.

Example:

This is the page for Apple store on the apple.com website. The Headline here is self-explanatory and explains the purpose of the page very nicely. Just waiting for my Paycheck to use this page.

Check – It should explain the purpose of the page in the simplest manner, and should encourage the user to do the desired activity, e.g. fill a form or download an App.

3. Call to action

The call to action is the most important feature of the page. After all, you want your user to do something, which is always supported by the Call to action. Again, a call to action can do dramatic changes to a page.

Example:

Flickr.com – Check out the call to action here. Big button hitting in the eye! You got to see that before anything else. The Button color is very light, but the solid color text inside stands out.

Check – The Call to action has to be always on the 1^st scroll. It has to be the most prominent among other features of the page. If there is more than 1 Call to actions, there should be one important call to action, which has to stand out among other. So many options always confuse the user. The text on the button has to be simple and short. There has to be a contrast between Button color and the Text color.

4. Background vs Text

The Background and text have always had to be each other’s enemy. Their colors can never meet. Normally, A background is always in a light color, and the text on it in a solid color. But still people opposite experiments sometimes which turn out to be good.

Example:

I didn’t want to take an example of a normal landing page with Light background and Solid color. Here’s a non-traditional page. It’s complete opposite to the normal, Solid Background with Light colored text. Still, some friends might feel that this page will look better in white background.

Check – Check the contrast between the two. The text always has to be easily readable without any extra effort.

5. Main communication

By Main communication, I don’t mean the copy of entire page, but the main communication about the product or the site. E.g, About us. This communication has to be like a woman’s skirt. Long enough to cover the essentials, and short enough to look interesting! It has to extend the Headline communication and explain the purpose of the page

Example:

The Firefox Homepage!, They have used this page to communicate how you can customize Firefox. The main text below the Headline Clearly extends the Headline.

Check – If there’s a headline, then the main communication has to extend it. If the text is too much, then it has to be broken down in points.

6. What’s in it for me factor

Any page has to answer this question, many sites end up boasting about themselves. E.g., You should by our product because we just won an award. But what about their customers? Talk about what are they getting from buying your product or services, and why would they buy them, What’s in it from them?

Example:

Hoot Suite is a famous Social Networking Client. If you see the page, their boasting gets completed in a one liner. Below are the features, the what’s in it for me factor.

Check – The page should answer one question. What’s in it for me?

The most important - How to perform this Check in 60 Seconds?

Now, once we know the importance of all checks and what to check for, We have to start checking it for pages in 60 seconds. Here’s how!

Create a Checklist as below

Once, The Table is ready, then start your check. Go through the landing page you want to check, and Start giving ratings for all the Checkpoints above. Give ratings from 1 to 5. 60 seconds over!

Now, since you the check is over, add one more column for comments, as below.

Fill the comments column as above, and you ready ready with a list of things you want to change, simple!

Please note one thing, if the user gets lost on your page, or get confused between too many options, he’ll always decide to leave the page. Would you buy from a Shopping mall that sells all the items from Electronics to Vegetables on the same shelf? This check will point out all the problems because of which the user gets lost in the all in one Shopping mall.

This post post aims to develop an understanding of how to calculate product specific conversion rate & discuss the potential analysis & insights can be generated from it.

Quite often the business problem or questions that most ecommerce website encounters is very specific to product management as to how much product to stock, which are fast moving ? how can I move some of the product quickly etc.

How to measure how many views different products have received & whether those views are turning into transaction & revenue? What actions can I take based on such data?

What is product conversion rate?

There are many ways to define what we can call the product conversion rate. For example you can check # transaction for any given product divided by # of visits to that specific product. Moreover, you can also use quantity to # of visits ratio to calculate the product conversion rate.

In omniture there is an event called prodview which counts # of pageviews for any given product and then when it is used with revenue or transaction, it gives interesting conversion ratios for different product.

For our understanding we will use ratio of quantity to # of visits for different pr

oduct as a product conversion rate.

Why product conversion rate?

Calculating product conversion rate is very important to understand which product is converting better vs. others? Moreover if you have cost data, you can also find out that whether the profitable products are converting better or not? With such insights, you can modify the e-commerce shop to ensure that the profitable products get more chance to convert etc.

