Demographics and Interests: Coming to a Google Analytics Profile Near You

I was really excited to see some new information in one of my Google Analytics profiles this week. What wasn’t so exciting is that out of the approximately 20 profiles I flit between, only one sported this new feature. With that said, my inner analytics nerd wanted to dig deeper.

How many of you are seeing “age” and “interest” data in your Google Analytics dashboards? I’d guess about 20 percent at this point in time, but it will be coming to all profiles as Google rolls the feature out.

I’m pretty excited about this for a variety of reasons, not the least of which is that as a marketer, the more information we’re armed with, the better we can do our jobs. Interest and age brackets we can apply custom segments and filters against offer a window into an entirely new way to market.

Why Age & Interests Belong in Google Analytics

Consider this: you run a mom and pop gift shop. You have a pretty good idea of your in-store clientele and what appeals to them, but you also sell those products online. Do the age and interest demographics of your online customers match those of your foot traffic customer? Now you can tell.

Now you can design and fashion your online storefront to match the ages and interests of your online traffic. Never assume that one is the same as the other.
I am under 40 (barely) and my mother is over 60; we like some of the same things, but would never shop for them in the same fashion. I do almost all of my shopping online, while my mom would hesitate and feel utterly exposed if she were to enter her credit card in an online form. We both like the same item, but you need to market to us differently.

The sticky wicket in this whole new view of analytics is implementation. It does take an edit to the tracking script, so dependent upon your skill level, you may need some help to get it going. Once you do, voila! New windows appear.

Let’s walk through the implementation.

Accessing and Activating New Features

First, check to see if you even have access to this new feature. Open a profile and click on “Audience.” If you see “Demographics,” “Interests,” and “Geo” in the menu, you’re in business. If you don’t see “Interests,” you haven't yet been given access.

 

If you click on “Interests,” you’re given a message that states your view isn’t configured for this data quite yet. There are a few steps here; they’re pretty easy to complete, but still necessary.

First, we need to access the Admin panel to enable the features:



Click on “Admin,” then choose the correct “Account” and “Property,” then “Property Settings.” Under Property Settings, scroll to the bottom of the page and you’ll see a selection for “Enable Demographics and Interest Reports.” Slide the button over to “Yes” and save the profile view.



Above, you can see a note stating you’re required to make a small change to your tracking code. See how by clicking “learn more” above, or read on.
The code changes are fairly straightforward; we just need to replace one line of the script. The new line of script basically allows your tracking script to support the display targeting platform.

We already know that display advertising can target via interest and age/gender, so we’re using the same script to collect that information from our guests, even if we aren't actively participating in display advertising.

To enable this feature, locate this line in your tracking script:

ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';

and replace it with:

ga.src = ('https:' == document.location.protocol ? 'https://' : 'http://') + 'stats.g.doubleclick.net/dc.js';

Now, you're collecting the new data. Please note that data will only be collected moving forward, so the sooner you implement, the more quickly you’ll see data.

Note: You may run into a message about thresholds. This appears if you have a fairly low volume site. Google will hold back some of the original data if your sample set is very small and they’re afraid you might know too much about an individual user. They want to deliver the data, but they don’t want to deliver too much information (I call this the creep factor). They aren’t going to make it possible for us to determine behavior or demographics of an individual visitor.

The Reports

Let’s take a quick look at the reports you can see within Interests, Age, and Gender. In the “Interest” report in the left column, you can see a pretty cool report of what your website visitors are interested in:



If you click on any one of these interest items, you can see a new report with the gender and age information for each one. We can also apply custom segments and other metric filters to this report.

Want to know which interest categories are the highest converting? Scroll up to the top and click “ecommerce.” That information is at your fingertips.

Once you’ve collected a good set of information, you can start tweaking your online marketing strategies to take advantage of this information. If your audience is young, market with design and culture trends that resonate to them. If you target and attract an aged population, consider the scrolling and font size of your website and try to improve usability for your customers.

Are you seeing Age and Interest breakouts in your Google Analytics? If so, tell us what you think about them in the comments.

Original Article Post by Carrie Hill @ Search Engine Watch

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Using the Google Analytics Service Provider Report for Lead Generation & Insight

The Service Provider Report is a small but significant report in Google Analytics. It's great for finding sales leads and markets to target, troubleshooting and reviewing cross domain requirements; quite a variety of uses!

This report comes in two parts: Service Provider and Hostname. These each have a lot of value to bring to your Google Analytics activity. We'll cover both in detail, but let's start with the Service Provider report, which can be found here:

Audience > Technology > Network

Service Provider Report in Google Analytics

Google will never give you the IP address of your users; however, they do report on the Internet Service Provider of your website visitors. This is the name of the Internet provider, which won't always be the large companies used by people at home – many service providers are named with the business or network.

For example, across various accounts I have access to, I've seen traffic from AT&T and Sky, but also providers like New York University, Google Inc., and local hotels, solicitors, and councils. Scrolling down this report can be very enlightening!

This contradicts the misconception that you need an external tool to be able to see who's been visiting your website. These lead generation / IP tracking tools do have some additional benefits and can be more comprehensive, but for those of you looking for free information this is a great place to start.

You may benefit from adding a Secondary Dimension showing Country/Territory so that you can see which country the ISPs are in. Generally speaking, analysis in this report will be country specific so making it clear whether the ISP is from a country you target is useful.



