But that’s OK, I use data alerts to stay on top of my data even if I can’t check analytics every day. Are you using alerts?

If you’ve never used Google Analytics alerts they’re fairly simple to set up. You can find them in the Profile Settings.

There are five things that you need to do to set up an alert:

1. Choose a profile to apply the alert to.
2. Select how often you want to monitor the data (daily, weekly or monthly).
3. Identify the segment of traffic you want to monitor (i.e. which group of visitors, like visitors from a particular campaign or geographic region).
4. Choose what metric you want to monitor (Revenue, Visits, Time on Site, etc.).
5. Set a threshold for the alert meaning how much does the metric need to change to activate this alert (ie increase, decrease, etc.).

I divide my alerts into two groups: those that insure I have good data and those that measure the performance of the business. This post deals with the former: alerts that will keep your data in tip-top shape.

Alert #1: 10% Daily Traffic Drop

This first alert is simply there to make sure that I’m collecting data. I’ve noticed, for my site, that my traffic usually never drops more than 10% for a given day when measured week-over-week. So if I see a drop of more than 10% I know that something happened and I need to investigate more.

A 10% traffic drop alert.

Alert #2: Flatline! i.e. No Data

This is a generic alert that identifies when a metric goes to zero. I can’t tell you how many times a client tries to analyze data at the end of a month only to find a data issue. This commonly happens because not every metric is analyzed every day, some metrics are reported monthly.

But I don’t want to wait until the end of the month to find a problem.

So for almost every important metric I will create a daily alert to insure that I’m getting data. Here’s an example alert that monitors an event.

A Google Analytics Alert that monitors an Event

Alert #3: Daily Error Pages

Another metric I like to monitor is error pages, more specifically 404 errors. I want to know if any of my content is generating an error for my readers. So I created a little alert that will alert me when the number of 404 pages is greater than 0.

Monitor 404 pages, and other website errors, with an alert.

Obviously you can change this alert to monitor almost any type of website error, it depends on which errors you are tracking with Google Analytics. The key is that you need to be able to identify your error pages in a Google Analytics report.

As you can see above, my error page has a unique URL (404.html) and a query parameter that identifies the page that was missing. You may need to use a virtual pageview or an event to track your error pages. Once you do you can create an alert.

Alert #4: Non-Domain Traffic aka The Poser Alert

The hostnames report in Google Analytics is a handy little report. It shows the hostname that is in the location bar of the visitor’s browser. On numerous occasions people have ripped off borrowed my content without my permission. They just copied my source code and posted it on their own domain.

I know, classy.

This alert will automatically let me know if my account is getting data from any domain other than my own.

The "Poser" Alert will let you know if someone is poaching your content.

In some cases this alert actually detects something good! I regularly see the hostname translate.googleusercontent.com, which is used when popele use Google Translate to translate the content on my site.

A note from your data therapist

All of these alerts can help. But you’ll still have inaccuracies in your data. The idea is to keep them to a minimum. If you try to eliminate all errors 100% of the time you won’t do anything else. It’a almost impossible. Do the best you can.

If you do have some data issues, and you will, you’ll have to spend some time resolving them when you do your analysis.

Save Your Ass With Google Analytics Data Alerts is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Adding Business Data to Google Analytics Data
2. Google Analytics Real Time: Real Time Data for Real Time Decisions
3. An Analysis of My Data

After the talk someone came up to me and asked if I could share more details on the dashboard. So here they are!

My goal with this dashboard is deep-dive on the mobile segment of the business: to focus on the business objectives (conversions), key actions that could lead to conversions AND ancillary data about the mobile experience. This will give us a wide range of metrics that provides a deep understanding of the mobile experience.

This is not a data puke.

Before we begin, some assumptions about the business that will make it easier to build the dashboard.

• This is an ecommerce business and revenue is queen!
• The business has launched an ecommerce website in hopes of diring more revenue via mobile
• There are a number of mobile marketing campaigns that are running and it is critical to measure their effectiveness
• The mobile site is ever evolving and the business is always looking for information on how to improve the site

A dashboard is a great way to pull all of this information together. Could you use a custom report? Sure.
But the dashboard does include some nice (but VERY basic) visualizations.

Here it is, the mobile dashboard.

Mobile Ecommerce Dashboard for Google Analytics

The key to creating tis dashboard is the filter option built into each widget. I’m basically segmenting each widget to include only mobile traffic. It’s not that hard to do, just set the Dimension to Mobile and the value to ‘Yes’. (The Mobile dimension is a yes or no flag.)

Filtering a Google Analytics Dashboard Widget for Mobile

That’s it. The widget will only contain data specific to mobile.

Now that we know how to manipulate the widgets so they only include mobile data it’s just a matter of putting the most appropriate widgets on the dashboard.

I’ve divided the mobile dashboard into four sections:

1. Revenue Measurement (outlined in green above)
2. Campaign Performance (outlined in red above)
3. Mobile Device Information (outlined in orange above)
4. Content Performance (outlined in yellow above)

Let’s look at each section.

Revenue, Revenue and Revenue!

The first section of the dashboard deals with revenue. Surprise! There’s not much to explain here. This is an e-commerce site and revenue is their key success metric. You could easily change this to conversion rate if you’re not an ecommerce site. I like the little spark line that shows me a trend.

Google Analytics Mobile Revenue Widget

Now this is where things get interesting, the next widget is Mobile Revenue vs Non-mobile revenue. This is cool if you want to see how mobile revenue compares to overall revenue.

Mobile Revenue vs. Non-Mobile Revenue

The way this widget is a pie-chart widget is to group the metric, in this case revenue, but the Mobile dimension. Like this:

Grouping a Pie Chart Widget

Channel & Campaign Segmentation

Next we continue to look at revenue but now we’re segmenting it my marketing channel. A bit more advanced, but very, very insightful.

This fictional company is leveraging a number of marketing channels, so let’s segment the revenue by medium to determine which ones are generating revenue.

