A version of this post originally appeared on Google Analytics Certified Partner InfoTrust's site.

by Nate Denlinger, Web Developer at GACP InfoTrust, LLC

One of our specialities here at InfoTrust is helping ecommerce businesses leverage their web analytics to make better data-driven marketing decisions. This typically starts with installing Google’s Universal Analytics web analytics software and utilizing all of the functionality that is offered with Enhanced Ecommerce tracking capabilities.

Enhanced Ecommerce provides you with a complete picture of what customers on your site are seeing, interacting with and purchasing.

One of the ways you track what your customers are seeing is with product impressions (whenever a user sees an image or description of your products on your website).

Normally, you track what products users see or impressions by simply adding an array of product objects to the DataLayer. These represent the products seen on the page, meaning when any page loads with product images/descriptions, data is sent to Google Analytics that a user saw those specific products. This works well.

However, there is a major issue with this method.  Sometimes you are sending impressions for products that the user never actually sees. This can happen when your page scrolls vertically and some products are off the page or “below the fold”.

For example, lets take a look at a page on Etsy.com:

Sample page on Etsy.com (click for full size)

Here are the results for the search term “Linens”. Currently, you can see sixteen products listed in the search results.  However, in the normal method of sending product impressions, a product impression would be sent for every product on the page.

So, in reality this is what we are telling Google Analytics that the user is seeing (every single product on the page):

Sample page of Etsy.com (click for full-size)

Obviously, no one's screen looks like this, but by sending all products as an impression, we are effectively saying that our customer saw all 63 products. What happens if the user never scrolls past the 16 products shown in the first screenshot?

We are greatly skewing the impressions for the products on the bottom of the page, because often times, users are not scrolling the entire length of the page (and therefore not seeing the additional products).

This could cause you to make incorrect assumptions about how well a product is selling based off of position.

The solution: Scroll-based impression tracking!

Here is how it works at a high level:

1. Instead of automatically adding all product impressions to the DataLayer, we add it to another variable just for temporary storage. Meaning, we do not send all the products loaded on a page directly to Google Analytics, but rather just identify the products that loaded on the page.
2. When the page loads, we actually see what products are visible on the page (ones “above the fold” or where the user can actually see them) and add only those products to the DataLayer for product impressions. Now we don’t send any other product impressions unless they are actually visible to the user.
3. Once the user starts to scroll, we start capturing all the products that haven’t been seen before. We continue to capture these products until the user stops scrolling for a certain amount of time.
4. We then batch all of those products together and send them to the DataLayer as product impressions. 
5. If the user starts to scroll again, we start checking again. However, we never send the same product twice on the same page. If they scroll to the bottom then back up, we don’t send the first products twice.

Using our example on the “Linen” search results, right away we would send product impressions for the first 16 products. Then, let’s say the user scrolled halfway down the page and stopped. We would then send product impressions for products 18 through 40. The user then scrolls to the bottom of the page so we would send product impressions for 41 through 63. Finally the user scrolls back to the top of the page before clicking on the first product. No more impressions would be sent as impressions for all products have already been sent.

The result: Product impressions are only sent as users actually navigate through the pages and can see the products. This is a much more accurate form of product impression tracking since it reflects actual user navigation. 

Next steps: for the technical how-to guide + code samples, please see this post on the InfoTrust site.

Last year we introduced “The Customer Journey to Online Purchase” -- a tool that helped marketers visualize the roles played by marketing channels like paid search, email and display ads in their customers' journeys.

The goal was to help marketers learn more about the customer journeys for their industries. If social makes your customers aware, and email makes them convert -- or vice versa -- you can make sure you're in both places with the right kind of message.

Today we're happy to introduce a new improved version of the Customer Journey to Online Purchase, with a few key enhancements.  We’ve refreshed the data based on millions of consumer interactions, updated the industry classifications, and we’ve split out paid search so you can see the influence of brand and generic search terms on the purchase decision.

In each industry you can now see journeys for small, medium and large companies, which can often be quite different.

Click to enlarge image

For instance, the above image shows the journey for customers of small businesses in the shopping industry. Note that organic search is very often an "assist" interaction for these customers.

Click to enlarge image

Now here's the same journey for large shopping businesses. Note that display clicks and social are strongly assisting interactions -- while display didn’t even appear for the small businesses above. For both small and large businesses, a direct website visit is most likely to be the last interaction. Across industries, the differences from small to large businesses illustrate how different marketing strategies and customer profiles may lead to different buying behavior.