As with any Google Analytics location report the data is where the IP is based, not the user's actual location.

Find the Businesses That Have Been Looking at Your Site

As mentioned, there are a wide range of service providers, some of which name the business in which the user is located. There are many uses for this data, including:

• Understanding behaviour on site that has generated leads / clients.
• Finding new leads to get in touch with. 
• Understanding who is already showing an interest in your product who you could then market to. 
• Fine-tuning sales / marketing targets.

To find these businesses, you first need to get past the common ISPs, as these will not be of much benefit here. Here's an advanced segment created by Jeff Sauer that you can apply to your analytics profiles to exclude many common U.S. and UK service providers: Filter Major ISPs.

You should now be left with a smaller, more manageable, list of ISPs that will be of much more use to you.

Who Loves Your Resources?

If small businesses aren't important to you, perhaps ask yourself who reads your resources; this could be an important aspect. Think about the different groups of people who you want to understand further and scroll through the report to see if you can fit ISPs to them.

For example, a publication like Search Engine Watch would probably want to know all of the different search and digital marketing companies that are reading it. Unfortunately, digital marketing companies don't all label themselves as such. You would have to identify them all yourselves and create an advanced segment. However, you may decide that this will be beneficial in the long run.

One group you can easily combine and analyze is universities. More often than not they kindly label their ISP with the name of their university; this means you can just pop 'University' in the filter box and find all the establishments that are enjoying your content.

Breaking Down ISP Activity

There is one downside to this piece of data – you can't use it to break down other reports as a secondary dimension. However, you can use advanced segments containing service providers to your heart's content.

The main data that you can see specifically against each ISP in one place is the general on page interaction data, goals, and Ecommerce. This could help you identify whether people using ISPs known for their fast connections actually convert better than those on slower Internet connections. Perhaps it could help you decide which provider to advertise your products on if they have ad space on their website or own TV channels, as the Ecommerce report will show you which users spend the most.

Additionally, if you have a few pages that you really want to see against ISP, then consider creating goals to track these and then viewing the data in the Goals tab of this report. If you have more than just a few then consider using a dedicated profile for this to allow for analysis of up to 20 pages or categories containing multiple pages through the use of regex in goal completion URLs such as /trainers/(.*).

Now that you know all about where your traffic is coming from you can start to do more with the valuable data. My next post will cover the Hostname report that sits with the Service Provider report in Network.

Original Article Post by Anna Lewis @ Search Engine Watch

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How to Turn the Google Analytics Visitors Flow Report Into Your Secret CRO Weapon

Are you searching for that super secret insight in Google Analytics that will fuel the next big win for your conversion rate optimization (CRO) testing program? Big data expert Sinan Aral from the New York Times Research & Development Labs suggests the power of visualization.

"We've found that visualization is one of the most important guideposts in this search for knowledge, essential to understanding what we should look for," Aral said in a recent HBR article.

The Google Analytics Visitors Flow report is truly a handy way to visualize what's happening on a website. Today's the day you turn it into your secret CRO weapon and glean big insights from it before your next test.

What is the Visitors Flow Report?

The Visitors Flow report illustrates how visitors arrive at your website and the most common paths they take during their visits. An intelligence algorithm clusters groups of pages together into interaction nodes, which appear as green blocks on the report.

The gray dimension blocks illustrate how traffic lands on your site via your interaction nodes. The connections between the interaction nodes are either gray or red, indicating whether users moved from one page to another or if they left the website, respectively.



As with most other reports, you can apply any advanced segments to Visitors Flow. For example, you can segment for only those visitors that convert (i.e., take action) to better understand the "typical" experience on your site. Conversely, you can segment by those who didn't convert to also see the not-so-great experiences.

Segment the Visitors Flow report for different locations, campaigns, and anything else that will help you hone in on the important parts of your analysis.

You can also change the dimensions of the Visitors Flow report. By default, the Visitors Flow report shows how different source/medium combinations made their way through the website. Right-click any of these dimensions or interaction nodes to highlight only traffic through that dimension or node.

Those are the basics of the Visitors Flow report. Now let's explore how to use it for CRO testing.

Where Visitors Flow Comes in Handy for CRO

Great CRO tests are often the result of insightful analyses. Big insights, as the fellas from the New York Times R&D Lab refer to them, often start with a visual. That's where Visitors Flow really starts to become a compelling report.

Any CRO testing program worth its salt will begin with a holistic evaluation of the website to determine which pages receive the most visits, where conversions occur and where conversions should occur but fail to do so. It's common to head straight to the Google Analytics Content reports, but these reports only show rows and rows of URLs along with their associated metrics. They don't give you a sense at all of how people interact.

The Visitors Flow report takes all of this quantitative data and lays it out visually, telling a much more nuanced and in-depth story of what happened on the website. Take this campaign, for example:



It takes about two seconds to realize that there is a crippling form error occurring – thanks to the creation of a virtual page view when a user triggers a form validation error – which comprises a large percentage of visitors after their first page. There's a major issue with the experience here and a need to troubleshoot issues with the campaign form. Also, it's clear that the campaign landing page has a high bounce rate and should be further analyzed for reasons why it isn't resonating with visitors.