Mobile Channel Revenue

Drilling a bit deeper we can include a table of the top 10 campaigns to quickly see which ones are successful and which ones are not. Again success is measured based on revenue. But if you are not an ecommerce site you can change the widget to measure almost any goal conversion.

Mobile Campaign Performance

Notice I’ve also included Bounce Rate in this table. This makes it easier for me to understand if the poor performance of a campaign might be due to the initial experience the visitor has on the site.

In this case every campaign has $0.00 and a 100% Bounce Rate. Not so good. Time to rethink my landing page experience.

Don’t forget, if you’re using Google Analytics you need to use Campaign Tracking to accurately track marketing activities.

Device Information

In addition to our key business metrics, let’s include some usability metrics that will help guide future development of the site. In this case, because we’re dealing with mobile, let’s include some device data.

Mobile Device Revenue

I know… not another pie chart. But it’s a fast way to show which devices are driving revenue on the site. 38% from the iPad! Maybe we should focus on the iPad user experience?

Just to provide a little context, let’s add a table with the top mobile devices.

Mobile Device Traffic and Bounce Rate

The table helps us understand two things. First, what are the most popular devices that people use to access our mobile site? This information is critical for future development work. Second, I’ve included bounce rate in the table. This metric will make it easier for us to determine if users of a certain device have trouble accessing the site.

Popular Content

The last part of the dashboard deals with content. I put the mobile site bounce rate just to keep it at the top of my mind. It’s basically useless without some segmentation, but good to keep an eye on.

Mobile Website Bounce Rate

Let’s segment it by landing page using a simple table widget. And to add more context, let’s add the number of Entrances for each landing page. Now I can see how popular a landing page is along with the bounce rate. Popular landing pages with really high bounce rates suck.

Mobile Landing Page Bounce Rate

Now let’s see what people actually like to read or interact with on the mobile site with the top mobile content. Using two simple metrics, pageviews and time on page, it’s easy to see what people like. And if I know what’s popular I might be able to promote it in new ways.

Most Engaging Mobile Content

Wrapping Up

I know that there are some serious shortfalls with the Google Analytics dashboard. BUT, let’s not look past certain things that are helpful. You get to add almost any metric and dimension. You can segment that data AND you can add some (VERY basic) visualizations. All in all, it doesn’t suck. Too much.

There are two things I wish the dashboard had:
1. The ability to add a simple text area where I can add my analysis and thoughts
2. The ability to add external data, like ad spend

Post Script

Google recently hosted a webinar with Avinash Kaushik promoting mobile marketing and, of course, measurement. You can watch the entire video below. It’s about an hour but well worth it.

Avinash also included a link to a custom report for mobile measurement. A nice compliment to the dashboard above.

Now it’s your turn. What would you add to a mobile dashboard?

Building a Mobile Ecommerce Dashboard in Google Analytics is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. 5 Google Analytics Custom Variables for Ecommerce
2. New GA Feature: Custom Dashboards
3. New GA Feature: Sticky Filters

Flow Visualization report in Google Anlaytics

For a long time click path analysis was not really possible in Google Analytics. Sure, we had the Navigation Summary and Entrance Paths reports, but these were very limited. This was by design. Most click path reports, no matter the analytics tool, has little to no value. They usually show 9,845 different paths to conversion. How does that help?

The new Flow Visualizations reports hope to remedy this problem and make it easier to understand visitor behavior regarding how they move through content.

Nodes: Foundation of Flow Visualizations

All flow visualization reports are built using nodes. Nodes are groups of pages. The cool thing is that the nodes are automatically created using an intelligence algorithm. For example, nodes will automatically group the same page that may only differ by a couple of query parameter.

Don’t worry, you can create your own nodes, and I’ll show you how to do that in a minute.

The new reports show visitor flow through nodes, and where people drop out of the flow (ie leave the site). The really important thing here is the visualization AND our ability to manipulate the visualization. So if you a specific issue or scenario that you are analyzing it’s easy to drill down on the scenario you want. But the visualization also supports ad-hoc analysis.

These new reports are in the Home > Intelligence > Flow Visualization section.

On to the Visits Flow report.

Visit Flow Report

The Visit Flow report is a nice refresh of the traditional click path report. Rather than looking at clicks from one page to another, we’re seeing visitors moving between nodes. The ‘story’ starts on the left side of the visualization where you can choose a to view a starting segment, like Campaign, Traffic Source, Country, Region, etc.

This is AMAZING! Now you can easily segment traffic through a site based on various dimensions of data! The next time someone asks what campaign traffic did, now you can provide some very detailed flow information.

Connections in blue represent the number of visits that move between the nodes.

Connections in red represent the drop off from a particular node.

How easy is that to understand? The brilliance is the simplicity.

Let’s say you want to focus on a particular segment of data, like the state of Texas. Just choose a dimension from the drop down, in this case Region. Then click on the Texas node at the far left and choose ‘Highlight traffic through here’. The path of traffic from Texas will appear a bit darker.

View the path for a specific dimension of data in the Flow Visualization report.

I know there can be a lot to take in. If you are a bit confused, then perhaps we should reduce the number of paths that are visible. Use the ‘Connections’ slider at the top to view more, or less paths and make the analysis easier.

Alter the number of paths visible in Flow visualization

The reason why click path reporting has sucked for SO LONG was the vast amount of data stuffed into a really crappy display. Google is trying to solve that using this new visualization, the Dimension drop down AND the Connections slider. You have control over the amount of data you are looking thus making analysis area.

Using this interface you can identify where people come from, follow them to various pages and evaluate the bounce rate, and then see what they look at after the landing page.

The interactivity is just awesome.

[ By the way, you can scroll to the right by dragging the visualization when you see the fist. You can also add more steps by clicking on the arrow at the far right. ]

Let’s say you want to learn more about a particular node. Just hover over a node and you’ll see something like this:

Node details in Google Analytics Flow Visualization

The first thing we learn is how many pages are in this node. Remember, an algorithm initially created this node. We can also see how many dropped off and how many moved on. Very useful.