And there's more! Now you can drill down into each marketing channel for a closer look at the role it plays based on its position in the purchase path. Channels that occur more frequently in the beginning of the path are more likely to help generate awareness for your product, while the end of the path is closer to the customer’s purchase decision.

Click to enlarge image

In these charts, for example, we see the different roles that different channels play in the Shopping industry. One interesting insight is that all channels -- even those traditionally thought of as “upper funnel” or “lower funnel” -- occur throughout the purchase path, but a given channel may be more common at particular stages depending on its role (and depending on the industry).

Each marketing campaign and channel may have a different impact on customers depending on when they interact with it. Using what you learn from this tool, you can help adapt your marketing messaging to be more relevant and useful for your customers.

Try the Customer Journey to Online Purchase today. And for more helpful marketing insights, check out Measure What Matters Most: our new guide chock-full of suggestions on how to measure the impact of your marketing -- across channels -- to complement what you learn from the Customer Journey tool and take action to improve your marketing.

Happy analyzing!

The Customer Journey to Online Purchase »

Posted by Sara Jablon Moked, Product Marketing Manager, Google Analytics

Earlier this week, we announced the beta launch of Enhanced Ecommerce for Google Analytics. It's a complete revamp of our ecommerce analytics, designed to provide richer insights into pre-purchase shopping behavior and into product performance.

“With Enhanced Ecommerce our clients can immediately gain clear insight into the most important metrics about shopper behavior and conversion: what products are viewed, where they are viewed, when they are added to carts, how the checkout process works and where customers get lost, and even details like payment methods.”

- Caleb Whitmore, CEO of Analytics Pros

Enhanced Ecommerce is designed to keep pace with the remarkable rise of online retail, which grew another 30% year over year in 2013. Digital data has played an essential role in that growth, offering deep insights into shopper behavior and letting retailers make smarter decisions. But needs are rapidly increasing and retailers are requiring more sophisticated and comprehensive analysis tools to understand shoppers and product-level performance. With the launch of Enhanced Ecommerce, we’re providing these tools.

“Enhanced Ecommerce will help us to overcome many challenges. As an example, I'm looking at a report that indicates a 74.4% checkout abandonment rate.  That insight is shockingly simple: over 7 out of 10 people that add something to the cart and start to checkout don't complete it! This is the kind of data that can drive change more readily than, say, simple conversion rates for e-commerce orders.”

 - Caleb Whitmore, CEO of Analytics Pros

Enhanced Ecommerce is built on top of the powerful Universal Analytics foundation. It includes tracking code updates (including full support for Google Tag Manager), data model changes, and new end-user reports that address ecommerce-specific use cases. Together they help online retailers see farther and understand customers better than ever before. 

Get deeper insights

• Analyze how far shoppers get in the shopping funnel and where they drop off. 
• Understand which products are viewed most, which are frequently abandoned in cart and which ones convert well. 
• Upload rich product metadata to slice and dice your data.
• Create rich user segments to delve deeper into your users’ shopping behavior and the products they interact with.

Optimize your site 

• Create product lists for onsite merchandising rules and product landing pages to see which lists and products are best at driving customer engagement.
• Analyze how internal promotions impact sales, and act immediately on the results.
• With retailers reporting average on-site conversion rates of around 2.7%, even small improvements can have a big impact.

Close the loop

• With refund support, Google Analytics now covers the entire shopping lifecycle.
• Import user segments, based on ecommerce activity, for targeting in your remarketing campaigns.

In the chart below, see an example of how the new reports can benefit your business. You can create segments directly from the funnel reports to analyze abandoned cart sessions. See which products were abandoned and which devices to target to recapture those users. This data allows you to take immediate action. 

Shopping behavior funnel report. Use the table to analyze by any session level dimension

Enhanced Ecommerce is all about the bottom line. We've designed it to help you improve your total experience and turn more shoppers into buyers.

Learn more

Sign up today for the new Analytics Academy course on Enhanced Ecommerce! Or come learn more at Internet Retailer Conference Exhibition on June 12; Google’s Jesse Nichols will present Enhanced Ecommerce live. 

You can find more information on getting started with Enhanced Ecommerce in our Help Center and Developer site.  

Happy Analyzing!

Post by: Marcia Jung, Product Manager, Google Analytics

Savvy marketers understand that you don’t always seal the deal with a single message, image, or advertisement. A user may see a display ad, click on a link from a friend, or do a search before buying something from your website — and all of these interactions can play a role in the final sale. It’s important to understand the entire customer journey so you can measure all of the elements that contribute to your campaigns, attribute the right value to them, and adjust your marketing budgets where appropriate.