Visualizing user behavior can also help make sense of what would otherwise be a hopeless list of rows of data. This campaign has a relatively low bounce rate and no one page appears to be sending people away from the site:



But by looking deeper, a pattern emerges where users are bouncing back and forth between section and sub-sections within the website hierarchy, never quite finding that which they seek. Folks land, they poke around for a few pages and then they leave, often without ever finding the information meant to convince them. In this case, Visitors Flow helps us see that perhaps the information architecture needs to be reviewed to ensure that your visitors are finding the information they seek.

Visitors Flow can also help you spot some of your biggest CRO testing targets. This website lives or dies on the success of its homepage and a key information page:



Clearly both key pages have a lot of volume moving through them but are underperforming, which makes them perfect targets for CRO testing. Let's stick with this example and walk through how to use the Visitors Flow report as the first step in a CRO test plan.

5 Steps to Creating a Killer Test with Visitors Flow

Once you have a page to test, it's time to analyze your page for insights before you build a challenger. Don't even think about creating your test hypothesis or your challenging variations until you've gone through this process. Not every test will involve all of these steps, but you should mix and match them the best you can. You can never have too many insights.

Step 1: Google Analytics Deep Dive

The Visitors Flow report is a good starting point, but you'll also want to examine your test control page from other reports within Google Analytics. Look for changes in traffic, engagement and conversion that might tell you where to dig deeper.

Step 2: Ask Your Visitors What's Missing

If users aren't converting on your website, something about the experience is missing. Quantitative data tell us what happened but it doesn't tell us why. Using qualitative survey tools such as Qualaroo on your website can dig into the why when a page isn't performing.

Do yourself a favor and install a Qualaroo survey across your entire site asking three questions:

• Did you find what you were looking for?
• How satisfied were you with your visit today?
• Is there anything we can add to this page to make it more useful?

Qualaroo allows you to export and segment your survey results so you can focus in on how a particular page is performing. Are people able to complete their tasks? Are they satisfied? What information do they want on the page to make it more useful? Do this now and you'll have incredible page-level insights at your fingertips when you need them.

Step 3: Walk in Your Visitors' Shoes

UserTesting.com provides an option for fast, affordable remote usability testing utilizing real live users, which often reveals a disconnect between the experience we think we're providing and reality. Where Qualaroo is about qualitative metrics, Usertesting.com is all about gaining perspective into the minds of your customers.

If you're trying to understand how consumers start researching, instruct Usertesting.com users to perform a Google search around finding a solution to the problem your product or service solves. Their screens and voices are recorded as they step through tasks so you're able to observe their entire thought process.

Once you have a good idea for the normal process, give them your web page's URL and have them try to complete the task. Make note of any frustrating or head-scratching moments your users have and add these notes to your analysis.

Step 4: Ask the World What They Think

At this point you're going to have some pretty juicy insights for improving your page, and you'll have some conflicting opinions internally about how to re-imagine the page in question. The next step is to run a Google Consumer Survey to determine which labels to use, which images appeal to people most and which headlines are the most compelling.

These surveys are cheap and act sort of like AdSense. Publishers allow Google to serve up these surveys as a way to gate the content on their site. Users answer up to two questions before the gate is lifted and their content is revealed; marketers have a new way to reach consumers via statistically significant surveys; and publishers gain an incremental revenue stream. Everyone wins!

Step 5: Pulling it All Together

Now it's time to pull together all of your insights from the Visitors Flow reports, other Google Analytics reports, Qualaroo, Usertesting.com and Google Consumer Surveys to tell the collective story about why this homepage is underperforming and what must go into the challenging variation in order to crush the control.



All of the insights for this test were compiled and reviewed by the entire team, at which point we prioritized which issues we wanted to address. Designers were then able to mock up a variation that embodied our best ideas on how to give visitors more of what they needed and less of what they didn't want.



In the end, we ran this test with Conversion Factory's assistance using third-party CRO testing software Optimizely. The challenger produced a 23 percent conversion rate lift over the control with 96 percent confidence. The Google Analytics Visitors Flow report was the first thread we pulled, and the visualization it produced eventually led to the unraveling of a poor homepage experience that resulted in low conversion rates.

Test Like a Big Data R&D Scientist

Conversion rate optimization (CRO) can be a double-edged sword. The freedom of being able to test anything can be either a powerful way to improve your marketing results or a fruitless flurry of subtle changes in button color, headlines and imagery, all fumbling about in hopes that something will yield a positive result.

Using the Google Analytics Visitors Flow report can make you feel like an R&D data scientist for the New York Times and is a sure-fire way to start CRO tests off on the right foot.

How do you use the Visitors Flow report? Is it counter-intuitive way to use GA or is it handy way to start your analyses? Do you send screen shots of it to your boss because of its eye-candy nature? How will you use it to start or improve your own CRO testing strategy?

Original Article Post by Josh Braaten @ Search Engine Watch

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New Features In Google Analytics Content Experiments Platform

Analyzing data to gain insights into your business and marketing efficacy is just step one. Taking action on that data is the all too important next step. The Google Analytics team continues its focus on making analytics actionable with the latest additions to the Content Experiments Platform. Together, these new features make Google Analytics A/B testing engine more powerful than ever!