As a normal analytics practice first thing is to build a template of what data we want to calculate the product conversion rate.

For our understanding we will use ratio of quantity to # unique views to product page for different products as a product conversion rate.

The quantity data will be available from the Google analytics interface & we need to get data of quantify & product views for different product.

How to get data from Google Analytic?

There is only small change that is required to calculate the product conversion rate in Google Analytics i.e. by using Google Analytics Events tracking.

Here is the syntax that you can use to generate product views statistic in

event tracking:

pageTracker._trackEvent

(“uniqueproductname”,

“variantname”,

“uniqecategoryname ”,

1)

This needs to fire on all your product pages in Google Analytics.

As a result of this, in your event tracking report you will find product names in event actions and get unique product views as well of total product views of the event via total events and unique event metrics.

You will find product names in event actions and get count of unique views as well of total views of the event via total events and unique event metrics.

By putting together all the data you have here is what you can get as an output for different product. Please note that in last column you can create conversion rate for your different product.

Obviously, some of the product has very high conversion rate as shown in highlighted portion. These are your winners.

Plot this conversion data with the product's revenue and you know whether high converting products are getting sold or not ? You can also use the advance segment to calculate the product conversion rate for different sources which will provide even better insights to what products works and which doesnt work ?! What more ? You can figure out low converting product and reduce them from your stocks  & save the money from warehouse !

What is Targeting?

My understanding of targeting is to provide content to the user which has high probably to be consumed.  It may be over simplified, however, easier said than done. Now that I am in my 6th year of web analytics industry, I now started realizing what & why probably Jim Sterne has his firm's name as Target !

Content personalization and targeting are two interchangeably used word that I have come across. However they are separate from behavioral targeting which has more to do with the targeted ads to be shown to the user. There is significant debate getting generated at Anil Batra's Blog about the definition of behavioral targeting ,however lets keep the focus of this post to content personalization and not behavioral targeting !

Different levels of targeting

I can think of two levels of targeting; Segment level & Individual level. The difference is in the granularity by which you can segment. In other words, this classification is based on the degree of small segments that you can create for your individual users. For example, you can create two segments of your visitor new & repeat and provide them different content. This is pretty straight forward as you create two different design of the page which works for your new & repeat visitor.

Individual level targeting or what I call one-to-one targeting is more granular where you provide exactly the content that your specific visitor would like to consume. For example if you are coming back to Amazon, it provides you specific unique content that would want to consume based on your prior visits to the site.

While Derek has a great content personalization presentation, I plan to expand the concepts that he has laid out. Another nice variable that should be added apart from different levels of targeting is situation in which customer is viewing the site.

In other words, your targeting effort doesn’t stop at just segmenting your traffic, but it should also include the situation in which users are coming to your site. For e.g. if you go to Zaaz on Friday night, you will see great message customized for you for friday night.

More to come on content personalization - What are your thoughts ?

Here is the list of  dimension and metrics along with definitions that is used in Tatvic Google Analytics Excel Plugin.

Metrics Definition :

Ad cost : Derived cost for the advertising campaign. The currency for this value is based on the currency that you set in your AdWords account.

Bounces : This field identifies the number of single-page visits to your site over the selected dimension. For example, if you apply this metric to the Ad Campaign dimension, it'll display the number of single-page visits to your site by users that reached your site via a particular ad campaign.

Bounce Rate : The percentage of single-page visits of no. of entrances (i.e. visits in which the person left your site from the entrance page).

CTR : Clickthrough rate is the percentage of impressions that resulted in a click.

CPC : Cost-per-click is the average cost you paid for each click on your  ad(s).

CPM : This stands for cost-per-thousand impressions. A CPM pricing model means advertisers pay for impressions received.

Clicks : This field identified the number of times a user has clicked on your Ads.

Entrances : This metric identifies the number of entrances to your site. It will always be equal to the number of visits when applied over your entire website. Thus, this metric is most useful when combined with particular content pages, at which point, it will indicate the number of times a particular page served as an entrance to your site.

Exits : This metric identifies the number of exits from your site, and, as with entrances, it will always be equal to the number of visits when applied over your entire website. Use this metric in combination with particular content pages in order to determine the number of times that particular page was the last one viewed by visitors.