Now, perhaps I want to understand this page a little better. I can click on the node and choose ‘Explore Traffic through here.’ That brings us to the next report

Navigation Flow Report

The Navigation Flow report is similar to the old Navigation Path report in Google Analytics. Now you can see the nodes before, and after, your chosen node.

Google Analytics Flow Navigation Report

Let’s talk about how we can create and edit your nodes.

Click on the small gear at the top of the node. You can use a reg ex, or other basic pattern, to group a set of pages together into a node.

For example, if I’m a publisher, I may want to group all my Sports pages together into a Sports node, like this:

The Name field is the name that will be displayed in the report, it’s nice and human readable :)

The value here is you can group your content together so you can analyze your site your way.

Ecommerce people, want to understand the flow of traffic through your product pages? Group them together in a node.

Publishers people, want to see where people go after the last page in all your articles? Group those pages together in a node.

Another really cool feature of the Flow Visualization reports is our ability to segment the entire graphic. Use the drop down at the top of the report to apply a segment, like new visits, return visits, etc.

Apply a segment to a Flow Visualization

Combine that with the dimension drop down and I can slice and dice the behavior of different groups as they move around the site. Crazy awesome.

Goal Flow Analysis

In addition to the basic flow reporting, there is also a Goal Flow report that provides insight into your conversion paths.

Goal Flow report in Google Analytics. Click to enlarge.

Again, you can choose a dimension of data, here I chose the medium, and view how that traffic moved through your funnels. I hope you have a funnel configured!

NOTE: At this time the Goal Flow report only works for URL based goals and funnels. Events will follow soon.

Notice the loops? Those show traffic that ‘loops back’ to other steps. I think this is a HUGE improvement over the existing Goal Funnel reports. It’s much easier to see holes in the funnel (drop offs) and behavior (looping).

Is this just the beginning?

Hopefully this gives you a basic idea of how the flow visualization reports work and how you can manipulate them. The key here is that you can segment the data to isolate the behavior that you want to investigate.

I’ve got to say, I think this is going to have a much bigger impact on Google Analytics than most people know. Sure, these reports are sexy. And we’ll start to do more path analysis.

But this visualization of data is the key change. I believe we’re going to see Google include more creative data visualizations to help aid analysis. That’s truly exciting.

Path Analysis in Google Analytics with Flow Visualization is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Event Tracking Pt. 3: Reporting & Analysis
2. Google Analytics Campaign Tracking Pt. 3: Reports and Analysis
3. An Analysis of My Data

The NEW Google Analytics Real Time Reports

Google Analytics now contains a series of real-time reports that measure what’s happening on your site in real time. These reports will roll out in the next 1 to 2 weeks.

I’ve long railed against real-time data. I’ve said that businesses don’t need real time data. It’s very hard to action on time data. I’ve said this on the record!

But here I am, with my tail between my legs, to admit that some businesses really do need real time data. I was wrong. I can absolutely see the need for real time data.

Chartbeat Real Time Report

And if you still need convincing look at the success of tools like Chartbeat. They provide some pretty awesome data that helps business make important decisions WHEN those decisions need to be made.

Real time data can be very helpfull in the following business scenarios:

• If you are a publisher, you often need real time data to understand what content is popular right now, so you can optimize the placement of that content, or publicize that content, to optimize ad revenue.
• If you are a retailer, you might want to understand, in real time, the launch of a new campaign. This is especially useful if you are using a channel, like social media, that has a very immediate impact.
• If you are holding a physical event, you might want to understand, in real time, how people in that location are using your website.

To fill this analysis hole Google Analytics now has a Real Time section of reports, creatively named Real Time. This series of repots offers a subset of data that is processed in real time, literally every second. You can see who’s on your site, how they got there and what they’re looking at in real time.

The data covers three dimensions:

• Geographic locations
• Traffic sources
• Content

I know, there’s no conversion data. Sucky. BUT let’s consider how much data is getting processed every second. Seriously, that’s a lot of data!

IMPORTANT: One thing to keep in mind is that the Real Time reports are NOT filtered. Even if you have a profile filter applied the data is not filtered. I guess that requires a bit too much processing power.

The real time reports are NOT real time data for all metrics, only a subset of metrics. But they are pretty good. You have access to real time stats for:

• Visitors
• % New visitors & returning visitors
• Pageviews
• Traffic sources (referrals, direct, campaigns, etc.)
• Active pages

Let’s look at the reports and how they solve the above business cases.

Real Time Overview Reporting

Everything starts with the Overview report. This is mission control for Real Time data and gives you a general overview of what’s happeneing.

The Google Analytics Real Time Overview Report

At the top of the report Google shows a second by second view of pageviews. It then aggregates this data and shows a minute-by-minute view. I know, this view is mesmerizing. Try not to wast too much time watching this.

The top of the report also shows the total number of unique visitors on the site (it counts the cookies). Google Analytics then segments this number to show you the amount of new visitors and returning visitors.

Moving deeper into this report we get information about what’s the most popular content right now, where visitors came from (both traffic source and keywords) and a geographic breakdown of where the visitors are located.

With this one report we’re able to answer the business questions we posed above.

Real Time Locations Report

The location report has basically the same geo data as the Overview report. It still show second-by-second data and a breakdown by Country.

The Google Analytics Real Time Locations Report

One thing that is different is the ability to view geography using Google Earth. Does this offer any additional insights? HELL NO! But it looks sexy. The Google Earth plugin will zoom you from from city to city.

Oooooooo! Zoom from city to city with the Earth View

Real Time Traffic Sources Report

The real time traffic sources is literally a dump of your top traffic sources. Again, not too different than the data on the Overview, the tabular data shows the Medium and Source dimensions.