That’s the philosophy behind Google Analytics tools like Multi-Channel Funnels and Attribution Modeling. Tens of thousands of our largest advertisers are gaining valuable insights from Multi-Channel Funnels every month, and we’ve collected these insights using aggregate statistics to develop a benchmarking tool — The Customer Journey to Online Purchase. This interactive tool lets you explore typical online buying behavior and see how different marketing interactions affect business success.


The tool draws on Ecommerce and Multi-Channel Funnels data from over 36,000 Google Analytics clients that authorized sharing, including millions of purchases across 11 industries in 7 countries. Purchase paths in this tool are each based on interactions with a single ecommerce advertiser.

You’ll find benchmark data for:

• how different marketing channels (such as display, search, email, and your own website) help move users towards purchases. For example, some marketing channels play an “assist” role during the earlier stages of the marketing funnel, whereas some play a “last interaction” role just before a sale.
• how long it takes for customers to make a purchase online (from the first time they interact with your marketing to the moment they actually buy something), and how the length of this journey affects average order values.

Channel Roles in the Customer Journey
The data shows that every industry is different — the path to purchase for hotel rooms in Japan is not necessarily the same as the path as for an online supermarket in Canada.

A few findings stand out, in particular:

• As you might expect, customers typically click on display ads early in their purchase journeys, but in some industries, such as US travel and auto, display clicks tend to occur closer to the purchase decision.
• Across industries and countries, paid search has a fairly even assist-to-last interaction ratio, implying that this channel can act both in the earlier and later stages of the customer journey.

Advanced tip:

• Once you’ve explored the benchmarks, look deeper into your own marketing data with the Multi-Channel Funnel reports, and consider defining your channels and campaigns to separate out categories that are specific to your business needs.

Purchase values and the length of the journey
We also see interesting patterns emerge when examining the length of the customer journey. While the majority of purchases take place within a single day or a single step (i.e., a single interaction with one marketing channel), longer paths tend to correlate with higher average order values. 

For example,

• in US Tech, online purchases that take more than 28 days are worth about 3.5 times more than purchases that occur immediately. And while 61% of tech purchases take place on that first day, only 53% of revenue comes from single-day purchases.
• in Consumer Packaged Goods (CPG), on the other hand, most purchases (82%) are quick, likely because these are smaller and simpler purchases that don’t require much research.
• in Edu / Gov, 41% of revenue comes from multi-day purchases, but 60% of revenue comes from multi-step purchases — suggesting that even when customers make decisions in a relatively short time period, they often have multiple marketing interactions before purchasing.

Advanced tip:

• In Multi-Channel Funnels or the Attribution Modeling Tool, you can adjust the lookback window to reflect the typical length of the purchase path in your industry. For example, if your business tends to have shorter paths, you can zoom in on paths that take 5 days or less:

Putting the benchmarks to work
For marketers, it’s always a crucial challenge to design campaigns that deliver the right message at the right moment in a customer’s journey to purchase. We hope these benchmarks will provide useful insights about the journey and help you put your business into context. In particular, take a look at the final infographic, the “Benchmarks Dashboard,” to get a quick overview of your industry. Then, when you view your own data in the Multi-Channel Funnels reports in Google Analytics, you’ll gain a better understanding of where different channels impact your conversions and what your typical path looks like, so you can adjust your budgeting and marketing programs accordingly.

Try The Customer Journey to Online Purchase today on Google’s new Think Insights website.

Happy analyzing!

Posted by Paul Muret, Director of Engineering, Google Analytics

We’ve listened to your feedback and have heard the requests loud and clear: E-Commerce should support multiple currencies. We’re pleased to announce the launch of this feature which will be rolling out to all users over the next few weeks. 

Multi-Currency support for eCommerce provides Google Analytics users with the ability to track transaction metrics (total revenue, tax, and shipping & handling) in multiple local currencies within a single web property. And Google Analytics will convert them into the one currency based on your profile setting. This provides key benefits for e-commerce brands looking to conduct analysis across an international customer base and helps make some previously complex reporting easier.

New metrics supported in multi-currency

Multi-Currency tracking code implementation:

Multi-currency is supported by web tracking and Android SDK (iOS SDK support is coming soon).

The ‘currency code’ is a global setting that can be set via tracker ‘_set()’. It only need to be set once, unless the page is sending multiple transactions in separate currencies.

Here are a few other things we think you’ll want to know:

How the conversion rate is decided?
The conversion rate is pulled from currency server which is serving Google Billing. The value is the daily exchange rate of the day before hit date. See a technical overview for additional information.

Which currency does GA support?

We support currencies which are available in GA profile currency dropdown menu. Right now, 31 currencies altogether are supported.