Goal Completions-1 to 20 : The total number of completions for the requested goal number.

Goal Start-1 to 20 : The total number of starts for the requested goal number.

Goal Value-1 to 20 : The total numeric value for the requested goal number.

Total Goal Value : The total numeric value for all goals defined for your profile.

Impressions : A display of a referral link or advertisement on a web page. This metric accounts for the total number of impressions for a campaign.

Quantity : The total number of items sold within one transaction.

Product Revenue : Total revenue from purchased product items on your website.This does not include the shipping cost or tax.

New Visits : The number of new visits by people who have never been to the site before.

Pageviews : This field indicates the total number of pageviews for your site when applied over the selected dimension. For example, if you select this metric together with Request URI, it will return the number of page views over the returned result set for the Request URI for your report.

Search Depth : The average number of pages visitors viewed after performing a search. This is calculated as Sum of all "search_depth" across all searches / ("search_transitions" + 1)

Search Duration : The visit duration to your site where a use of your internal search feature occurred.

Search Exits : The number of exits on your site that occurred following a search result from your internal search feature.

Search Refinements : The number of times a visitor searched again immediately after performing a search.

Total Unique Searches : The total number of times your site search was used. This excludes multiple searches on the same keyword during the same visit.

Visits with Search : The total number of visits where internal site search was used.

Time on Page : This field indicates how long a visitor spent on a particular page or set of pages. It is calculated by subtracting the initial view time for a particular page from the initial view time for a subsequent page. Thus, this metric does not apply to exit pages for your site.

Time on Site : The time a visitor spends on your site.

Revenue : The total sale revenue, including shipping and tax, if provided in the transation.

Transactions : The total number of transactions. One transaction can have many quantity. Quantity and transactions has many to one functional relations.

Shipping : The cost of shipping for a transaction.

Tax : The amount of tax applied to a transaction. This value should be a number without any monetary symbols or commas in the value.

Unique Pageviews : The total number of unique visitors to a given page.

Unique Purchases : The total number of times this product was purchased in a transaction.

Visitors : A user that visits your site. The initial session by a user during any given date range is considered to be an additional visit and an additional visitor. Any future sessions from the same user during the selected time period are counted as additional visits, but not as additional visitors.

Visits : The number of times your visitors has been to your site (unique sessions initiated by all your visitors). If a user is inactive on your site for 30 minutes or more, any future activity will be attributed to a new session. Users that leave your site and return within 30 minutes will be counted as part of the original session.

Exit Rate(%) : The percentage of site exits that occurred from a page or set of pages.

Conversion Rate-Goal1 to 20(%) : In the context of Campaign Tracking, the percentage of sessions on a site that result in a conversion goal being reached on that site.

Event Value : The total value of events for the profile.

Total Events : The total number of events for the profile, across all categories.

Unique Events : The total number of unique events for the profile, across all categories.

Total Goal Completions : The total number of completions for all goals defined for your profile.

Total Goal Starts : The total number of starts for all goals defined for your profile.

Abandonment Rate for a Goal : It is the ratio of visitors who start conversion process but do not finish to the no of visitors starting the conversion process.

Total Abandonments for a Goal : It is the difference between no of visitors who start conversion process and the no of visitors actually completing it.

Funnel Completion Rate a Goal (%) : It is the ratio of no of visitors who completes conversion process to the no of visitors actually starting it.

% of New Visits : This will give Percentage of new visits based on all visits

Average Time on Site : This field is obtained using TimeonSite/visits.It is mainly used to calculate Average session length

Avg. Time on Page : This field is obtained using (Time on page)/(Total no of Pageviews-Total no of exists)

Average Goal value per Visit : Average Event value

Average Revenue per Transaction : This field is obtained by dividing total transaction revenue to total transaction

Average Revenue per Visit : This field is obtained by dividing total transaction revenue to total visits

Cost per Transactions : This metric is a ratio of total ad cost and no.of transaction that are recorded via Google Analytics. It is advises that you should break down this metric by campaign dimensions.

Dimensions Definition :

Ad Content : The first line of the text for your online Ad campaign.

Ad Slot : Thev position of the advertisement as it appears on the search results page. For example, the online adertising position might be side or top.

