This post originally appeared on the Google Analytics Japan blog. - Ed.

Google Analytics’ e-commerce tracking allows online merchants to measure items sold and tie those results back to their digital marketing activities. But did you know that it can also be used to track non e-commerce activity?

Nissan Motor Company does just this. Nissan operates in the automobile industry, and owns a network of websites designed to help consumers around the world decide which Nissan vehicle they would like to purchase.



Nissan uses e-commerce tracking whenever a visitor submits a request for a test drive or a brochure. They treat each request as if a car were sold, and record details such as the model, colour, transmission type, and location of the vehicles people inquire after. A traditional Google Analytics implementation for a non e-commerce site would simply use goals to measure conversions. So why did Nissan opt to use e-commerce tracking instead?

They wanted to be able to measure more information about each inquiry within their Google Analytics reports. By implementing e-commerce tracking they are now able to pass additional information to their Google Analytics account, such as the category, colour, and model of car the visitor was interested in. Nissan's Global Marketing Strategy Division then analyses this information to understand which vehicles are in hot demand in each market; it then feeds those insights to their manufacturing plants across the globe to ensure that there is enough supply to satisfy demand.

One of the benefits of Google Analytics is that you can decide who should have access to your suite of reports. Nissan’s Global Division uses this feature to decentralise access to their different market operations, allowing each country manager to log into Google Analytics and quickly assess the popularity of different models for their market. Nissan employed a Google Analytics Certified Partner in Japan, Ayudante, to help set up their account profiles and custom reports that could then be accessed by each of the country managers.

Nissan’s Global Marketing Strategy division says there are 3 key benefits they gain from Google Analytics as a whole:

1. It is easy to assess product popularity globally and by market. The user experience is seamless and there was no complex setup necessary.
2. Custom reports allow you to easily view complex information in one view. It dramatically reduces the time to summarize multiple reports, document it, and share it within the organisation.
3. Google Analytics gives them access to timely information, which allows for better decision making.

Even if you are a non e-commerce site, you should explore e-commerce tracking as a means of measuring more information about the products or services your visitors are inquiring about. Then share that information with your wider marketing and product teams so that they can make effective decisions to maximise sales.

Posted by Noriyuki Ouchi, Google Analytics Solutions Consultant, Google Japan and Vinoaj Vijeyakumaar, Senior Conversion Specialist, Google Southeast Asia

Multi-Channel Funnels are a new set of reports that show which channels your customers interacted with during the 30 days prior to a conversion or purchase. In this series of three posts, Michael Fox, co-Founder and Director of Operations of Shoes of Prey, shares how he uses these new reports to improve sales for the business. You can read Part 1 and Part 2 to catch up on the series. - Ed.

In our first post, I discussed why we like Google Analytics’ new Multi-Channel Funnels reports and how we improved our site experience based on insights gained from the Top Conversion Paths report. Today I want to focus on another report: the Assisted Conversions report.

Assisted Conversions report
The Assisted Conversions report summarises the roles and contributions of channels that brought traffic to our website. Prior to Multi-Channel Funnels we used to attribute sales to the last channel (e.g. organic search, paid display, etc.) that the customer interacted with--in other words, the last channel to send us the customer’s click.

What does this mean? Let’s take, for example, a visitor who first came to our site via a link they saw on Twitter, then a few days later clicked on one of our ads running on the Google Display Network, then came through an organic search result on Yahoo, and finally visited our site by clicking on a text ad on Google Search and made a purchase.

We traditionally attributed the sale to the Google Search text ad as that was the source of the last interaction. It also meant that we completely discounted the contribution made by the preceding channels that brought visitors to our site. This method of attribution just doesn’t reflect reality.

The Assisted Conversions report helped us change our view, because for every channel that brings traffic to our website, the report can now tell us how many:

• Last Interaction Conversions a given channel contributed towards (i.e. that was the last channel used before a purchase was made)
• Assisted Interaction Conversions a given channel contributed towards (i.e. it contributed towards a purchase, but was not the last channel used)

Insights: Social media influences sales down the line
When evaluating the Assisted Conversions report, we tend to focus on the “Assisted / Last Interaction Conversions” metric, which is displayed as a ratio between the number of Assisted and Last Intereaction conversions. This metric is able to tell us which channels are best for direct response (lower ratio) and which channels are best for influencing sales further down the line (higher ratio).