Currency dropdown menu

Which currency code shall I use?

A full version of currency codes shared across Google products is available on the Google Developers site.

Can I retro-process my history transaction data?

Only from the day you started using multi-currency support, you can get both local and global value. 

Several companies have already started using Multi-Currency in Google Analytics and are seeing great results. One of our Certified Partners, Blast Analytics & Marketing, helped their client AllPosters.com implement this feature. David Tjen, Director of Analytics at AllPosters.com reports:

"Google Analytics' new multi-currency feature increases sales metric accuracy for AllPosters.com. As an international brand, the AllPosters family of sites supports 20 currencies across 25 countries. Previously, manual adjustments were required before we could read sales metrics in Google Analytics when we had transactions with large currency conversion ratios to the US dollar, such as the Mexican Peso and Japanese Yen. The simple code update solves the issue by automatically converting all transactions to the primary currency on each site, providing sales metrics that allow us to make faster decisions with our web analytics data.”

To get started today, view our help center page with detailed instructions on how to begin.

Posted by Wayne Xu, Google Analytics team

At last Thursday’s webinar on Goals, we we explored one of the most fundamental analytics topics: how to translate your business objectives into measurable actions on your website. You sent in your questions, and we heard from many users that you want more guidance on turning all that data into insights.

Please read on for answers to your top questions, and watch the recording of the webinar here:

How do I do data analysis?

Performing data analysis requires understanding what your company defines as success before you can even start to figure out which reports and metrics to use. The best place to begin is to think about why you have a website, what you’re trying to achieve (lead generation, site engagement, sales, et cetera), and how those objectives map to specific metrics in Google Analytics. For example, if you  have an ecommerce website, you might want to track which types of users purchased and which types of users didn’t purchase. If you have a site with lots of content, you might want to understand where users came from before watching a video (e.g., were they referred by a blog post, or did they click on a paid search ad?), or you might be interested in how users moved through your site before getting to a certain page.

Once you’ve figured out your business objectives and defined your questions it’s all about finding those metrics in the reports. We have a lot of great 60-second YouTube videos that walk through different reporting and analysis techniques.

Why should I use Goals if I don’t have a product to sell?
You created your website with the hope that users would come and visit. Even if you aren’t selling anything, you can use Goals to help you dive deeper into your site performance and learn where your users might be having trouble. For example, you might want to ensure that visitors to your site are able to find directions to your physical location, or you might want to be sure that they view a particular piece of content on your site. You could set up a Goal for that page, and then use Goal Flow in the Flow Visualization tool to see how users get there. You might then determine that it's too hard for users to find the information that they need. The specific metrics that you should use will depend on the purpose and goals for your site.

Which types of Goals should I use?
There are four different Goal types to choose from in Google Analytics: URL destination, Time on Site, Pages per Visit, and Event. URL destination goals are best for goals based on a visit to a key page of your site, such as a “thank you” page after a purchase. Time-on-Site or Pages-per-Visit goals are best if you’re more interested in determining site engagement. Event goals should be used if you want to track specific actions such as watching a video, listening to an audio clip, or downloading a PDF. Note that the first three types of goals can be set up with no changes to your tracking code, but if you want to use Event goals, you’ll need to set up Event tracking. And don’t forget that if you’re an online retailer, or if your conversion process pulls in dynamic monetary values, Ecommerce in Google Analytics allows you to track transactions and the order value of every purchase made on your site.

What are good trends to measure for websites without a shopping cart?
A "conversion" isn't just a sale -- it's about all of the reasons why your site exists; it’s any action you want your visitors to take based on your business objectives. Analytics users often want to compare themselves to industry trends or best practices -- but the truth is that in many cases the best benchmark is your own website performance. You should define your own business goals, then develop some key performance indicators, or KPIs, and track them from month to month or quarter to quarter. It may also be helpful to set up simple surveys that ask your visitors if they’ve succeeded in finding the information that they were looking for on your site.

How do I set up Google Analytics for my site?
For some websites, all you need to do is copy and paste the standard JavaScript code to every page of your site -- Google Analytics will automatically generate this standard code for you, so it’s very easy to implement. Read more about this in our Help Center. Other sites, such as those that span multiple domains or subdomains, require additional lines of code. If you have this type of site, you should check out our documentation on all the different implementation scenarios. Use these guidelines with your webmaster to get the code implemented properly. If you need additional help, you should consider contacting one of our certified partners for advice and assistance with all aspects of Google Analytics.

