Universal Analytics – Hyperbolic with substance

The last monday, 28 of October 2012, was a great day with with some amazing announcements at the Google Analytics Summit 2012 (#GASummit). Google had launched its new strategy that even when it sounds a little hyperbolic (Universal Analytics?), it has substance. With this new strategy Google Analytics is trying to move out from the Cookie centric (browser centric) measurement model to a new user centric model, which is GREAT! It means that they are not going to use cookies any more? No…means that they are still using the cookie but it will save a user ID (that will remain when the user log in and will be associated to a particular person!), qne that ID will be the new data base key, which means that reports will able to be based on People instead of cookies. I was talking about this some time ago, why not using the User id to join the cookies that a particular user has in different gadgets so you can understand the full stream of the interactions between a particular user and our brand (website, mobile app, etc).

Server Side Sessionization: With “Universal Analytics” the “sessionization” occurs at he server side. The new analytics.js will not maintain any tracking information (other than an anonymous identifier).

It represents important advantages allowing to add new search engines in traffic sources, configure the timeout of a cookie, classify some cookies as direct traffic (yoursite.com in a search engine), and last but not least the unique ID allow us to integrate the behavioral information of a user to al the information from that user, stored in another sources like a client database or CRM.

Customized segments and metrics: The above mentioned enable to configure the custom dimensions and metrics right on the tracking code and in the administration section as shown in the following image.

_gaq.push(['_setCustomDimension',1,'Custom Dimension 1']);

Measurement protocol: This is similar to the well known EDS (External data sources) from other platforms. This feature allows to send information from any source to Google Analytics scaling its possibilities to a new level. So now you can send to Google Analytics information related to external sources Call Centers or CRM, among others, to measure even measure a conversion generated offline. This will be done with the current method __utm.gif (image) and the information is send with the GET or POST method. As long as you use the Google Analytics protocols in a correct way, it will always accept the sent data.

Besides, will be possible to assign marketing and other costs to a particular user. So we can start talking about the model proposed by this blog, the Analytics 2.0 model, in which instead of analyzing ROI we will be able to analyze ROCI (Return on customer investment) allowing us to understands which segments of clients are making us earn money and witch other we are losing money so we have to stop investing money on them.

Dimension Widening: This feature permits generating more and better decision making scenarios based on custom dimensions and metrics, helping us understanding the impact (if there is any) of thousands variables towards a particular conversion (sales, registration, etc). Some post ago we talked about how to do that by using variance analysis (anova). This feature is an insight generating machine! in my opinion one of the best features ever introduced by Google Analytics.

This is becoming interesting. I went with very low expectations to the summit, waiting for “Much ado about nothing” but finally we see a light at the end of the tunnel, it’s far, but it’s there!

Dispersion Analysis with advanced segments in Google Analytics

In statistics, statistical dispersion (also called statistical variability or variation) is variability or spread in a variable or a probability distribution. Common examples of measures of statistical dispersion are the variance, standard deviation and interquartile range.

A measure of statistical dispersion is a nonnegative real number that is zero if all the data are the same and increases as the data become more diverse (Wikipedia).

Dispersion Analysis is one of the most basics and powerful statistical analysis, allowing you to understand how homogeneous is a population or sampling you are analyzing. Why would that be important? Well, if we talk specially about digital analytics one of the biggest problems that that we love to use “average” (or even rates), average time on site, average pages per visit, bounce rate, etc. The problem with averages and rates is that you put in the same bag apples and oranges, driving you to very Inconsistent decisions. Disperse points can drive you to a wrong understanding of the reality, ergo, will make you make wrong decisions.

One way of analyzing dispersions is taking off the disperse points from the analysis. I mean, if most of your visits have an average pageviews per visit ranging from 8 to 15, and have some with just one pageview (maybe bounces if the can’t do any other measured action in that particular page) and you know those ones are non qualified visitors, you can just take them out of the analysis. It will allows you to analyze a more homogeneous set of data, effectively increasing the certainty of the decision making scenarios.

So, let’s do this in Google Analytics. In order to select a particular set of data we will use Advanced Segments.