Ad Slot Position : The order of the online advertisement as it appears along with other ads in the position on the page. For example, the ad might appear on the right side of the page and be the 3rd ad from the top.

Affilation : Typically used to designate a supplying company or brick and mortar location; product affiliation.

Ad Group : This field identifies the ad groups that you have identified for your online ad campaigns. For example, you might have a campaign called "Christmas" that uses the keywords "fuzzy bear" and belongs to the ad group "toys."

Browser : The names of browsers used by visitors to your website. For example, "Internet Explorer" or "Firefox."

Browser Version : The browser versions used by visitors to your website. For example, 2.0.0.14

Campaign : The name(s) of the online ad campaign that you use for your website.

City : The cities of website visitors, derived from IP addresses. The city field falls in a hierarchy of geographical groupings used in Analytics, which proceeds in the following order: continent, sub-continent, country, region, sub-region, and city.

Connection Speed : The qualitative network connection speeds of website visitors. For example, T1, DSL, Cable, Dialup.

Continent : The continents of website visitors, derived from IP addresses.

Count of Visits : Number of visits to your website. This is calculated by determining the number of visitor sessions.

Country : The countries of website visitors, derived from IP addresses.

Date : The date of the visit. An integer in the form YYYYMMDD.

Day : The day of the month from 01 to 31

Days Since Last Visit : The number of days elapsed since visitors last visited your website. Used to calculate visitor loyalty.

Days to Transaction : The number of days between users' purchases and the related campaigns that lead to the purchases.

Event Action : Which actions recorded events? Click any action in the table to see the labels or categories for that action. The Site Usage and Ecommerce tabs show how event visits compare against all visits to your site. For example, if 500 visits out of 1000 included events, Visits (under Site Usage) would reflect 50% of Site Total. (If a comparison date range is set, the report compares event visit metrics for the two date ranges instead.)

Event Category : Which categories recorded events? Click any category in the table to see the actions or labels for that category. The Site Usage and Ecommerce tabs show how event visits compare against all visits to your site. For example, if 500 visits out of 1000 included events, Visits (under Site Usage) would reflect 50% of Site Total. (If a comparison date range is set, the report compares event visit metrics for the two date ranges instead.)

Event Label : This field is used for event tracking and identifies the optional label you can apply to a particular event you are tracking. For example, you might track videos under the category "video" and apply the label "[movie name]" for each separate video.

Exit Page : The last page of the session (or "exit" page) for your visitors.

Flash Versions : versions of Flash supported by visitors' browsers, including minor versions.

Hostname : This field identifies the hostnames visitors used to reach your site. In other words, if a visitor types in 'www.googlestore.com' to reach your site, then this string appears as one of the hostnames used to reach your site. However, if users also come to your site by typing in 'googlestore.com' or via an IP redirect from a search engine result (66.102.9.104), that value will also be retrieved by this field.

Hours of the Day : Choose from a range of hours to refine report data by hourly range.

Java Support : This field, used in determining browser capabilities for visitors, identifies if the visitor has Java support enabled on their browser or not.

Keyword : This field identifies all keywords, both paid and un-paid, used by users to reach your site.

Landing Page : path component of the first page in a user's session, or "landing" page.

Languages : This field uses the language as provided by the HTTP Request for the browser to determine the primary language used by visitors. Values are given in 2- or 4-character language code (e.g. en-br for British English).

Latitude : The approximate latitude of the visitor's city. Locations north of the equator are represented by positive values and locations south of the equator by negative values.

Longitude : The approximate longitude of the visitor's city. Locations east of the meridian are represented by positive values and locations west of the meridian by negative values.

Medium : This field identifies the type of referral to your website. Thus, while a referring source (URL) to your website might be a search engine, there are two possible mediums that can be used from a search engine referral: organic (from a search result) and cpc (from an online ad).

Month : The month of the visit. A two digit integer from 01 to 12.

Domain : The domain name of the ISPs used by visitors to your website.

Network Location : The name of service providers used to reach your website. For example, if most visitors to your website come via the major service providers for cable internet, you will see the names of those cable service providers in this element.

Next Page : A page on your website that was visited after another page on your website.