What are Goal match types/settings?
There are three match types for URL destination goals: head match, exact match, and regular expression match. Exact match is used when you have a static URL (a page that does not change based on user actions) -- you can just enter the URL as it appears on your site and Google Analytics will track the goal. Head match is used if you have a URL that has dynamic values at the end, such as session IDs. Head match will record goals for whatever URL you enter into the interface -- plus anything that comes after that. Finally, regular expression match is used for completely dynamic URLs or to capture multiple URLs in one goal. Check out our Help Center article on setting up Goals to get more information about which match type is right for you.

How do we determine what goal value to set?
Goal value is what each action is worth to you. Ask yourself how much it’s worth to have someone sign up for your email newsletters, knowing they'll now get consistent messaging from your business. You may want to start with a larger objective that has a monetary value, like landing a big client, then map out the smaller steps leading up to that sale. For example, it may take an average of 25 lead forms filled out on your site to drive one sale. The value of a filled-out lead form would then be equal to an average sale divided by 25.  It may take some time to determine these attribution amounts, and you shouldn’t be afraid to adjust your Goals and Goal values periodically!

How do we test alternate landing pages?
Once you’ve set up Goals, you may discover that certain pieces of your funnel are losing lots of visitors. Small improvements to those pages could have a dramatic impact on your conversion rates. Fortunately, we have a great tool called Google Website Optimizer that allows you to test different variations of the same page so you can improve the effectiveness of your website and your return on investment.

What are the top 5 metrics to share with the CEO?
There aren’t really 5 golden metrics that will work for every single company and every single CEO. You’ll need to do some brainstorming and discovery to understand which metrics in Google Analytics map to your business objectives. Think about your business strategy -- for example, are you looking to reach customers who are on-the-go? Then it’s probably helpful to track the percentage of visits and conversions coming from mobile, so you can tell the CEO about the success of your mobile strategy. Do you want to make sure that you’re getting a good return on your marketing investments? Then you should consider tracking the percentage of conversions coming from advertising vs. other sources (this is a good place to use Multi-Channel Funnels!).

Although it may take some work to determine the relevant metrics, it’s worth the effort to ensure that you are presenting information that tells the right story about your business. Once you’ve defined your metrics, you can use Google Analytics dashboards to pull everything together in an easy-to-read format. So dive into the Google Analytics reports and find your story!

Please also check our help center for further details on all of your questions.


Posted by Sara Jablon Moked, Google Analytics team

Increasingly, mobile applications allow you to purchase products and virtual goods. For that reason, it’s important to track these mobile transactions in order to understand which products perform well.

So today we’ve added Ecommerce tracking functionality to the Google Analytics SDK for Android.

Ecommerce Tracking
With Ecommerce mobile tracking, you can capture transaction and product information, send the data to Google Analytics, and then analyze which products performed best. Of course, because this is all within Google Analytics, you can also tie transaction data back to app usage behavior. For example, you can now compare the referral that generated an app download by the revenue it generated. See the Google Analytics SDK for Android developer docs to learn how to implement this feature.

Debug and Validation
In addition to Ecommerce, we’ve added new debug and dry run modes to make it easier to validate your Google Analytics implementation.

Debug Mode:

tracker.setDebug(true);

With debug mode, all data requests to Google Analytics are sent to the Android log, allowing you to validate that your app is sending data properly. You can view the Android log using the adb logcat command.

Dry Run:

tracker.setDryRun(true);

The dry run mode sends all tracking data locally so that you don’t corrupt your production data.

See Us At Google IO
We’ll be demoing all this new functionality this year Google IO, so stop by the Optimizing Android Apps With Google Analytics session on May 11, 12:30PM – 01:30PM / Room 9.

Posted by Jim Cotugno, Google Analytics Tracking Team

This is a guest post from Tom Critchlow who is an excel ninja, data geek, analytics nerd and head of search for Distilled, a London & Seattle based search agency. Tom provides a cautionary tale on the importance of keeping your site up to date.

This blog post title may appear sensational but I assure you that it's not (much...). I recently spotted an issue with a client's e-commerce website which was costing them £100,000 / month in revenue (~$150,000). The fix took 5 minutes. Even more surprisingly, since I've been on the lookout for this issue I've spotted it on quite a significant number of websites. Hence why I got in touch with the Google guys and asked if I could talk about this in front of as many people as possible to try and spread awareness!

1) Graph of Win

Firstly, let's take a quick look at a pretty graph. This is comparing revenue month on month before and after the fix was made:

Note the increased revenue! :-) Everyone loves increased revenue. For those with beady eyes you will have spotted that this isn't total revenue on the site but it's just IE8 users. What's going on here?