The Google Analytics Real Time Traffic Sources Report

This is especially handy when you launch a new campaign and want to see how it’s working. Think about when that big tweet goes out and you want to see what’s happening on the site.

Or consider the case where you might have an unexpected spike in traffic. This report will help you understand if there is some referring site that is driving a lot of traffic. We still can’t see if there is a lot of conversions (grrrrrr) but at least we can see traffic.

Real Time Content Report

And finally we have a dedicated real time content report. Again, not much new here. You can view how many active users are viewing a specific page or get an agregate view of pageviews over the last 30 minutes.

The Google Analytics Real Time Content Report

Notice how some of the data rows are shaded green and red? Green indicates a row of data that has increased while a row of data that is red indicates a row of data that has decreased. This is a nice touch to make it easier to see things “move.”

So there you have it. Google’s new Real Time feature for Google Analytics. How do you plan to use this to optimize your business?

Google Analytics Real Time: Real Time Data for Real Time Decisions is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Adding Business Data to Google Analytics Data
2. An Analysis of My Data
3. Event Tracking Pt. 1: Overview & Data Model

For those that have not used custom variables before you can get read Mastering Custom Variables for overview.

Now on to the custom variables!

Tracking Coupon Codes and Promotional Codes

I think this is a pretty obvious use of custom variables. If you sell something you probably run various promotions. And you need to track these promotions to see how they perform. Some promotions can be tracked using campaign tracking. I’ve seen lots of people use the utm_content parameter to identify the promotion in a marketing campaign, like an email. But a custom variable works just as well.

When coming up with a strategy think about how you might scale this as time goes on. Do you want all of your promotional codes aggregated together under one variable? You could do something like this:

_gaq.push(['_setCustomVar',1,'PromoCode','<PROMO CODE ID>',3]);

Or you could get fancy and use different custom variables to bucket groups of promotions, like seasonal promotions. For example, if you lots of promotions during the holiday season you might want to create a custom variable named HolidayPromos and then a unique name for each of the codes, something like this:

_gaq.push(['_setCustomVar',1,'HolidayPromo','Free2DayShip',3]);
_gaq.push(['_setCustomVar',1,'HolidayPromo','FreeWrapping',3]);
_gaq.push(['_setCustomVar',1,'HolidayPromo','10perOff',3]);

The above code would need to appear on your receipt page. And remember, the slot, or index, in the code above may be different for you. It all depends on your use of custom variables.

You might be wondering why I decided to go with a page level custom variable here. Remember, Google Analytics will sessionize a page level custom variable. So even though the custom var will only fire on the receipt page the data will be applied to the entire visit.

Tracking Payment Method

Remember, we study visitor behavior to understand the impact on business. One of these behaviors is how people pay for a purchase. Is there a difference between a visitor who pays with a credit card vs one who pays with PayPal? Does one spend more, on average, than the other? You’ll never know unless you capture payment type and review metrics like average order value and conversion rate.

To capture payment type use a page level custom variable. The resulting GA code will look something like this:

_gaq.push(['_setCustomVar',2, 'PaymentType','<NAME OF PAYMENT>',3]);

Don’t forget to replace <PAYMENT TYPE> with the customer’s payment method.

Tracking Shipping Method

Like payment method, it’s interesting to see what shipping method people choose with various products. Why? Perhaps people who buy certain products choose certain types of shipping. If so, maybe you can build a new promotion using this information. Could there be no insights here? ABSOLUTELY! But you’ll never know unless you have some data and do a bit of analysis.

_gaq.push(['_setCustomVar',3,'CustType','Repeat',1]);

Tracking Repeat Customers

I remember reading Eric Peterson’s book Web Analytics Demystified a looong time ago. Besides being one of the first books on analytics it was exceedingly actionable. One of the ecommerce key performance indicators Eric talked about, and rightfully so, was the repeat-buyers.

The behavior of repeat customers is different than first time customers. This segment of customers usually takes less time to purchase due to a knowledge of your products and services. Normally it costs you less money to get these people to convert. So it’s a good idea to understand what marketing they respond to and how they use your website.

To track repeat customers in Google Analytics you must use a visitor scope custom variable. Remember a visitor scoped custom variable persists on the visitor’s computer as a cookie. The trick is when you set the custom variable.

Most people think you can set the custom variable when the transaction happens, like this:

_gaq.push(['_setCustomVar',4,'CustType','Repeat',1]);

But in reality this will not work. When you set a visit level custom variable the value gets applied to the CURRENT visit and all future visits. So you need to wait until the SECOND purchase before setting the above custom variable. Then it should work just fine.

[UPDATE: Elizabeth Brings up a good point in the comments. This method will only work if the visitor comes back and makes a second purchase on the site. You can tweak the above logic and set the custom variable on the visitor's return to the website, rather than when they make a second purchase. While this is not perfect it is a workaround.]

I should note that this is an AWESOME custom variable to use in an advanced segment. Actually, they’re all great to use in Advanced segments, but segmenting repeat buyers is especially useful

Purchase History

This is where things get a little more complicated. Tracking things like purchase history requires a bit of configuration on the server side, meaning you or your nerds need to create some code to categorize customers based on the number of purchases they’ve made in the past. Rather than track every single purchase I prefer to bucket the purchases, like this:

• 1 to 3 purchases
• 4 to 6 purchases
• 7 + purchases

You need to have the logic on the server to review the custom’er purchase history and set the custom variable accordingly. The GA JavaScript will look something like this:

_gaq.push(['_setCustomVar',5,'PurchHistory','1-3',1]);

Now you’re probably thinking that there is some duplication with the previous custom variable, and you’re right. The repeat customer variable is a bit more generic and gives you a quick view of new and returning customers. The purchase history variable is geared towards deeper analysis of customer behavior.

So there you have it, five custom variables for ecommerce websites. This is by no means an exhaustive list, but I think these can help any commerce based business to better segmentation and analysis.