What we were able to see is that social media channels, such as our Shoes of Prey blog, Twitter, and Facebook, have a high combined Assisted / Last Interaction Conversions ratio of 8.67. What this means is that these channels contribute significantly to conversions early in the funnel and this may not have been picked up if performance was measured on last interaction conversions only.

Actions: Re-evaluating how we value our social media efforts
The Assisted Conversions report helps us evaluate our social media channels. In the past we weren’t sure how effective our social media campaigns were towards driving sales. Today it’s clear that they play an influential role in making sales happen further down the line. We’ve now ensured that our marketing budgets are apportioned appropriately based on these insights.

We’ve started taking action on social media sites to help our potential customers purchase their shoes sooner. For example, we’ve updated our social content to ensure it includes educational material on shoe design, and experiment with our calls to action to encourage visitors to design their own shoes.

Because social media plays an important role in driving sales further down the funnel, we are taking steps to acquire a larger social audience. We now run online campaigns to capture more fan page likes, Twitter followers, Google+ followers, and blog subscribers. We also started promoting our social media channels more prominently on our website and newsletters.



I strongly recommend that you take a close look at your Assisted Conversions report if you aren’t doing so already. By comparing assisted conversions against last interaction conversions, we revised our outlook on certain certain channels (e.g. social media) that we assumed weren’t performing well.

Posted by Michael Fox, co-Founder and Director of Operations, Shoes of Prey

Multi-Channel Funnels are a new set of reports that show which marketing channels your customers visited your site from during the 30 days prior to a conversion or purchase. In this series of three posts, Michael Fox, co-Founder and Director of Operations of Shoes of Prey, shares how he uses these new reports to improve sales for the business. You can read Part 1 here. - Ed.

In our first post, I discussed why we like Google Analytics’ new Multi-Channel Funnels reports, and how we improved our website and our customers’ experience based on insights gained from the Top Conversion Paths report. Today I want to focus on another equally insightful report: the Time Lag report.


Time Lag report
The time lag report shows how many days passed between when the visitor first came to our site and when they made a conversion (i.e. in our case, sales). This provided us with useful insights into the length of our online sales cycle.


Insights: Make the design process easier for our customers



When analysing our sales cycles earlier in the year, we noticed that 40% of our conversions (and 37% of our revenue) happen one or more days after the first visit. Furthermore, we could see that 13% of total conversions happen 12 or more days after the first visit. This reinforced our conclusions from the last post that our customers take time to make a decision on which shoe design they would like to purchase. We need to take steps to shorten this for them.

Actions: Email campaigns to help customers make decisions sooner
These insights convinced us to put into action a number of email campaigns to help our potential customers make a decision sooner.

We first developed an email marketing program that keeps in regular touch with our customers over time. We knew from the report that for every day that a customer stays away from the design process, the more likely they will drop off without making a purchase. These emails were designed to remind them about their unfinished designs and also provided design tips.

We also tested another email campaign where we sent customers content related to their unfinished design. We tested offering free shipping or free leather samples of the leathers used in their design. The leather samples offer got a reasonable take up but hasn't shown a big uplift in sales yet. The free shipping offer didn't perform very well though. We hypothesise that our customers care more about the quality of the product over saving a few dollars on shipping. Moving forward, we’ll focus on the quality aspects of our products when doing this kind of outreach.

We also started an email campaign targeting visitors who abandoned their shopping cart. We ask for feedback on why customers abandoned their cart and offer to answer any questions they might have. We’ve received some great feedback, but most importantly, we were able to “re-activate” shoppers who abandoned the purchase process. This campaign has not only lead to a 7% increase in sales, but has also provided valuable learnings on how to fine-tune our purchase process.


Results: Shortening the time-to-purchase
In combination with what we have done here, and with our actions we shared in our first post, we have seen a decrease in the time to purchase. Over the course of 4 months, we’ve seen same-day purchases increase by 20% and 12+ day purchases fall by 8%.