1. Take the set of data you wanted to analyze. In this case, let’s take the above mentioned case, Average pages / visit.

2. Create a new segment that takes only the set of data you are looking for. In this simple case we will just select all the traffic but those that visited just one page.

3. Analyze the information with the new set of data. Take a look at the difference in the results with one and the other set of data.

Looks like a huge difference right? Is much more than that, you can avoid disperse points and having not a huge difference in the results but you have the certainty of using the correct information.

The Yahoo! Web Analytics Merchandising Report

If you have an eCommerce project and have installed Yahoo! Web Analytics, or you haven’t but you are thinking about implementing it I drop you some interesting tips about the Merchandising Report.

The Merchandising report it’s an awesome additional reporting solution if you already have the eCommerce report installed.

With the Yahoo! Web Analytics Merchandise Report you will be able to track not just the regular stuff from each sale like the individual products your customers preview, add to their shopping cart and purchase but also it allows you to define categories for your products, create custom reports, and update your reports to reflect cancelled orders or changes to order amounts by sending API requests to the system, and even doing up selling / cross selling analysis. You can also upload your individual products costs and calculate how each campaign contributes to your profits.

Yahoo! Web Analytics implementation is pretty simple if you, at least, take a look at the manual . The merchandising report has the very same logic, you simple add functions to your tracking code like:

Action;
DocumentGroup;
Amount; setAmounts records the total price of a product (i.e., the individual price of an item multiplied by the total number of units of the respective item).
OrderId;
Discount;
Tax;
Shipping;
SKU; Corresponds to the specific products you wish to track. The product SKU information is usually expressed as a function employed by your shopping cart. However, it can also be expressed as a constant (e.g., TEN114/S/03)

It is important to mention that each Yahoo! Web Analytics function is used to inflate a function from your shopping cart. Since shopping carts have different setups, you need to be familiar with the functions used in your shopping cart.

Another interesting feature is “Tracking viewed products“. By adding the ‘PRODUCT_VIEW’ action to your action function, as in the following example, you can track how often potential customer view your products and which products are the most popular.

YWATracker.setAction(“PRODUCT_VIEW”);
YWATracker.setSKU(“H84963422″);

If you wanted to track more product views at the same time you can just do the following:

YWATracker.setAction(“PRODUCT_VIEW”);
YWATracker.setSKU(“H84963422;H09273923″);

Another feature that you will love is ADD TO CART TRACKING. By activating this feature (you simply add the ADD_TO_CART action to your action function, as in the following example) you can track which products your visitors added to their online shopping cart.

YWATracker.setAction(“ADD_TO_CART”);
YWATracker.setSKU(“H84963422″);

Important: The SKU does not have to include a letter and eight digits. It can be any combination of letters and numbers that you use to identify your products.

So we measured the viewed products, the added to cart products and now you can also track the Purchased products. To do so you simply activate the Sale action (01) action, as in the following example:

YWATracker.setAction(“01″);
YWATracker.setSKU(“H84963422″);
YWATracker.setUnits(“3″);
YWATracker.setAmounts(“300.00″);
YWATracker.setAmount(“EUR300.00″);
YWATracker.setOrderId(“123xxx”);

If the tracked currency is important to you, let me suggest you to take a look at this link where you will find the total currencies supported by Yahoo! Web Analytics

To enter the price of your purchased products, you need to use the setAmounts function. Unlike the setAmount function, the setAmounts function does not need to have the currency code entered, as the currency is inherited from the setAmount function.
You can also track more products purchased at the same time:

YWATracker.setAction(“01″);
YWATracker.setSKU(“H84963422;H09273923″);
YWATracker.setUnits(“3;1″);
YWATracker.setAmounts(“300.00;50.00″);
YWATracker.setAmount(“EUR350.00″);
YWATracker.setOrderId(“123xxx”);

One fantastic thing in Yahoo! Web Analytics is that the Tracking code has a very simple logic that it is replied in all the tracking functions. So once you understand the basics is not hard at all implementing another features.

Back from Google Analytics Summit 2011

It was a very intense week at the Computer History Museum. Jesse Nichols, the tireless Program Partner Manager for Google Analytics and Google Optimizar, did a great job with his team, arranging an event for more than 500 people from all over the world in in a very exquisite way.