Operating System : This field identifies the operating system of your visitors. For example (Windows, Linux, Macintosh).

Operating System Version : This field identifies the version of the operating system of your visitors, such as 'XP' for Windows or 'OSX' for Macintosh.

Page Depth : The number of pages visited by visitors during a session (visit). The value is a histogram that counts pageviews across a range of possible values. In this calculation, all visits will have at least one pageview, and some percentage of visits will have more.

Page Path : A page on your website specified by path and/or query parameters.

Page Title : Enter a string to refine report data for pages on your site by title. The title for a page is located in the field of the HTML header area for your pages. You can filter by title by entering either a portion of the title or the entire title (for exact matches).

Prev Page : A page on your website that was visited before another selected page on your website.

Product Category : Any product variations (size, color) for purchased items as supplied by your ecommerce application.

Product : The product name for purchased items as supplied by your ecommerce tracking method.

Product SKU : The product codes for purchased items as you have defined them in your ecommerce tracking application.

Referral Path : This field returns the referral URI (path and page, generally) of the referring site. If someone places a link to your site on their website, this field returns the path and page of the website that contains the referring link.

Region : The region of website visitors, derived from IP addresses. In the U.S., a region is a state, such as New York.

Screen Colors : This field identifies the screen color depth of visitors' monitors, as reported by the browser HTTP Request Header.

Screen Resolution : This field identifies the screen resolution of visitors' monitors, as reported by the browser HTTP Request Header.

Site Search Category : The categories used for the internal search if you have this enabled for your profile. For example, you might have product categories such as electronics, furniture, or clothing.

Site Search Destination Page : A page that the user visited after performing an internal website search.

Site search Keyword : Search terms used by website visitors on your internal site search.

Refined Keyword : Subsequent keyword search terms or strings entered by users after a given initial string search.

Site Search Start Page : A page where the user initiated an internal site search.

Site Search Used : A boolean that separates visitor activity depending upon whether internal search activity occured or did not occur. Values are Visits With Site Search and Visits Without Site Search.

Source : This field, used in reporting traffic sources to your site, identifies the domain of the referring source (e.g. google.com).

Sub Continent Region : The sub-continent of website visitors, derived from IP addresses. For example, Polynesia or Northern Europe.

Transaction : This field is used in ecommerce-enabled tracking and identifies the transaction ID for the shopping cart purchase as supplied by your ecommerce tracking method.

User Defined Value : The value provided when you define using _setVar variable for your website.

Visit Length : The length of a visit to your website measured in seconds and reported in second increments. The value returned is a String. To replicate the length of visit report in the user interface, after requesting the data, you can convert the string value to a number and sum up the visits for a group of visit durations.

Visitor Type : A boolean indicating if visitors are new or returning. Possible values: New Visitor, Returning Visitor.

Count of Visits to a Transaction : This field, used for ecommerce-enabled tracking, identifies the number of visits made to your site via a given campaign before the user makes a purchase.

Week : The week of the visit. A two-digit number from 01 to 52.

Year : Enter one or more years in yyyy format, with multiple years separated by commas. This refines report data by a given year or years.

customVarName : The name for the requested custom variable.

customVarValue : The value for the requested custom variable number.

Tracking worldpay transaction with Google Analytics & getting ecommerce data in most accurate manner is amongst one of the challenging project that we executed for one of our clients recently. I wanted this blog post to address what we all did to capture most accurate Google Analytics data possible into worldpay.

Several issues need to be addressed before proper e commerce tracking can be executed.

Here is the design how worldpay works:

Worldpay doesnt allow javascript to be executed on their domains. So you cannot post any Google analytics code on green boxes as describe above. So technically, nothing can be tracked post step no.1 as described above.

To make this tracking work, several things needs to happen.

1. We need a thank you page after worldpay transaction finishes which is on a domain where javascript can be executed. That is, we need to have one more step after (3) occurs which pushes user to move from (3) to a new page. That is the page where we can place Google analytics ecommerce tracking and track the value of transaction. Let’s call it step no.(4)

   

2. More importantly, we need to pass all the Google analytics cookies to this thank you page ,so that the ecommerce code that gets executed on step no.4 attributes the transaction to original cookies that were present on product page or step (1).