Google Analytics users who have linked their accounts to AdSense can now select AdSense Revenue as an experiment objective. Once set, Google Analytics Multi Armed Bandit optimization algorithms will shift traffic among the experimental variations to achieve maximum revenue in the shortest amount of time. This feature has been a top request among AdSense publishers and Google Analytics is excited to provide a tool to further empower our publisher ecosystem.  

For our most sophisticated Content Experiments users, we’ve added an advanced option to allow even traffic distribution across all experiment variations. Using this feature bypasses the programmatic optimization that Google Analytics provides so it isn’t right for everyone. If you have an experiment objective that can’t be entirely captured by a Content Experiment objective, then this new feature might be right for you.

Learn more about the Content Experiments Platform and the Content Experiments API.

Posted by Russell Ketchum, Google Analytics Product Manager @ Google Analytics Blog

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Updates on Analytics Access Controls

We want to share an exciting update to the earlier post about the new Analytics access controls. 

As we mentioned in that earlier post, we have built a more powerful access-control system to help you better manage who on your team can access what entities in your Analytics accounts. These access controls are now enabled on all Analytics accounts.

The feedback from our early users highlighted a clear need to let report viewers collaborate with teammates, and in response we created the new Collaborate permission that lets users not only create but also edit shared assets like dashboards and annotations.

Open the Admin page for your Analytics account, and click User Management.

You can see the new Collaborate permission listed along with the others.

Learn more about our new access-control system, and gain more precise control over your Analytics accounts.

Posted By Tim Thelin and Matt Matyas, Google Analytics Team @ Google Analytics Blog

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Google AdWords Adds New Paid & Organic Report

Google AdWords is introducing a new feature for advertisers to give more data right within the AdWords interface, even when it isn't paid ads specific. This is part of their campaign to connect data between the Google AdWords, Google Analytics, and Webmaster Tools.



The new paid & organic report, which can help advertisers see their search footprints and enable them to determine if there are keyword areas that can be supplemented with paid advertising. It also allows you to view detailed reports to show for particular keywords, how much organic traffic as well as how it advertising traffic you are getting or have the potential to get.

Google suggesting several ways for advertisers confined to the inclusion of organic traffic information beneficial to their business. You can:

• Look for additional keywords where you might have impressions on natural search, but without any related ads.
• Use it to optimize your presence for your most important high-value keyword phrases, so you can see where you need to improve your presence.
• Use it to test website improvements and AdWords changes, as you can compare traffic across both AdWords and organic in the same interface, which enables you to adjust accordingly.

In order to take advantage of this new report, you need to have a Google AdWords and Webmaster Tools account, and you will need to verify and sync them.

In unrelated AdWords news:

• Google has introduced a new option for reporting trending traffic. Now, you can toggle between daily, weekly, monthly and quarterly so you can quickly and easily see any resulting trends during those time periods.
• And finally, Google will officially retire the AdWords Keyword Tool on August 26. However, the keyword planner has been out for several months so you can easily get all the same data in their all-in-one tool.

Article Post @ Search Engine Watch

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Google Analytics on Google Developers Live

Ever wanted to learn more about Google Analytics APIs? Maybe even have someone talking to you about how to use them? Well, if you haven’t gotten a chance to tune in, we’re excited to present Google Analytics on Google Developers Live. Our Developer Relations team has been hard at work putting these together; we’ve done a few already, and also have some coming up that we’re excited about!

We'll be doing these a few times a month, on Thursdays at 10AM PDT (full schedule here). Each show is about a half hour.

The show will either take you “Behind the Code” or “Off the Charts.” Off the Charts is a series about getting into the deep features of Google Analytics, understanding how it works, things you can do with it and how to use the feature itself. “Behind the Code” will not only showcase new GA features and technology, but also take us behind the scenes and give you a chance to hear directly from some of the engineers, product managers, and others who work behind the scenes to design, build, and deliver these new features.

Here’s some of our favorites from the past:

Off the Charts: Google Analytics superProxy

Google Analytics superProxy is an open source project developed by the Google Analytics Developer Relations team. Join Developer Advocate Pete Frisella to learn how to use this application to publicly share your Google Analytics reporting data and power your own custom dashboards and widgets.

Behind the Code: Analytics Mobile SDK

The new Google Analytics Mobile SDK empowers Android and iOS developers to effectively collect user engagement data from their applications to measure active user counts, user geography, new feature adoption and many other useful metrics. Join Analytics Developer Program Engineer Andrew Wales and Analytics Software Engineer Jim Cotugno for an unprecedented look behind the code at the goals, design, and architecture of the new SDK to learn more about what it takes to build world-class technology.

Don’t forget to check out next week’s show (8/29, 10AM PDT) on the recently launched Metadata API, which contains all the dimensions and metrics that you can query with in Google Analytics Reporting APIs. We’ll be discussing how you can use this API to to simplify data discovery. Tune in here!

Posted by Aditi Rajaram, Google Analytics Developer Relations team @ Google Analytics Blog

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Introducing The New Google Analytics Metadata API

Google Analytics users can use the Core Reporting API to save time by building dashboards and automating complex reporting tasks. This API exposes over 250 data points (dimensions and metrics), and new data is added every few months. For many developers, it can be difficult to keep their applications up to date with all the latest data.