2) The Issue

Before I delve into the issue, let me first give you a little background. When you enter private information online, such as your credit card details, you want to be sure that you're transmitting the information over a secure connection. You can usually tell you're on a secure connection to a website if the page URL begins with https:// instead of http://

Making webpages secure, however, is more resource intensive and so most websites only make their most important pages secure (though Gmail now always uses https:// by default). This means that when you browse a website, for example http://www.amazon.com you will browse around product pages which are all located on http:// URLs. When you want to actually purchase something from the site however you transition over to secure URLs such as https://www.amazon.co.uk/gp/cart/view.html

This is standard practice for e-commerce websites and when you move through the buying funnel you should inevitably transition at some point from a non-secure page (http://) to a secure page (https://).

Now, the issue I'm talking about in this post is with the client's site. The site uses Google Analytics however unfortunately they were using the old version of the code and were using the same piece of code across all pages of their site. The code they were using looked a little like this:

Unfortunately, this means that their secure checkout pages such as https://www.example.com/checkout/payment contained non-secure elements - namely the URL call to "http://www.google-analytics.com/urchin.js". Browsers like Chrome and Firefox don't display a warning but Internet Explorer 8 produced the following security warning when users transitioned from the non-secure (http://) pages to the secure (https://) pages. This error looks like this:

Pretty scary huh! Unsurprisingly this was causing almost all users browsing in Internet Explorer 8 to abandon the shopping process. Since Internet Explorer 8 is one of the most popular browsers on the web this was a huge amount of revenue they were missing out on!

3) How To Fix It

This issue arose because of a non-secure HTTP call within a very old version of the Google Analytics tracking code. The fix for this is very simple - just install the new code! The new code is more versatile than the old code and works both on http:// pages and https:// pages so you don't need to worry about using a different code on secure and non-secure pages. The new code looks a little like this:

There's a complete run-through here on using this new code here and specific migration advice.

And that's it! It's a simple fix but one that can have significant impact on your bottom line. I repeat what I said at the top of the post - I've seen plenty of sites that suffer from this issue so it's really not as rare as you might think!

I should point out here that the Google Analytics code has been able to handle HTTPS and HTTP pages properly since well before the asynchronous code was released, but plenty of sites are still using very old legacy code, which is why this is still an issue for some sites. Also, it's not just the Google Analytics code which can cause problems! Any non-secure elements on a page can cause a security warning so double check your code carefully.

4) How to Diagnose This Issue (simple)

If you're wondering if your site suffers from this problem there's a quite easy way of checking by looking at your conversion rate segmented by browser:

Setting up these custom segments is really easy, but to make it even easier I've set them up for you and all you need to do is click these links to add both these segments directly into your Google Analytics account:

Internet Explorer 8 Users

Non-Internet Explorer 8 Users

Then browse to your conversion rate report and select the segments from your custom segments:

5) How to Diagnose This Issue (advanced)

Of course, the issue I'm talking about in this post is only a specific issue and plenty of other issues may well exist like it. The underlying principle is that segmenting your funnel is a useful thing to do so that you can see if a specific visitor type are not converting or there is a specific drop-off point for them. Unfortunately there isn't a way of segmenting your funnel within Google Analytics at the moment but there are a few advanced ways of getting around this. For example:

• ROI Revolution have a method for segmenting on the fly. Unfortunately this method doesn't let you check custom date ranges.
• LunaMetrics have a way of segmenting the funnel using goals. Unfortunately this method won't let you capture historical data.
• Analytics Ninja has a way of segmenting using advanced segments. Unfortunately this method only let's you track up to a maximum of 3 funnel steps at a time.

None of these methods quite does what I want it to so I'm presenting a 4th option here:

Step 1 - Identify your funnel steps

This is fairly straightforward, all you need to do is understand what the URLs look like for your funnel. For example, let's say our funnel looks like this:

1. http://www.example.com/cart/availability
2. http://www.example.com/cart/details
3. http://www.example.com/cart/extras/
4. http://www.example.com/book/check/
5. https://www.example.com/book/payment/
6. https://www.example.com/book/confirm/

Step 2 - Create some regex

This is getting slightly more complex, however, assuming that all your URLs are exact match (rather than head match or something more complicated) the regex to create is this:

^/cart/availability$|^/cart/details$|^/cart/extras/$|^/book/check/$|^/book/payment/$|^/book/confirm/$

Where we generate this string as follows:

• ^/url1/$ - this matches the exact URL contained between ^ and $
• | - separate each URL with a pipe, this OR matches any of the statements in the string

For a more complete (and very pretty) guide to using regex in Google Analytics download this PDF.