So essentially we need to have a page at step (3) that provides a button on Worldpay that says click here to finish the transaction. I will come back later as to what other things that button needs to do.

So till now , by having that button “click now to finish the transaction” ,one problem is solved so that we have one page where we can put GA code & execute the addtrans etc functions of Google Analytics.

Lets focus now on how we can pass on same cookies that existed on step (1) to step (4). Normal google analytics functions of linkbypage will not work as they can only work if the next page can fire Google Analytics.

This is where this gets really innovative.

You can get all the required cookies one by one. But, there is a simple way to get all GA cookies required at once. By using the method, pageTracker._getLinkerUrl of Google Analytics, which will give you all the cookies required along with the URL.

Now, there is a concept of hidden variable in Worldpay. Hidden variables can pass different values like price, currency, order type etc. You can create a new hidden variable and pass the Google Analytics cookies into these hidden variable.

Generally, the RBS World Pay form (where the RBS World Pay button is located and from where the users goes to RBS World Pay site for payment) looks like the following:

<form action="https://select.worldpay.com/wcc/transaction" method="post">
	<input type="hidden" name="cartId" value="Cart ID">
	<input type="hidden" name="desc" value="Product Desc">
	<input type="hidden" name="currency" value="GBP">
	<input type="hidden" name="amount" value="XX.XX">
	<input type="hidden" name="instId" value=137379>
	<input type="hidden" name="lang" value="en">
	<input type="hidden" name="subst" value="yes">
	<input type="submit" value="Order by credit/debit card" name="submit">
</form>

There are some changes that you need to make for this to work:

1. The form needs to be given a name, if one is not present. This can be done by adding name=”worldpay” in the form element.
2. We also need to have one custom variable defined in RBS World Pay system which will have the value of the cookies required, that can be accessed in Thank you page. Here, the defined custom variable is MC_gacookie. In this particular example, we also have one more defined custom variable MC_analytics which will have account id. This is required only when pages with different profile ids leads to same Thank you page.

With these changes, the above code of RBS world pay on product page will look like the following:

<form action="https://select.worldpay.com/wcc/transaction" method="post" name="worldpay">
	<input name="cartId" type="hidden" value="Cart ID" />
	<input name="desc" type="hidden" value="Product Desc" />
	<input name="currency" type="hidden" value="GBP" />
	<input name="amount" type="hidden" value="XX.XX" />
	<input name="instId" type="hidden" value="”XXXXXX”" />
	<input name="lang" type="hidden" value="en" />
	<input name="subst" type="hidden" value="yes" />
	<input name="MC_analytics" type="hidden" value="XX-XXXXXX-X" />
	<input name="MC_gacookie" type="hidden" />
	<input name="submit" type="submit" value="Order by credit/debit card" />
</form>

Now, let us see what extra statements that we need to add to the normal GA tracking script on product page (or step: 1) that is generally placed at the end of the page.

The modified GA tracking script looks like the following:

<script type="text/javascript">
var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www.");
document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));
</script>

<script type="text/javascript">
try {
	var pageTracker = _gat._getTracker("UA-XXXXX-Y");
	pageTracker._setDomainName("none");
	pageTracker._setAllowLinker(true);
	pageTracker._setAllowHash(false);
	pageTracker._trackPageview();
	var save_url = pageTracker._getLinkerUrl("www.abc.com");
	var aPosition = save_url.indexOf("?");
	save_url = save_url.substring(aPosition + 1);
	worldpay.MC_gacookie.value = save_url;
} catch(err) {}
</script>

These additional statements are aimed to accomplish the task of saving all the required cookies as the value of the custom variable MC_gacookie that is created above.

Now, we need to store this value in a custom variable, MC_gacookie, which is specially created for this purpose. This value is accessed in the format <formname>.<variablename>.value and to this, we assign the value of required substring, save_url, obtained above. In the above example, formname is worldpay and variablename is MC_gacookie.

So by doing above, we have been able to pass the cookie values to a specific custom variable to be passed into worldpay without the need of javascript.

What is needed now is what to be done on page 3 (in worldpay’s language its called callback page). In This call back page (step: 3), we get all the variables through post methods. Just to remind that this page (or call back page or step 3) is generally a purchase completion page. Here we are changing to just have a button which says “click here to complete the transaction” button. This call back page resides on website’s server however it gets executed on worldpay.