To make things easier, today we are launching the new Google Analytics Metadata API to simplify data discovery. The Metadata API contains all the queryable dimensions and metrics included in the Core Reporting API. We’ve also added attributes for each dimension and metric, such as the web or app name, full text description, grouping, metric calculations, deprecation status, and whether the data is queryable in segments. You can check out at a live Metadata API response here.

You now have programmatic access to generate the same list of dimensions and metrics we use to generate our public documentation.

You can now create this list using the Metadata API.

 

Saving Developers Time

When you create tools to query the Core Reporting API, you can use the Metadata API to automatically update your user interfaces. For example, Analytics Canvas, a popular 3rd party Google Analytics data extraction tool, uses the Metadata API to keep its query building interface up to date.

Analytics Canvas uses the Metadata API to power its query builder.

According to James Standen, founder of Analytics Canvas, "In the past, keeping Analytics Canvas up to date with the Google Analytics API dimensions and metrics required a lot of manual updating to our application. The new Metadata API automates this process, saving us time, and giving our users direct access to all the great new data the instant it's available. Users love it!"

New Deprecation Policy

To increase data transparency, we’ve also published a new data deprecation policy for dimensions and metrics. New data we release will be announced on our changelogs and automatically added to the Metadata API. Data we decide to remove will be marked as deprecated in the Metadata API, allowing developers to gracefully remove these values from their tools.

Get Started Today

Our goal was to make this API super easy to use. To get started, take a look at our list of resources below:

• Read the Metadata API Reference guide to learn how to use the API data in your application.
• Read the Metadata API Developer guide to learn how the API can be used to solve common use cases.
• Join us for our Google Developers Live show on the Metadata API, Thursday August 29th at 10am PDT / 5pm UTC.

Questions? Comments? Simply want to share in the excitement? Join the analytics developer community in our Reporting API Developer forum.


Posted by Nick Mihailovski & Srinivasan Kannan, Google Analytics API team @ Google Analytics Blog

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Google Analytics Adds Mobile Capabilities to Tag Manager

Google Analytics has introduced two new features: a new version of Tag Manager for your mobile apps and a software development kit (SDK) to make it all work together. The Google Analytics SDK words two-fold. It includes all the Google Analytics functionality you need, while also allowing providing a framework for Google Tag Manager for Mobile Apps to work.
Last year, Google introduced Tag Manager to help you sort out the multitudes of JavaScript code snippets that are required for all your widgets and plug-ins. From social sharing buttons to analytics tracking code and everywhere in between, Google Tag Manager helped you organize them all in one web-based interface that gave you one line of code to insert into your site. For websites, using Google Tag Manager meant better managing of code and – more importantly – increased page load speed.

Previewed at Google I/O, Google Tag Manager For Mobile Apps provides similar conveniences, but with better effect. Depending on how your tech team has developed your mobile app, it can be difficult to change settings or add additional tracking elements.
Apps for devices are not like Web pages. They must take original code (typically Objective C or Java) and then be recompiled into the app package, itself. Changing one setting not only means testing and recompiling, but also deployment. Your app is reliant on users to update to the latest version before that change is implemented.

Google Tag Manager for Mobile Apps eliminates that problem. All of your tracking codes can be edited and fine tuned right from the Tag Manager Web interface.

When changes are made, a push notification is sent the devices running the app. The Google Analytics SDK interprets the changes and makes them happen, without any need for recompiling. This means your app doesn't "change" or "constantly update" users.

Out of the box for its initial launch, Tag Manager for Mobile Apps supports Google Analytics tracking, and both conversion tracking and remarketing using AdWords tags. There are also a myriad of third-party tracking event functionality that can be taken advantage of using the "custom" tag. Only Android and iOS platforms are supported currently.

Setting up your Mobile App is quick and easy. Click the "New Account" button from your Overview page. On the next screen, select a name for the new account and tag container and choose "Mobile Apps" instead of "Web Pages." then select your platform(s) and time zone and you're off. you can start adding your JavaScript code snippets and parameters.



While adding the Google Analytics Services SDK will require a recompile and re-deployment, it is likely the last one you'll need for the foreseeable future, at least as far as tracking events and campaigns is concerned.

Article Post @ http://searchenginewatch.com/article/2289832/Google-Analytics-Adds-Mobile-Capabilities-to-Tag-Manager

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Google Analytics Engagement Report: How to Find Helpful User Insights

Following on from my posts about the New vs. Returning and Frequency & Recency reports in Google Analytics, it's time to have a look at the third behavior report: Engagement. This has two parts to it – Visit Duration and Page Depth. They are both useful for a top-level analysis of how your websites users interact with the site.

Visit Duration

This report shows how many visits lasted each length of time shown in the report. The second column shows how many pageviews each time bracket delivered.


In the 0-10 seconds row, there was a very high number of visits compared to the other rows, and the pageviews weren't much higher than the number of visits. This makes sense as those who weren't on the site very long wouldn't have had time to visit many pages. In addition, it also includes all bounce visits where only one page was viewed before the user exited.

Moving further down, you can see the visits and pageviews increased where the time frames covered a longer period of seconds. This slightly skews the view, but you can hardly expect the report to break it down into 10-second chunks from 0 to 1800+ (30 minutes) – the report would be huge and unmanageable! Grouping data is often the best way to manage it anyway, hence advanced segments.