Are you using custom variables on your ecommerce website? If so I’d love to hear how!

5 Google Analytics Custom Variables for Ecommerce is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Mastering Google Analytics Custom Variables
2. Google Analytics Custom Variables Overview
3. Google Analytics Configuration Mistake #2: Query String Variables

During our presentation Amy announced an amazing new feature called Multi-Channel Funnels. This awesome feature is a series of marketing attribution reports that will help marketers understand how different marketing channels lead to conversion. These reports are full of strategic and tactical data.

Note: Google Analytics has let us know that the feature called Multi-Channel Funnels discussed in this blog post is in limited pilot. That means that Google Analytics is testing the feature and its usefulness to a small group of trusted testers, and have not made any plans or a timeline for a full launch.

You’re probably thinking, “HOLY COW!” I know, this feature is really amazing. But I want to reiterate, this is NOT a formal launch. There is NO TIMELINE to roll these reports out to GA users.

Multi-channel funnels are completely new. That means a whole set of metrics to measure the interaction of all your online marketing channels. Before we begin I know there are some basic questions you might have:

1. What is the look-back window? These reports provide a 30-day look-back window. That means that Google Analytics will stitch together all the different traffic sources 30 days prior to a conversion.

2. Do these reports include view-thru data? View-through data from other systems, like DoubleClick, is NOT included in this data. The reports will only include data from visitors who visit the site.

3. Is there any attribution modeling? No.

4. Do I need to do anything special to set up these reports? You must be tracking conversions using Goals or tracking ecommerce transactions. But to really make these reports meaningful you should also be tracking your marketing campaigns with Campaign Tracking.

Let’s start with the beginning. Multi-channel funnels are part of the Conversion reports in the new GA v5 interface. There are 5 new reports and all are very useful.

One of my favorite new reports, and one that I’ve been asking for, is the Path Length report. This report shows the number of interactions that leads to a conversion. This is the next version of the Visits to Transaction report from the old Google Analytics.

The great thing about this report is that you can now choose to view the path length for ANY conversion, not just transactions. Use the drop down box at the top of the report to choose any conversion.

What are the insights? Now you know how many interactions you need to have with a visitor before they convert. If it takes a lot of interactions you can engage in different types of activities to engage prospects.

But let’s dig in and get more details about various marketing activities and where they fall in the funnel. That’s the job of the Assisted Conversions report.

This report shows a number of new metric, all your traffic sources, grouped by source/medium. The new metrics are:

Assisted Conversions: This is the number of conversions that contained this source/medium combination in the last 30 days.

Last Interaction Conversions: This is the number of conversions where this source/medium was the “last touch.”

Assisted / Last Interaction Conversions Ratio: This is the simple ration of the above two metrics.

The Assisted / Last Interaction Conversions Ratio is THE KEY new metric. I’ve come up with my own name for this metric: the Exposer to Closer Ratio. It’s way more catchy, don’t you think? This single number will tell you which traffic sources are Exposers, meaning they spread your brand message, and which ones are Closers, meaning the get people to convert.

Marketing activities that have a higher Exposer to Closer ratio are upper funnel activities. They get you prospects.

Marketing activities that have a lower Exposer to Closer ration are lower funnel activities. They close deals.

So if you Path Length report shows that you have a longer sales cycle, that takes a lot of interactions, you need to push upper funnel activities. What kinds? Look for marketing activities that have a higher Exposer to Closer ratio and start pushing those!

There is another view of this report that is actually very useful. Google has created traffic groups which bundle certain kinds of traffic together. For example, all referral traffic from Twitter and Facebook will be grouped as Social Media.

There are some cool features of the Assisted conversions report. Notice the Custom Dimensions item at the top of the page? Google will let you group your traffic together according to your marketing activities.

I think one report everyone wants to see is the Top Paths report. This is a list of every combination of marketing activities that led to a conversion. This is the one that people have been asking for.

Let’s just soak in the beauty of this one for a minute….

While I too like this report, it can be a bit overwhelming. Like click-path reporting, there can be a LOT of different marketing paths. This report will NOT show you the ideal way to mix and match marketing channels. But it will help you drill into your channels and uncover details. For example, we can use the tools at the top of the report to focus in on keyword paths.

The last report I’d like to share is a very strategic one. The Overview report in the Multi-Channel Funnel section actually allows you to mix and match different marketing channels and see which combinations result in the most conversions.

To me, this is the most advanced feature. This is the beginning of multi-channel modeling: a way to help marketers determine spend across multiple channel. Wow.

I’ve got a lot more to write about search funnels. I had to hammer them pretty hard last week to put together some slides for AdTech.

I’ll leave you with the official videos from Google:

Google Analytics Multi-Channel Funnels is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Google Tackles Campaign Attribution with AdWords Search Funnels
2. New Google Analytics Goals
3. Tying clicks & content to conversion in GA

One of the major paradigm shifts of the new GA is the move to more customization. Just look at the new custom reports and the new dashboard. Google wants to move away from puking the standard reports and let us create our own report suits. I can live with that.

Why Use Custom Reports

Simply put, custom reports help you, the analyst, save time. Why bother using the standard GA reports when you can create a report that contains the exact information that you, or some other stakeholder, wants?

Remember that custom reports are build using Dimensions and Metrics. Dimensions are the attributes of your visitors and the visits they create (i.e. keyword, traffic source, etc.). Metrics are the actual data that is collected (things like revenue, conversion rate, visits, etc.)

So what custom reports should you create? That’s a really hard question to answer. Custom reports, are, well, CUSTOM. They’re specific to your business and your reporting needs.

Here’s one tip: focus on outcomes. What are the business objects you’re trying to analyze? Pull metrics like conversions or revenue into your custom reports to get some idea of how your business is doing. Then look at the metrics that support outcomes.

For more juicy information about custom reports you can read Avinash Kaushik’s excellent post about custom reports you should check it out. It will serve as a great roadmap for creating your own custom reports.