Multi-Channel Funnels helped us understand the time lag between when a visitor first comes to our and when they complete a purchase. These insights helped us formulate a “continuous touch” strategy that has helped us increase sales. I would be interested to hear what your ideas are for reducing the number of days between a first visit and purchase.

Posted by Michael Fox, co-Founder and Director of Operations, Shoes of Prey

A few weeks ago we launched Multi-Channel Funnels, a powerful tool to help you understand all the online interactions that lead your users to conversion. With five insightful reports, you can now measure the full conversion path, from first interaction to last click. More important, Multi-Channel Funnels provides actionable analysis about how your marketing channels work together, and answers key questions such as:

• How much time does the average user take between first interaction and conversion?
• How many interactions does it take to convert?
• Which of my marketing channels are “assisting” conversions and which are “closers”?

To help you get the most out of this tool, we’ve scheduled a webinar to walk through the new reports and go over common uses with Bill Kee, the Product Manager for Multi-Channel Funnels.

Title: Getting started with Multi-Channel Funnels
Date: Wednesday November 2, 2011
Time: 8am Thailand/Indonesia, 9am Singapore/Malaysia/Philippines/China, 10am Japan, 12pm Sydney/Melbourne, 2pm New Zealand
Register for the webinar

Have questions about Multi-Channel Funnels? Send them to us ahead of the webinar so we can make sure to answer them. You can also vote for the questions you want to see answered most. You can submit your questions on our Google Moderator page.

If you can't attend the webinar, please check the Google Analytics YouTube Channel for a recording about a week after the live event. You can also read more from the initial announcement of Multi-Channel Funnels and watch a video about the tool.

We hope that you will be able to participate!

Posted by Nagalakshmi V, Product Specialist, Google Asia-Pacific

Last month we ran a series of GoMeasure with Google Analytics events across Sydney, Melbourne, Singapore, and Kuala Lumpur. In those four events, Googlers and Google Analytics Certified Partners shared insights into how to get the most value out of Google Analytics’ new features as well as sharing site optimisation and conversion tips.

Today we’re releasing the videos of the presentations from the Singapore and Kuala Lumpur events. The videos are of easy-to-digest bite-sized lengths. So you should be easily able to watch them in between meetings or while taking a break. You can also download the slides if you would like to view them on a bigger screen.



Posted by Vinoaj Vijeyakumaar, Senior Conversion Specialist, Google Southeast Asia

Multi-Channel Funnels are a new set of reports that show which marketing channels your customers visited your site from during the 30 days prior to a conversion or purchase. In this series of three posts, Michael Fox, co-Founder and Director of Operations of Shoes of Prey, shares how he uses these new reports to improve sales for the business. - Ed.

What are Multi-Channel Funnels reports?
We were excited to be one of the earliest testers of Google Analytics’ new Multi-Channel Funnels reports. Multi-Channel Funnels are a new set of reports that show how customers arrived at our site (i.e. which channels they interacted with) during the 30 days prior to a conversion (e.g. newsletter sign-up) or purchase. We get a better understanding of what role website referrals, searches and ads play towards influencing a purchase; and how much time passed between the visitor’s first visit and their purchase. What this means is that we no longer have to base our decisions based on the source of the last click. Using these reports, we can now look at all the channels that visitors may have used prior to converting. This gives us much more powerful insight into which channels are working for us.

I would like to walk you through how Shoes of Prey gained useful insights that helped our business through these sets of reports. Today, in the first of our three articles, I’ll focus on the Top Conversion Path report.



Top Conversion Paths report
We use the Top Conversions Paths report to understand the sequence of channel interactions that led to conversions. For example, if we study this conversion path (the number of times a customer visited our website, and from where) below, we can see that two conversions happened due to a series of interactions where the visitors:

1. First visited us three times via a direct visit (i.e. using a bookmark or typing our URL directly into their browser)
2. Then visited us by clicking on a paid ad
3. They returned twice more to our site, but this time from clicking on organic search results
4. Then they visited us again directly three more times
5. Finally they came to us through organic searches. They ended up purchasing a pair of shoes on the very last search.