To make this data even more useful to you than it is at first glance, make sure you utilize advanced segments. You can use these to really understand different types of visitors and what is of most value to your website:

• Visits with conversions
• Visits with conversions worth over £50
• Visits with conversions worth less than £10 but over £0.01
• Visits that included a view of a key page (i.e. a key lead generation page if you don't have monetary conversions or goals set up)
• Visits where certain files were downloaded or links clicked (measure with Event Tracking http://www.koozai.com/blog/analytics/the-complete-google-analytics-event-tracking-guide-plus-10-amazing-examples/)

From this, you might find you get a very different picture, like this example with the "Visits with Transactions" default advanced segment applied to an example profile which uses Ecommerce tracking:


Here we can see that to have completed a transaction almost all users have spent over 180 seconds (3 minutes) on the site and between them have viewed a large number of pages. If we divide pageviews by visits, we can see the average for those spending 181-600 seconds on site is a mighty 17 pages per visit.


Now, if we compare transactions with revenue over $50 to those below $50, you can see that those spending less money spend less time on site and view less pages. This makes sense because if they have spent more, chances are they had to view more pages in order to find additional products.

However, from this data you should try to understand why users are acting like this on site. See if you can encourage higher value purchases without the user having to significantly increase the length of time they are on the site and how many pages they have to trawl through.

Think about the following:

• If you make the products more accessible, could you bring down pageviews while increasing order value?
• If users have spent five minutes on your site but not converted – what's gone wrong?

Make sure, as with any analysis, that when you review this report you use it to understand your users. Ask questions of the data and your website that help you pinpoint where improvements can be made. Don't assume that every metric needs to go up – trying to increase visit duration might be counter intuitive as those on for a long time may be the ones not finding what they're looking for!

Page Depth

This report is all about how many pages the users viewed (i.e., how many visits saw five page views and how many pageviews did that generate in total). This report varies in usefulness depending on how many pages people view on average – when the average is high you will see a lot of data in the 20+ group that you won't be able to do a huge amount with. However, for smaller websites where the average pageviews is lower than 20, the report could be very insightful for you.

This report can be good to review based on different areas of your website. For example, blog only data may be very different to services pages. Again, it's interesting to review this for different advanced segments to compare the different levels of engagement between users who convert and those who don't.


This comparison shows results from two very different websites. See how on the Ecommerce site's graph there is a high number of people viewing more than 20 pages. However, on the blog, far less people view this many.

If you find that you have visits which triggered < 1 pageview, make an advanced segment for this. Take a look at the data in reports, such as Technology, Traffic Source and Demographics to see if they are bots or caused by something else.

Summary

Bear in mind that both reports here are based on sessions, so users coming to the site 20 times and only viewing one page each time will all fall under the 1 page row. In contrast, users who view 20 pages in one session will be in the 20 pages row.

Again, you can add advanced segments to see whether those spending more visit a certain number of pages:


This report is often proof that users view a lot of pages when placing a high value order, but perhaps your data will open your eyes to other patterns too.

For both parts of the Engagement report, the big thing is to understand what works for your users and what you can improve on. The reports can help you to profile good customer's actions, which can then help you work to get more customers of a similar nature and turn the unsuccessful visits into more successful visits.

Article Post @ Search Engine Watch

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Google Analytics Expands Attribution Capabilities for Premium Users

Hang on to your seats, data lovers. Google Analytics has announced a new way for examining the multiple touch points customers make on their way to conversion on your website. The feature is live for all Analytics Premium users worldwide.

Two years ago, Google Analytics introduced us to multi-channel funnel reports. These reports – available to all users – allow you to see which multiple paths visitors followed to get to your website. It counted all the visits and sources that it took a visitor to convert a goal on your site.

Earlier this year they introduced the the Customer Journey to Online Purchase tool that helped site owners get a better picture of various models for attributing touch points. This tool worked with the existing multi-channel funnels to view purchase paths.

But all of these tools required web analysts to apply values to each touch point based on various attribution models. Some models suggest the first touch point or the last touch point should be weighted higher (first-touch or last-touch attribution). Others suggest that the path of all channels be weighted equally (linear model). Either way, it required an analyst manually applying values.

Lastly, it is difficult to determine how much one particular channel worked. In combinations, a channel's contribution to making a user convert might change by any number of factors.

Google Analytics Premium has now taken attribution modeling to the next level. Premium users can now enjoy the Attribution Model Comparison Tool. Essentially automating the process, the new Data-Driven Attribution in GA Premium automatically sets the weights based on data in the world. And it’s smart!

Instead of leaving the assigning of weighted values to the analysts, the Data-Driven Attribution uses an algorithm to do it for you. It determines how individual ad interactions or other touch points across channels interact with each other. Taking samples of data from the previous 90 days, the Data-Driven Attribution model compares one set of users to another set of users and figures out the probability of each group converting.

For example, say you have a segment of visitors who converted after interacting with social media, display ads, and organic search. Perhaps that segment's conversion rate was 3 percent. Google Analytics Data-Driven Attribution will compare that segment to another segment that interacted via social media and search but not display. If that segment converts at a 2 percent rate, the attribution model can reasonably predict that how much weight the display ad channel contributed. The incremental increase in probability of converting helps feed the algorithm and becomes the basis for attribution.