Now on to the changes!

Custom Report Filter

The first thing you’ll notice about the new custom reports interface is the ability to apply a “sticky” filter to your custom report. This filter is actually the same as an the filter that appear at the top of each standard report.

I like this feature a lot. Many times someone will ask for a custom report that needs to be segmented or filtered.

Let’s look at a real life example. I often get requests from content owners for a report about their pages or sections of the site. Normally I would do this using the Site Content > Pages report with an in-report filter.

But now I can save a couple of steps by creating a custom report and applying a custom report filter. My buddy @sondra is really excited for this feature. She does a ton of content reporting.

Different Dimensions Per Tab

Like the old version of custom reports you can still add multiple tabs of data. BUT, unlike the previous version you can change the dimensions on the different tabs! This is a huge advantage and truly makes custom reports customizable.

Now I can mix and match dimensions and metrics to create a custom report that has all the data I need.

Here’s an example. Let’s say I need to keep an eye on content performance, some marketing campaigns and various AJAX widgets on the site. I can now combine all of this data into a single report.

I can create one tab for site content and use a dimension like Page. I can create a second tab for marketing campaigns with a Dimension of Campaigns and I can create a third tab with The Event Category/Action/Label Dimension.

Another new part of the tabs is the ability to add Metric Groups. This makes it easy to add A LOT of metrics to a report BUT keep them organized. Each report tab can have it’s own set of Metrics groups. This provides an almost infinite way to jam all sorts of data into a report.

Data Type

Continuing down the custom report setup form you’ll notice the next big change: the data type. I’m excited about this feature. A normal custom report has a drill-down, or explorer, setup. You explore the data in your custom report by clicking on a row of data and drilling down.

For example, I might create a custom report that “nests” marketing media below city. To explore the data I would need to click on a city to view all of the marketing media.

But with a Flat Table all of the data is right there in one view. No more clicks!

All you need to do to create a Flat Table is choose “Flat Table” and select a couple of dimensions for your report.

And here’s what the data would look like:

This view is especially useful if you’re going to export your data for use in another tool, like Tableau.

[For all the nerds in the group, this is the same way that data comes through the API.]

There is one drawback to the Flat Table view; you can only use two dimensions in a Flat Table view of the data. But it’s a start!

To Be Continued

You may have noticed that there are a few things missing from the new Custom Reprots.

First, there is no longer the ability to share custom reports. While I don’t know their exact plans, I can pretty much guarantee that Google is not taking away this functionality. They’re probably just changing it.

Second, there is no longer a way to export a custom report in PDF format. In fact you can’t export ANY report in PDF format. Again, I think this is just a feature that will be upgraded soon. So stay tuned!

There you have it. MUCH more customizable reports in Google Analytics. How do you plan to use them to make your life easier?

Understanding Google Analytics Custom Reports is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Find Out When Your Campaigns Suck with GA Custom Reports
2. Understanding the New Google Analytics Interface
3. Making Google Analytics Content Reports more Readable

Companies should track how people react to these campaigns and which ones are most successful. But what’s the best way to do this with Google Analytics?

Some people use the standard campaign tracking to track internal campaigns. THIS IS INCORRECT AND SHOULD NEVER BE DONE. Using the standard campaign tracking for internal campaigns will cause problems with your source data. So don’t do it!

There are a few correct ways to track internal campaigns. You could use Event Tracking, Custom Variables or Virtual Pageviews. But I like to use GA’s internal campaign tracking tool.

What? You’ve never seen or used the GA’s internal campaign tracker? It’s in the profile settings and it’s called Site Search tracking! Did I fool you ;)

Site Search can easily be configured to track internal campaigns. Let’s walk through the steps to set it up and then the data and analysis.

Step 1: Create a New Profile

Because we’re using Site Search for an unintended purpose it’s best to configure these settings on a new profile. It’s not possible to use Site Search for both tracking internal campaigns and internal site search within the same profile. You need to have a separate profile to track internal campaigns.

Step 2: Tag your Internal Campaigns

Once you’ve created your new profile it’s time to tag your internal campaigns. Internal campaigns need to be tagged in a similar manner to external campaigns: you need to add query string parameterrs to your internal ad.

However, unlike external campaigns you do not use the standard link tagging parameters (utm_campaign, utm_medium, etc.). You get to make up your own parameters!

You can use one or two parameters for internal campaign tracking and you can name then anything you want. The reason you can use one or two parameters is that GA’s site search configuration uses two parameters, one for the search phrase and one for the search category.

Whatever you choose, make sure the parameters are not used for anything else.

TIP: Check your Top Content report for a complete list of your site’s query string parameters. Verify that the parameters you create are NOT in this list.

For the sake of this post I’ll use the parameter icn (shor for internal campaign name). This parameter will holds the name of the internal campaign. I’m going to use the following format for the value of the campaign name parameter

icn=[internal-campaign-name]

I mentioned that you can use two paramters. You don’t need to use two, but GA’s site search can be confiugured to track the internal site search phrase and a site search category. We’ll use the category paramter to track the internal campaign name.

I’m going to name the second paraeter ici (short for internal campaign info). Again make sure the parameter you’re using does not already exist. This second parameter let’s me collect details about the ad the visitor clicked on and the location of the ad.

Here’s a basic format:

ici=[ad-creative]_[location-on-the-page]

You can see that I’m stuffing a lot of information into the parameter. You can put whatever you want and GA will gladly suck it in. By adding more information we’ll get a granluar view of how the internal campaigns perform and which locations and variations lead to tbe most conversions.

If you don’t have different types of internal ads, or just don’t care about this level of detail, then you can ignore the add internal campaign info parameter. It blank, it’s up to you!

Now you need to define the values for all the ads. Thic can get messy if you’re running a lot of internal campaign. But you can do it, just be organized! Use a spreadsheet to keep track of all the values you use.