I’m not sure what it is and what it is not under NDA so I wont go in depth about new launches and developments. The most important things I wanted to mention are:

1. The first day was basically an overall presentation about the platform improvements. All of them where Woowww… not all of them really useful, but the ones that does are awesome…at least are the ones I was expecting for such a long time.

2. The second day, Thursday, we went in depth about the Partner program and Technical aspects of the current and future launches. I had the honor of being part of the Panel with Justin Cutroni (Cardinal Path), Timo Aden (Trakken) and Russel Sutton (ConversionWorks), moderated by the awesome Sophie Chesters (Google).

At the end of the event it was a Web Analytics Thursday with a Rock Band, networking, drinks and food…anything else? Oh, yes…amazing people from all over the world willing to talk about their experiences without constraints. See you there next year mates!!!

Google Analytics changed the session (visit) definition

Last week Google Analytics changed the way the session (or visit) is calculated. Why is this so important? Because your past information will not change, just from now on, ergo when you analyze trends you will identify a variation in you reports comparing before and after the new visit definition, so the first thing you have to do is loading a new event note in your Google Analytics platform so when you analyze the information in the future it will be easy to understand the cause of the variation.

Last visit or session definition:

More than 30 minutes have elapsed between pageview for a single visitor. No changes.

At the end of a day. No Changes.

When a visitor closes their browser: It changes by “When any traffic source value for the user changes. Traffic source information includes: utm_source, utm_medium, utm_term, utm_content, utm_id, utm_campaign, and gclid”.

How is this new session definition different?

Basically if the person leave your site and come back from a different source (any of the above mentioned values changed) this will count as a new session. According to Google, this change will just generate a variation of not more than 1%.

Important Note from Google, remember add a note in your platform:

Update 8/17/2011 2:10 PM PST:
“We identified an issue responsible for unexpected traffic changes following our recent update to how sessions are defined in Google Analytics. A fix was released at 2pm PST Tuesday August 16th”.

The issue affected some sites using the following configurations:

1. If a user comes to a customer’s site with a space in some part of their traffic source data, then revisit the same landing page during that session by refreshing the page or later pressing the back button, a new session will be created for every hit to that page. (Clicking a link elsewhere on the site that leads back to the page should not matter.)

2. Google Analytics implementations using multiple trackers (an unsupported configuration) are also affected when a space is included in the traffic source data. These sites will see fewer visits from new visitors, and more visits from returning visitors (with some variation due to different implementations).

Campaign comparison Google Analytics vs. Yahoo! Web Analytics

Which is the best Web Analytics solution? That’s one of the most frequently asked questions in this industry. Unfortunately things in the world are not that easy, because if there is one “best” solution why would people buy another one? If there is one “best” solution why competitors don’t just work on the same line of development?

Most of the current solutions are the best…for a particular need. So the first thing to define it is what is your need.

Let’s see a very simple example comparing Google Analytics vs Yahoo! Web Analytics (or Y!WA) :

1. Campaigns with Google Analytics: Google Analytics has it’s own query parameter structure for campaigns. Which means that you have to use one utm_source, utm_medium, utm_term, utm_content and/or utm_name for any of your campaigns. The good thing is that you don’t have to do anything else to do it. I mean, you don’t need to configure anything on the tool, just add those query parameters with the specific values on the url you are advertising and that’s it. You can even use the Google Analytics URL Builder which concatenate all the values you provide on each field generating the campaign url in a very simple way.

So, if you have an standard campaign structure Google Analytics is a great solution, simple, faster and very effective.

2. On the other hand Yahoo! Web Analytics or Y!WA count with a more flexible solution that allows you to track campaigns based on different conditionals and variables that allows you to track almost everything. More work but more flexibility and more in depth analysis.

First you can select type of campaign, free campaign, one time cost, cpc or cpa.

Secondly you can fill the standard query parameters or even change them by others you are already using on campaigns (ie, adserver)

Finally you can select the required conditions for that campaign like “Url parameters equal”, “Url parameter contains”, etc…

So, none is the best. The best one is based on each client requirement… or just enjoy both!