Additionally, the Data-Driven Attribution model also compares non-conversion visitor groups. By running the model against both converter and non-converter provides a more accurate comparison. The attribution model looks at "similar visitors" based on various channels, ad exposures, ad placements ad types, and repetition.

While the weights across channels are automatically algorithmically applied, Analytics Premium users are able to tweak them, if they choose.

Rules for applying manual weights can be applied. After the model does its thing, manual weighting rules can apply. For example, if your administrator feels direct visitors do not have any bearing on conversion, a rule could be applied removing all weight from direct visitors.

In addition to its incredible simplicity, the algorithm is transparent. The Model Explorer Tool, another new feature, will allow you to see exactly how each channel is weighted and why. By clicking around the report the tool creates, it will help you explore how the model will actually score various channels.

Additionally, you can drill-down into secondary dimensions – similar to any other Google Analytics report – to see which combinations work best. This allows you to view how certain creative ads perform against various placements. While you many know display ads, as a channel, is weighted high, by drilling down in, you may discover sidebar skyscraper ads outperform wider horizontal banners. The data will tell you which yields the best ROI.
A Google spokesperson told Search Engine Watch this is where the model really soars.

For display ads, the tool allows you to understand the difference between click-throughs and impression views. If a user is exposed to numerous banner ads, regardless of whether that user clicks, the exposure is counted in the model.

For channels like YouTube, the data gets more granular. You can determine if full video ads were watched completely or skipped after 15 seconds. All of this data goes into the attribution model to fine-tune your ad spend.

Reporting methodology is geared toward aggregate data based on trends of a customer. It isn't prioritized toward identifying individuals. It's geared toward of users exposed to a particular channel or ad strategy. When all is said and done, it truly only speaks to the probability of how much a channel is helping visitors convert.

The model self-adjusts itself as it goes. It uses a rolling 90-day history and adjusts, if necessary, on a weekly basis.

If your new video campaign goes viral, it will account for those additional click-throughs, especially if they lead to conversions. When the viral spike is over, it will adjust accordingly.

No attribution model will ever be able to tell you exactly what any given user will do on any given visit. Attribution models that require values and weights to be applied manually are prone to personal bias and statistical inaccuracy. While this data-driven model isn't perfect, it is certainly one of the more useful.

At the end of the day, by which model are you making your decisions?

Article Post @ Search Engine Watch

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BEST Practices: Google Analytics Conference

The following is a guest post contributed by Caleb Whitmore, founder of GACP Analytics Pros and the BEST Practices Conference, Google Analytics enthusiast and aspiring mountaineer.

BEST Practices: Google Analytics Conference

Boston, September 19

Seattle, November 14

As a digital analytics firm, we obviously love the constant connectedness of social media, mobile devices and the web. But we are also the first to admit that the never-ending noise leaves little room for the brilliance that come from letting your mind wander.

BEST Practices for Google Analytics is designed to give you the best of both worlds. 

We combine strategic inspiration, practical instruction and a wide-open location to create a Google Analytics conference like no other. In six short weeks, BEST Practices will land in Boston and we invite you to join us.

Top 7.2 Reasons to Attend A BEST Practices for Google Analytics Conference this Fall:

1. Networking: You will be surrounded by innovators in the digital analytics industry - previous attendees include Starbucks, Yelp, Priceline, GoPro and more. Talk to both experts and peers who are using analytics to creatively solve problems.
2. Speakers: Our speakers are actively practicing what they preach every day. Members of my AP team will cover specific best practices, I will review some of the tricks I have learned from a decade in this business, Ian Myszenski from Wildfire will be showcasing the measurement of social media . . . and the list goes on.
3. After-Party: Mix and mingle following the event. Past after-parties have provided a great place to keep the brainstorming and inspiration flowing as you chat with people from a wide variety of industries and backgrounds.
4. Topics: Receive practical instruction on the latest Google Analytics features, including advanced segmentation, multi-channel funnels, attribution modeling, Google Tag Manager, Universal Analytics, social and more.
5. Interaction: Hands-on interaction is key when learning to apply new knowledge. We will give you a chance to apply tricks directly to your profiles as you listen and chat about your challenges with like-minded people during lunch.
6. Venue: The Boston BEST Practices conference will be at New England Aquarium and in Seattle at the Seattle Art Museum - venues specifically chosen because they give you open spaces to think creatively. We have intentionally scheduled space into the agenda to allow you to wander, enjoy and dream.
7. Training: If you’re looking to make it official, the Google Analytics Individual Qualification test is an important milestone when building your GA resume. Our preparatory course is a full day of in-person training time following the conference, led by me.

 7.2.    Discount: And last, but definitely not least, we have a discount just for you! Use discount code BESTAnalyticsBlog for a 20% discount off the conference pass at either our Boston or Seattle conferences this fall.

And don’t forget to check out other BEST Practices conferences as we storm the country. We’re headed back to San Francisco in the spring of 2014 - don’t miss out!

To keep up to date on what’s coming, follow our team at @analyticspros and @BEST_con to hear about the latest speakers, locations and events.

We hope to see you in Boston and Seattle!

Posted by Caleb Whitmore, Google Analytics Certified Partner @ Google Analytics Blog

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3 Places to Source Data Beyond Google Analytics

With big data seemingly on everyone's minds, the question is no longer, "Should we use big data analytics to guide our marketing strategies?" but rather, "How can we best use big data to guide our marketing strategies?" For many, the answer to that second question is clear: Google Analytics, end of story.