Step 3 - Enter this regex in the top content report

In the top content report copy and paste this regex into the filter box:

This will then filter the top content report to only show you visits to one of the above pages in your funnel. Now we can see the drop off between steps like we can in the regular funnel.

Step 4 - Add custom segments & export to Excel

Now, we add whichever custom segments we want (for example IE8 users like above). This gives us each step of the funnel and the visits to each step broken down by segments:

Unfortunately this data is a little bit difficult to analyse as it doesn't give us the drop off percentage. So, to make this data easier to process and analyse export it to Excel. This will allow us to create a nice little table like this (very minimal excel magic required!):

This is an improvement over the simple diagnosis above because it not only shows us that IE8 users are not converting as well as users from other browsers, but it even tells us the exact step where it's a problem (the cell highlighted in red in the image). Looking back at the URLs we've identified we see that this drop off percentage is the same step where a user transitions from HTTP to HTTPS.

Note: The super-observant among you may have noticed that there is a potential discrepancy here. The warning message that IE8 throws up allows the user to select the option to only view secure elements on the HTTPS page. If the user selects this option then theoretically the user could still carry on through the site and complete the purchase. This visit and the revenue from this purchase wouldn't be tracked in Google Analytics since the HTTP Google Analytics call is blocked by the browser. So the extra £100,000 / month could in theory only be a reported increase in revenue. In reality however we found that the true bottom line still increased by over £30,000 per month as a result of this change. This implies that displaying the pop-up still has a drastic effect on conversion rates.

6) Conclusion

So what have we learned? The key lessons here are as follows:

• Keep your GA code up to date
• Use advanced segments to monitor conversion rate between browsers
• Always perform browser testing to ensure your website functions for all browsers

Remember, the HTTP/HTTPS issue applies equally to all URL calls so even if you use the up-to-date Google Analytics tracking code some other non-secure element on the page might be costing you revenue so always make sure that your website is functioning perfectly across all browsers. If you don't, you might end up losing £360,000 ($500,000) a year or more!

Thanks Tom for a thorough look at how to avoid this problem. And to echo Tom's advice, we encourage everyone to move to the newest version of the GA tracking code. You can follow more analytics insights and online marketing tips at the Distilled Blog or follow Tom on Twitter.

Posted by Trevor Claiborne, Google Analytics Team

If you're a business owner of any size, you've at some point considered expanding. And as the web makes the world smaller, one way to expand is to offer your website in different languages and take your business across borders or to different segments. By entering other markets with your website, you can gauge new markets and find ways to grow and generate revenue.

Getting set up to offer your products and services in a different country can have a number of steps including localization and legal processes. Another thing to keep in mind is how you will set up your web analytics for the different languages and countries your site now serves.

We're highlighting a series of posts on the topic, called "Google Analytics reporting for multilingual e-commerce stores" by Gavin Doolan, a Googler based in Dublin specializing on Google Analytics for Europe. The posts are all from our Analytics blog in Europe, the Conversion Room. This is obviously a topic very close to the European businessperson's heart.

The great thing about the posts is that Gavin presents solutions for different structures of sites, since not everyone is doing the same thing when they sell products internationally or in different languages.

Part #1: Multiple languages on a single domain

Part #2: Multiple profiles, multiple domains and a single payment gateway

Part #3: Roll up reporting, multiple domains and a single payment gateway

We hope you'll find this information helpful as you think about expanding your business and your website.

Posted by Trevor Claiborne, Google Analytics Team

Last year, Justin Cutroni of EpikOne published a four-part tutorial on how to use Ecommerce Tracking in Google Analytics. We've seen a lot of interest in this topic, so we thought we'd republish the first part of the series here on the Analytics blog.

Ecommerce Tracking Part 1: How it Works

This post is the first in a series of e-commerce transaction tracking with Google Analytics. Why is e-commerce tracking important? Well, transaction data is a vital piece of information when analyzing online business performance.

Sure, it’s great to measure things like conversion rate, but revenue is much more tangible to many business owners. Having the e-commerce data in your web analytics application makes it easier to perform analysis. Do you need to set up e-commerce tracking? No, but it sure helps. :)

The Big Pictures

E-commerce tracking is based on the same principal as standard pageview tracking. JavaScript code sends the data to a Google Analytic servers by requesting an invisible gif file. The big difference is that e-commerce data is sent rather than pageview data.

But how does Google Analytics get the e-commerce data? That’s the tricky part. You, the site owner, must create some type of code that inserts the transaction data into the GA JavaScript. Sounds tricky, huh? Well, its not that bad.

Step by Step: How it Works

Let’s break it down and walk through what actually happens.