Now this button needs to pass the values of Google analytics cookies that we had been able to pass it via a custom variable (in our example MC_gacookie) in worldpay. If you use PHP, you can use following code to get that custom variable and form a query string (don’t confuse this with GA custom variable- this is WP custom variable).

<?php $parameter = 'MC_gacookie';
if($_REQUEST[$parameter])
{
    $query="";
    //Get all existing parameters
    foreach($_REQUEST as $k => $v){
     if($k != $parameter) {
     $query=$query.$k."=".$v."&amp;";
        }
        else
		{
        $query=$query.$v."&amp;";
        }
    }
    $query=substr($query, 0, -1);
?>

Here $currentpage is the complete path of the thank you page. So, $currentpage can take value like http://yourwebsite.com/thankyou.html
Note: You will get a warning message when you click on the button above.
So what you have done till now is, you have passed the GA cookies till step 3 and have it as a query parameter when user clicks on the button.

The thank you page will now have the following GA e-commerce code.

<script>
var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www.");
document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));
</script>

<script>
var pageTracker = _gat._getTracker("UA-XXXXXX-XX"); //This needs to be set if this value is different
pageTracker._setDomainName("none")
pageTracker._setAllowLinker(true);
pageTracker._setAllowHash(false);
pageTracker._trackPageview();
pageTracker._addTrans(
	"", // order ID - required
	"", // affiliation or store name
	"", // total - required
	"", // tax
	"", // shipping
	"", // city
	"", // state or province
	"" // country
);
pageTracker._addItem(
	"", // order ID - required
	"", // SKU code (stock keeping unit)
	"<?=$_GET['item_name']?>", // product name
	"", // category or variation
	"", // unit price - required
	"" // quantity - required
);
pageTracker._trackTrans();
</script>

Recently, I read highly respectable Hal Varian's research at inside adwords about their research on ad position and conversion rate. I was really intrigued by the findings but since their findings are statistical, it is reliable. I still have respectful disagreement to the concept which I'd share here.

The hypothesis is higher positions tend to get more clicks and therefore more conversions in total and higher relative value derived from the top position.

We tried studying the cause and effect relationship between the Ad Slots and revenue. The purpose was to establish a relationship that if we move up our advert on Google Adwords, can we gain extra revenue? If ye how much?

To answer this question we created two advance segments with respect to medium and Ad slot (Top and RHS) as shown below:

Advance segment for Adwords slots

If you are not familiar about Ad slots here is what I am talking about:

Top spots in google adwords

Note that, when you see data for Top slot your ad is shown in first three position and if it is RHS , it could be from 4 to 11 slot no.

So what does that mean now from site usage standpoint!!

Site usage report after applying advance segments in google analytics

Ok I know its not rocket science and probably now you even dont need me to analyze but just to finish the post, I will get it done ! Bear with me. If you are an Analytics Ninja, you are most likely to go off from here and immediately create these segments !

So what does the site usage report suggests to us :

• Visitor engagement is more for Top slot compared to RHS slot as seen from the No. of pages/visit metric which is 9.02 for former and 7.72 for later one.
• Bounce rate in Top slot case is less than 50 % of site’s bounce rate.
• Average time on site is also higher in case of Top slot visits compared to RHS visits.

Essentially the Top slot provides quality traffic to web site. Now lets have a look at what is the revenue impact of your ad slot.

Ecommerce report with adwords position slot

It isn’t hard to find out that, top Slot provides almost double per visit value than the RHS slot.

Now you know that the Top spot per visit value (which is our friend's favorite metric) which is about 100% more than when ads are shown at right hand side of the google ads. You can now go ahead to your adwords change the budget and position for your important keyword based on the data that you will see after creating such segment.

So in nutshell, I dont think the positioning of have has no relavance with your conversion/revenue. It certainly has. However, to establish better relationship (above is too simplistic) , we need to take into account quality score and ad copy etc.

But can you discount the numbers if you see them as you see in above reports ? Do you have opinion here ? do you think if there is better way to do this ? no ?

Thanks for reading !