Once you’ve got al your parameters it’s time to tag your links. The exact process depends on your site. You may need to change static links, like this:

< a href=”/internal-page.php?icn=2010-spring-sale&ici=stubs_home-roller >

Or if you have complicate flash ads you may need to get inside the Flash code. It depends on your site.

The bottom line is when somone clicks on an internal ad you want to see your internal campaign parameter on the next page. If you don’t see the parameter in the URL then you did something wrong.

You can use the sample spread sheet below to track the different parameters you use for your internal campaigns. The spread sheet also has a formula in column D to automatically add the parameters to your URLs.

NOTE: There is an iFrame in this post. If you can not see it, you can view the original post here or view the Google Spreadsheet here.

Once youe’ve got the parameters added to your links it’s itme to configure the Site Search settings.

Step 3: Configure Site Search Settings

Remeber, we’re configuring these settings on a new profile so we don’t break the site search in our main reporting profile.

Site search has three settings. First, turn site search on.

Next, tell GA the name of the paramter that holds the site search phrase (in this case it’s out internal campaign name) by adding the parameter to the ‘Query Parameter’ filed.

Next, choose Strip Query String Parameters. This setting will remove the parameter from the URL after GA processes the data. This is a good idea because it reduces duplicate pages in your top content reports.

TIP: You probably want to exclude your internal campaign name parameter, and internal campaign information parameter, from your other profiles. It can really mess up your pageview data.

If you’re using an internal campaign information parameter configure the Site Search Category settings the same way. Just make sure you use your internal campaign info parameter in the ‘Category Parameter’ setting.

Here’s how the settings look using the parameters from my example:

That’s it! Let’s look at the data.

The Reports

Let’s start by answering a simple question: do people who respond to internal camapigns convert more or less than those that do not respond to internal camapigns? To answer this question use the Content > Site Search > Usage report. Here we can see that there were only eight visits that clicked an internal campaign. Sad! But it’s just test data.

Now let’s drill deeper ad identify which inernal camapigns are most effective. Use the Content > Site Search > Search Terms report. Rather than search phrases this report contains the names of all internal campaigns. Again, what was the response to the campaign? Was it worth the effort? Don’t forget to check the Goals tab and the Ecommerce tabs (if applicable) to measure outcomes!

But let’s drill deeper to understand which ads within those campaigns are working. Click on a campaign name and choose Category from the Analyze drop down.

Now we’re looking at all of the information that we put into the ici query string parameter for this particular campaign name. If we had multiple internal ads we’d be able to differentiate ad placements and creative variations.

Don’t forget to use the Goals and Ecommerce tabs to measure outcomes! This is what most people want to know: did internal campaigns, and specifically which internal campaigns, generated revenue and conversions?

But we can do more. Now change to the Content > Site Search > Start Pages report. Now you can see which page people were on when they click on an internal ad. Again, more insight into where visitors responded to an internal campaign.

And for all those marketing folks that are so concerned with internal campaigns, how about creating a nice custom report and automating the delivery or, better yet, use the Custom Report Sharing feature to share this report with others. People will love this because you can change the wording so it does not say Site Search it says Internal Campaigns Report.

But wait, there’s more! What about using a secondary dimension to view the external marketing campaigns (or sources, or mediums) that drive visitor to react to internal campaigns. Perhaps the extrnal creative has some influence over how visitors react to the internal campaign creative. The data isn’t so hot in the image below, but you get the idea.

And finally, the ultimate in analysis, internal campaign attribution. We can use the Search Term Refinement feature if visitors click on multiple internal campaigns. Google Analytics will track all subsequent site searches, but in our case follow up site searches are actually additional internal campaigns that the visitor responded to. Honestly, I have never found any insights from this type of analysis, but you can do it if you want!

Ok, I’ve officially entered nerdville.

I think you get the idea. By adding all this data you can do many different kinds of segmentation and analysis. More than enough to understand the behavior of your site visitors and how your internal campaigns perform.

Last but not least, I’ll mention that you can track internal campaigns using events and custom variables. But both of those solutions require coding. And that requires working with IT. Using Site Search, in most cases, will not require any code changes to your site.

Tracking Internal Campaigns with Google Analytics is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Tracking Zero Result Searches in Google Analytics
2. Measuring Internal Site Search with Google Analytics
3. Find Out When Your Campaigns Suck with GA Custom Reports

Throughout the discussion it has become clear that the classic first click and last click attribution models that many web analytics tools use are flawed. The problem is no one has come forward with a better solution to the attribution issue… until now.

Google has taken a very low-risk move by tackling campaign attribution for AdWords only. The new AdWords Search Funnel reports help marketers understand which cpc ads people see and click on prior to converting.

If you’re looking for details about the reports and how to use them check out the video below from Google. The new Search Funnel reports have not been rolled out yet so no one has had a chance to play with them. Hence no real description here :)

We’ve long known that people see a lot of different cpc ads during a sales cycle. Avinash Kaushik calls these keywords “upper funnel” keywords. They are used by people that are early in the buying cycle. While many of these keywords don’t always lead to a conversion they help educate a potential customer and move then closer to purchasing a product or service.

Even though they do not directly generate revenue there is some value in bidding on upper funnel keywords.

Up until now we haven’t had many ways to help us understand the true value of upper funnel keywords. Sure, we can use time on site or pageviews per visit to measure “engagement”, but that was a bit of a hack. We can also create all sorts of custom JavaScript to store the first click and last click in a Custom Variable. But again, these are just hacks.

The Search Funnel reports are a well thought out way to understand how people interact with AdWords ads prior to conversion and thus help us understand the ROI of our AdWords spend. The reorts provide insight into which keywords

I think this is a good first step by Google. They took reliable set of data that was just sitting around a data center and created some reports that will help marketers understand the real value of different types of keywords. This is all very low risk for Google with very high potential (read: more AdWords revenue).