Report your +1 in Google Analytics and Webmasters tools

Well, it is great to find out that at least some players in the industry are taken seriously the importance of information integration, the importance of having all the pieces of the puzzle available when creating the decision making scenario. A way to revert the situation displayed in “Top Performance Metrics“.

Last week Google released the +1 button, kind of a “Like” but for the Google+ Project. The best part of this released is that Google thought about integration from the beginning and you can measure the +1 button from Google Webmasters tools and Google Analytics understanding how +1 affect your traffic and traffic behavior.

Regarding Google Webmasters tools:

The Search Impact report gives you an idea of how +1‘s affect your organic search traffic. You can find out if your clickthrough rate changes when personalized recommendations help your content stand out. Do this by comparing clicks and impressions on search results with and without +1 annotations. We’ll only show statistics on clickthrough rate changes when you have enough impressions for a meaningful comparison.
The Activity report shows you how many times your pages have been +1’d, from buttons both on your site and on other pages (such as Google search).
Finally, the Audience report shows you aggregate geographic and demographic information about the Google users who’ve +1’d your pages. To protect privacy, we’ll only show audience information when a significant number of users have +1’d pages from your site.

Regarding Google Analytics, the good news is that is you configure the Javascript for Analytics, it reports not just the +1 but also other buttons allowing you comparing the different sharing actions by using Social Plugin Tracking in Google Analytics.

The Social Engagement report lets you see how site behavior changes for visits that include clicks on +1 buttons or other social actions. This allows you to determine, for example, whether people who +1 your pages during a visit are likely to spend more time on your site than people who don’t.
The Social Actions report lets you track the number of social actions (+1 clicks, Tweets, etc) taken on your site, all in one place.
The Social Pages report allows you to compare the pages on your site to see which are driving the highest the number of social actions.

Here I leave you a link to enable tracking for other social plugins in just a few simple steps.

On my way to Google

Sunday night, onboard at the 996 American airlines fly to Dallas and after that to San Francisco. If I’m enough lucky Hebert (a great guy from Codice) will be waiting for me. After that we will be heading Google Headquarters to catch up all the new stuff and to be in touch with fantastic people from all over the world. It’s the kind of places where you know you will learn a lot and charge the batteries of passion. I’m not talking about learn theory, or how to do things, it’s much, much more than that. It’s a place where you do learn about life, about passion in a place where nobody talks about the competition but about co-opetition.
I know I’ll be in touch to different cultures and mental models and the idea is drawing me an smile upon my face.
I’m also glad since I’ll be interviewed by Pavel from Czeck Republik, my first interview for such amazing country.

And last but not least, tons of web analytics!

Coremetrics acquired by IBM

Yesterday I was surprised with the news that IBM acquired Coremetrics. First, because IBM was not in my radar as one player interested in something like Web Analytics. Second because Coremetrics is a pretty solid platform with huge clients and they were working a lot during this last months in order to get some of the Web Analytics market that still pays for Web Analytics Solution. The Corporative market, mainly from publishers.

However, the deal is done, and this time I have no clue about what is gonna happen with this deal. The Financial aspects have not been announced but I assume it was a greaaaaaaaat deal. So congratulations to all the team for the deal, you always worked to build a solid platform that help us (the analysts) to make our work even more interesting. Appreciate! I just hope IBM do it better than Microsoft with Gatineau…

Google launches the Google Analytics APP store

Google has recently launched the Google Analytics Application Gallery allowing companies that are developing useful apps to offer their apps to Google Analytics users.

The idea is just amazing. As we were talking in this blog for several years, every person of every company of every industry has a very unique information need for making their decisions. Google could take two ways, the first is to develop all the required apps to satisfied the most users as possible, the second is to allow third party developers to do it by their self. The first possibility was very risky for Google since it is really difficult to them attend the unique needs of all their clients/users. So in my opinion they choose the very best decision, leave third party developers to do that by their self with the possibility of earning money…in a win-win situation.

Even when the app store has 53 Apps by now, since everyone could upload their app, the quantity will grow exponentially (as well as the unuseful apps will invade the store).

By know I’ll be testing Google Analytics for Ipad and let you know.

Analytics 2.0

Much more than just tagging

Category Archives: Web Analytics Tools