1. The visitor submits their transaction to your server.
2. Your server receives the transaction data and processes the transaction. This may include a number of steps at the server level, such as sending a confirmation email, checking a credit card number, etc.
3. After processing the transaction the server prepares to send the receipt page back to the visitor. While preparing the receipt page your server must extract some the transaction data and insert it into the Google Analytics JavaScript. This is the code that you must create.
4. The receipt page is sent to the visitor’s browser.
5. While the receipt page renders in the visitor’s browser the e-commerce data is sent to Google Analytics via special GA JavaScript.
6. Here’s a basic diagram of the process. Again, the biggest challenge during implementation is adding code to your web server that inserts the transaction data, in the appropriate format, into the receipt page. I’ll cover the setup in part 2 of this series.

What Data can be Tracked?

Google Analytics collect two types of e-commerce data: transaction data and item data. Transaction data describes the overall transaction (transaction ID, total sale, tax, shipping, etc.) while item data describes the items purchased in the transaction (sku, description, category, etc.). All of this data eventually ends up in GA reports. Here’s a complete list of the data:

Transaction Data

• Transaction ID: your internal transaction ID [required]
• Affiliate or store name
• Total
• Tax
• Shipping
• City
• State or region
• Country

Item Data

• Transaction ID: same as in transaction data [required]
• SKU
• Product name
• Product category or product variation
• Unit price [required]
• Quantity [required]

A few notes about the data. First, the geo-location data is no longer used by Google Analytics. The new version of GA tries to identify where the buyer is located using an IP address lookup.

Also, you should avoid using any non-alpha numeric characters in the data. Especially in the numeric fields. Do not add a currency identifier (i.e. dollar sign) in the total, tax or shipping fields. this can cause problems with the data.

Continue reading parts 2-4 of this series on EpikOne's Blog, Analytics Talk

Posted by Sebastian Tonkin, Google Analytics

In the spirit of the holidays, we would like to offer tips on how to increase visibility into your e-commerce performance and your advertising spend using Google Analytics. For many, seasonality influences purchasing decisions and affects business revenues. Analytics can help keep a close eye on your advertising spend and e-commerce trends to run a cost conscious business.

We recommend 3 simple methods captured in the videos below. You can find these videos and more on the new Google Analytics Youtube Channel.

1. Use Google Analytics to track your e-commerce activity. As an e-commerce site, you likely want to know who is visiting your site and the goods they are purchasing. By enabling E-commerce tracking on your site, Google Analytics will provide vital metrics including overall revenue, revenue per product, average transaction amount, and more.

Coupled with our Motion Charts feature, you can easily see how the the products trend over time by various dimensions including: revenue, quantity, and average price.

2. Identify your high spenders to better target your website promotions and ad spend. With additional information on ROI for keywords and spending trends, you can focus your efforts on the traffic you care about the most.

3. Link your AdWords and Analytics accounts to track ROI, Revenue per Click, campaign and keywords performance. Added benefits include drilling down to the ad campaign, ad group, and keyword levels for goals conversions and e-commerce transactions.

And don't forget, even a few minutes a day with Google Analytics can help your website.

Posted by Melissa Hsieh, Google Analytics Team

For many of you the fourth quarter is the busiest and biggest season, and in this economy analytics are more important than ever. With holiday traffic starting in November and peaking in early-December, now is the time to make sure your site is in the best shape to maximize holiday traffic and revenue.

To help you better analyze your campaign performance, optimize your web pages, and drive even more traffic to your e-commerce site during this crucial time, we'd like to share some tip and tools you can use in Analytics and other Google products.

Use the Analytics Funnel Visualization report to improve conversions

• Learn how many shoppers drop out during each step of your shopping cart conversion process.
• Then, work on the steps that lose the most customers.
• Website Optimizer, our free testing tool, is a great way to improve those key pages.

Geo-target your AdWords campaigns through Analytics

• Find out where your most profitable customers are coming from, and direct your advertising dollars to target customers in those areas.
  
• Get data for region-specific keyword performance in your Analytics account.
  
• Create more targeted AdWords campaigns by region. Watch this video for a step-by-step demo.

Submit your products to Google Product Search

• Google Product Search enables shoppers to search for and find products to buy online, and enables you to submit your products for free and target users shopping on Google. Google Product Search is currently available to merchants in the U.S., U.K., and Germany.
• If you've never used Google Product Search, you can start submitting your products using feeds you've already prepared for other shopping engines.

Visit our Google page on holiday success to see a full list of tips. We hope these tips and tools help you make the most of your holiday season!

- Dai Pham, Google Analytics Team