We were working with lot of clients to track the outbound link going out of website using Brian Clifton’s Script. After using it extensively, we found if there are some updates that we can do , it will certainly help our customers and other users of the script to get greater insights on outbound link tracking.

Here are the Quick Updates :

1. From Trackpageview to Trackevent
In the old scripts pagetracker._trackpageview was used as medium to communicate the outbound link name to GA. It’d create an extra page view on the site and would show up in the content report. With the advent of Event tracking and now it being available for Advance segments, we realized that it is worth using event tracker for the code.

2. Time To Click The Link/PDF/Mailto
Brian Clifton had another script to track the page load time. This script measures how much time it takes to load a page for different users and it gets reported via event tracking. We used this same concept to integrate it into outbound link tracking.

We merged two script to create a mash up script so that when user clicks on link, an extra pageview is not generated and tracking happens via event tracking. Also, we added value of time it takes for users to click on specific link from the start of the page. This can give important insights on link placements and change the prominence of placing an external link to understand the user’s pattern of clicking external links. Since, this script works for downloads, mailto links as well it will be interesting to know, time it took for users to click on pdf/download/mailto links.

A normal event tracker is _trackEvent(category, action, optional_label, optional_value)

With the new script what will go into it ?

_trackEvent(“link type”, “Link URL” , “medium”, “time taken by user from page load to click on links”).

You can find new Script here.

Needless to say this though, we are extremely thankful to Brian for making scripts available for free and providing opportunity to update them !

While we had overwhelming response to our Google Analytics Excel Plugin, we realized that it might be worth explaining in detail the core features of the plug-in.

So for this post, I have decided to explain how to use our auto refresh feature using cell references from an Excel sheet. Below are the steps that users can take in order to update their dashboards automatically by changing input criteria. You would require to login before you execute these steps.

1.       Insert required from and To dates in excel sheet in two different cells as shown in image below.

2.       Click on Excel Icon in the client next to "From" date

3.       Select the cell where "from" date is inserted(in example it is B3) & Click "OK". In example below, it is B3.

4.       Similar to #4 select the "To" date by clicking on excel icon next to "To" date

5.       Select the cell within excel where you have "To" date provided. In example below it is B4.

6.       Select required parameters like data granularity (breakdown by)

7.       Select the appropriate metrics & dimension that is required for analysis. In the example below, for the sake of simplicity, I have requested no. of visits by visitor type.

Once, the above request executes you will see the output as shown below.

Above table starting from cell D4 provides you visits by visitor type for the month of July-09.

Now if you need the same data for Aug-09 or for any other dates, you can just change the date in excel sheet (aka B3 & B4) and click on refresh to get updated data in your excel sheet directly.

For .e.g.

As shown below once you change the dates in cell B3 & B4, and click on refresh, the Tatvic Google Analytics Plugin will automatically, extract the data from your Google Analytics account for the updated dates based on value in cell B3 & B4. This will result in updated numbers for visitor type table as shown below. Notice that in July, there were, 22,240 visits by new visitors vs. in August about 20,762 visits by new visitors !

Support for Both Excel 2007 and Excel 2003

We are in the process of implementing suggestions as shown by page speed (an open-source Firefox/Firebug Add-on) for one of our clients. One suggestion is to optimize the size of the images.
In the client's website, there are a lot of jpeg images (in thousands) that require image optimization which are all located in the same folder. It is time consuming process to get all the images optimized through pagespeed.
To avoid this tedious process, I have written a small batch script, which uses jpegtran, used to optimize only jpeg images. It gives similar optimizations as pagespeed does.

To be honest, I am not good at batch scripting. But, tweeked a bit to get it working.

Follow the steps given below to achieve the same:
1. Download jpegtran.exe and jpeg62.dll
2. Assume all original images are under the folder named original
3. Copy jpegtran.exe and jpeg62.dll to original
4. Copy the following code into notepad and store it as convert.bat in original

@echo off
for /f %%a IN (’dir /b *.jpg’) do jpegtran %%a > ../converted/%%a
pause

5. Double click to execute the script convert.bat
6. Once the script is executed, you will find all your optimized images in a separate folder named converted

Hope this helps.

Note: In my case, all of my images are of jpeg format. For other formats, you cannot use this.