But these new reports are also a good test of how users, and the overall analytics market, will respond to Google’s version campaign attribution reporting. Real attribution models are very complicated to create. They involve a lot of data about different types of campaigns (banners, cpc, email, etc.).

[Side note: Why is it that we haven't seen any DoubleClick data in Google Analytics yet? Pulling that data into GA will be critical for real attribution measurement.]

In addition to the data complexities, every business will have their own way to weight certain marketing activities in an attribution equation. For example, some companies may value email more than paid search. This business logic will be difficult to implement. Not impossible, but difficult.

At the end of the day the new AdWords Funnel reports are exciting. But I’m excited to see how Google takes information about how these reports are used and tackles the bigger challenge of true campaign attribution!

Google Tackles Campaign Attribution with AdWords Search Funnels is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Google Analytics Campaign Tracking Pt. 3: Reports and Analysis
2. GA On Site Search Pt. 2: Reporting & Usage
3. Google Analytics Campaign Tracking Pt. 1: Link Tagging

You can now create up to 20 goals per profile in Google Analytics. I can literally hear the applause at eMetrics :)

In addition to expanding the number of goals Google has expanded the types of goals to include ‘threshold’ goals for pageviews per visit and time on site.

I think we all know the importance of tracking goals, so I’m not going to get too deep into why you should use goals. If you’re not using goals you should start NOW!

Let’s talk about this new feature.

Goal Sets

Goals are now organized into four sets. Each set of goals can contain up to five different goals.

Sets have been introduced as a way to accommodate all the new data in GA. In the report tabs, rather than one goal tab there can be up to four goal tabs in a GA reports.

When creating a goal you can place it in any set as long as there is room. Once you place a goal in a set it’s best to NOT MOVE IT. Google Analytics sees this as a NEW goal and does not move the previously captured conversions to the new goal.

TIP: I like to organize goals by business function i.e. put goals that are related together. For example, if you’re a content site, you might create goals for spending a certain amount of time on site (1 minute, 2 minutes, etc.). I would group these goals in a set all related to time.

Goal Types

In the old days a goal was a pageview that represented the completion of some high value process, like a thank you page. Now goals can be based on actions that have nothing to do with viewing a page. Conversions can be based on how much time a visitor spends on the site or how many pages the visitor views.

Time Based Goals

Time based conversions are triggered after a visitor has spent a certain amount of time on the site. To configure a time based goal enter the hours, minutes and seconds that a visitor must spend on the site before a conversion is counted. Once the visitor reaches that amount of time on the site then a conversion is triggered.

What’s interesting here is that you can create a time based goal if a visit does NOT reach a certain amount of time. If you choose ‘Less Than’ Google Analytics will trigger a goal if a visit does NOT reach a certain length.

Why on earth would you measure this? I like to think of ‘Less Than’ goals as ‘Failure’ metrics. We often define success metrics, like Conversion Rate, but rarely define metrics to measure our failures!

Using failure based metrics really packs a punch when you’re talking to co workers or clients. For example, when you configure a failure goal you can easily measure and say, “Did you know that 97% of our traffic does not spend at least 2 minutes on our site? We suck!”

Abandonment rate is another well know failure metrics.

Time based goals can also be very useful if you’re trying to MINIMIZE the amount of time people spend on your site. For example, if you have a support section on your site you may want to understand what percentage of traffic spends a certain amount of time on your site. Long term you can try to reduce the number of visits that are too long.

How about setting up a goal set for various time intervals and then try to move visitors from one “goal” bucket to the next. 10 minutes, to 7 minutes, to 5 mintues… You guys are bright, you get the idea :)

Remember, time based goals can be affected by creating virtual pageviews and events. Both of these activities send data to Google Analytics and can change how visit length is calculated.

Pageview Based Goals

Another new goal type is pageviews per visit. Like time on site goals this this type of conversion is triggered when a visit exceeds a certain number of pages. I can literally hear all the advertisers clapping out there!

Pageviews goals are set up in the same manner as time based conversions. Just specify a condition (greater than or less than) and the number of pageviews in a visit.

Like time goals, pageview goals can also be affected by virtual pageviews. If you’re creating a lot of data using _trackPageview() you need to understand that this can change your overall goal calculation.

URL Destination Goals

The old standby! ‘Traditional’ goals are now called URL Destination Goals. You can still use a regular expression, head match or exact match to identify a page that represents a goal. This functionality has not changed (you can learn more about goals in this old post.)

Now that we have 20 goals we can easily measure all of those micro conversions (RSS subscription, email signup, reaching product page, downloading white paper… etc, etc, etc).

And yes, you can still use a virtual pageview as a URL Destination goal.

Funnels

Google did spend some time tweaking the interface. The old interface always showed 10 steps in the funnel. Now you can choose the number of fields the funnel form displays. You’re still limited to 10 steps in total. This isn’t such a big deal.

But think about the bigger picture. Do we really need funnels if we have so many goals? With 20 goals we can use a goal to represent each stage in a process, rather than a funnel step? So do we still need funnels?

Yes. Funnels provide a nice visualization of critical processes, so I think they are still relevant. Plus, you need to configure a funnel if you want to measure Abandonment rate, a very nice failure metric that can make people squirm :)

Odds and Ends

A few random thoughts re: new goals:

If you’ve been creating lots of profiles for goals you may want to consider consolidating all goals to a single profile. The benefit is you can have all your conversions in one interface. No more messing with multiple browser tabs and adjusting the date range.

If you need to control the access to certain goals, you may need to create a profile for certain goals and then give only the people who need access to those goals access to the profile.

A visitor can only convert at each goal once per visit. This is the way it’s always been.

And finally, creating new goals will not modify your historical data, only future data. So all those new goals you’re going to create this week will only track from the day your create them onward.

New Google Analytics Goals is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Time-On-Page Goals in Google Analytics & Website Optimizer
2. All About Google Analytics Goals
3. Getting More out of Google Analytics Goals