There is no question that Google Analytics provides a wealth of invaluable tools. With it, we can easily create multiple dashboards and add widgets galore. We can use it to understand our worldwide stats and to figure out what our best (and worst) content is.

However, perhaps because Google Analytics is so competent at helping us make sense of our data, many in the marketing world get a little complacent and fail to think outside of the Google box.

Innovation is the name of the game in big data, and not taking advantage of all of that innovation in the form of tools outside of Google Analytics means marketers miss an important opportunity to gain insights from multiple platforms. Below are some tools outside of GA that can help you make sense of data and develop strategies that are responsive to it.

1. Followerwonk

Twitter is a powerful marketing tool, but too often marketers fail to use it strategically and ask questions such as:

• Who are the most influential though leaders in my business niche?
• Are any of them of following me?
• Do any of my followers know any of those thought leaders?
• When is the best time for me Tweet if I'm looking for shares?

These questions can help get your content in front of thought leaders and increase audience engagement—key components for a successful Twitter campaign. However, answering those questions requires analytic help beyond Google. Luckily, there is Followerwonk, a powerful segmentation tool that can help you use your Twitter following strategically and effectively.

Use Followerwonk to identify prominent thought leaders in your niche, compare your follower stats with those of a competitor, and analyze your followers' behavior on Twitter. When you use even the free version of Followerwonk to analyze your followers, you can unearth a data goldmine, including:

• Social authority scores
• Follower counts
• Frequency of tweets
• Total tweets
• Most active hours
• Locations
• Retweet stats

This data can point you towards individual influencers in your niche, but it can also give you a holistic view of when your followers are active and the likelihood they'll retweet your content—making your campaign more likely to succeed than if you have just tweeted blindly.

Follerwonk Case Study
Ben Folds, of the band Ben Folds Five, had over 500,000 followers, but very few of them were actually converting.

Some social media analysis with Followerwonk quickly shed some light on the issue. It turned out even though he had all of those followers, over half of them hadn't tweeted in over a month. Further, 78 percent of those had fewer than 499 tweets to their names. Finally, most of his followers were in an entirely different time zone, which meant he wasn't tweeting when his followers were actually on Twitter.

This data was used to determine that while on "paper," Folds may have had 500,000 followers, in reality he had maybe 30,000 active followers. This information can then be used to develop strategies optimized to reach active followers and connect with the people who really wanted to engage.

2. Tag Manager

Tag Manager bills itself as the solution for busy marketers who don't want to spend their time "bugging the IT folks," which is a pretty good sell. This tool allows you to easily add and update tags yourself without getting involved in all the coding.

If you don't know, you can add tags to get a better look at things like web traffic to different parts of your site, visitor behavior on your social media channels, and A/B testing data, for example. And note, you can use these tags in other platforms than just GA.

Simply put, while you need tags in order to understand what is really happening with your sites, bad or duplicate tags can skew your results and fatally slow down your load time. This tool aims to provide a seamless and efficient way to manage and create new tags so you can spend more time analyzing data and implementing responsive strategies.

Tag Manager Case Study
Brazilian fashion retailer dafiti was managing more than 100 tags across their various sites. This caused a slew of problems, but the two most vexing problems were

• All of those tags were dragging down load time.
• IT staff was spending too much time responding to tag-related issues.

The company brought in Tag Manager to streamline their tagging system. First, they migrated all of their tags to one central location, which helped with load time. Currently, it is the tool and not the IT folks, who manage those 100 tags, which means that IT can focus on other issues, like site development.

3. Fliptop

Marketers are always looking to narrow down target markets so they can create hyper relevant and focused campaigns. Fliptop can help with that process: it's a social analytics tool that helps marketers integrate social data (demographics, identifiers, social profiles) in order to better segment and target customers.
While marketers have tended to segment audiences along sociographic lines (income level, political affiliations, gender), Fliptop allows you to be more thorough in your segmentation, so you can use groups relevant to your specific business.

"Fliptop helps brands understand who their subscribers are, what the overlap is between their Twitter, Facebook and email subscribers, and who is most engaged socially with their brand," Dan Chiao, VP of Engineering at Fliptop, explained.
Knowing who is most engaged allows marketers to reach out to main influencers, prioritize audiences, and then group them into relevant lists.

Fliptop Case Study
Pardot, a B2B marketing automation service, wanted their marketing clients to have the ability to integrate their existing email lists with public social data, so they could:

• More accurately segment and personalize tough points.
• Create new channels through which they could reach out to target audiences.

To resolve this, Pardot used the Fliptop API to integrate social data with email lists for their clients. The results? In less than six months after integrating Fliptop, Pardot's customers performed over 10,000,000 social lookups. Not only that, but the number of Pardot's customers who subscribed to the premium service grew by more than 20 percent.

The Takeaway

For a long time, it seemed like big data was a treasure trove only the largest and most resource-rich companies could mine. However, times have changed and big data analytics is no longer out of reach for the rest of us. While Google Analytics has been a boon to marketers starting out in big data, we need to take a look at what tools are available and decide which tools will present us with the best information about our audiences.

For more ideas of Google, specific products to check out for marketing functions, check out Mike Tekula's post over on Moz.

Article Post @ Search Engine Watch

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