We could then further break out these results to see more details, for example, which particular keywords attracted the visitors when they came to our site via Paid Advertising and Organic Search.



Insights: Is there confusion among some of our customers?
When analysing recent top conversion paths, we realised that a significant number of sales occur due to a series of direct visits from people who had typed in the URL or came from a bookmark. Some visitors were making up to 30 direct visits before purchasing a pair of shoes!

It was heartening to see a lot of all-direct visits, as it signified that these visitors had made up their mind to purchase their shoes from us. We realised, however, that we need to take efforts to help our customers design and purchase their shoes in a fewer number of visits. We understand that our offerings could be overwhelming for some customers when they could choose from over four trillion shoe combinations!





Actions: Reducing the number of visits to purchase
We took steps to drive more of our potential customers to our leather videos. We wanted them to learn more about the products in a shorter period of time and encourage them to design their shoes sooner.

We also implemented a website chat solution that allows customers to ask us questions while browsing the site. We can answer their questions in real-time and hopefully help them arrive at a decision sooner.

We have also been continually testing changes to our user interface that would help customers reach a decision on which pair of shoes to purchase. These include testing different forms of wizards and guides, and even highlighting how to get started.

Results: Shortening the purchase cycle
Taking these steps have helped our customers make a purchase decision sooner. In the last three months we’ve seen a 40% increase in our conversion rate and a shortening of all-direct paths before a sale. We’ve seen same-day purchases increase by 20% and 12+ day purchases fall by 8%.




We found the Top Conversion Paths report to be an eye-opener. It clearly demonstrated to us how our potential customers were interacting with our site prior to making a purchase. I encourage you to start looking at your Top Conversion Paths report now - I guarantee that you will find at least one conversion path worth exploring that you had never considered before!

Posted by Michael Fox, co-Founder and Director of Operations, Shoes of Prey

What a crazy two weeks it has been! GoMeasure with Google Analytics did a whirlwind tour through Sydney, Melbourne, Singapore, and Kuala Lumpur. In those four events, Googlers and Google Analytics Certified Partners shared insights into how to get the most value out of Google Analytics’ new features as well as sharing site optimisation and conversion tips.

You can view the presentations from the four events via the below links. We’ll also be providing the videos of the talks from Singapore and Kuala Lumpur next week. Stay tuned!

• Southeast Asia Leg: Kuala Lumpur (Sep 8 2011)
• Southeast Asia Leg: Singapore (Sep 6 2011) 
• Australia Leg: Melbourne (Sep 1 2011) 
• Australia Leg: Sydney (Aug 30 2011)

Posted by Vinoaj Vijeyakumaar, Senior Conversion Specialist, Google Southeast Asia

Google Analytics Certified Partners play an important role in Asia Pacific’s web analytics ecosystem. They are the Google Analytics implementation and reporting experts, and they partner closely with businesses of all sizes to help them improve and grow their online presence. This is one in a series of articles from Google Analytics Certified Partners across the region.

Adrian Tan is one of the founders of clickTRUE Pte Ltd, Southeast Asia’s first Google Analytics Certified Partner. - Ed.


I would like to share an example with you on how our team at clickTRUE use insights from Google Analytics to benefit our clients’ online marketing effectiveness. Recently, a world leading electronic security and alarm monitoring service provider approached us to optimise their reporting and analysis framework. We helped them adopt Google Analytics as a way of measuring the number of leads generated by their website. With Google Analytics we were able to react to changing conditions within days rather than months.


Problem: Non real-time analysis
The client ran several Google AdWords campaigns to drive sign-ups via their enquiry forms. These sign-ups represented the number of leads for their business and provided a forecast of their revenue for the months ahead. The client was used to consolidating the enquiry form sign-ups from their website on a monthly basis and sending it to us for analysis.

We would analyse the numbers and determine how many conversions (i.e. enquiry form sign-ups) were attributed to their AdWords campaigns. We would then suggest and implement changes for their following month’s AdWords campaign so that they could generate a higher volume of sign-ups at a lower cost. Waiting for monthly reports was less than ideal. Since we deal with the Internet, we wanted to measure the performance of our enhancements in real-time! We wanted to cut down this lag to make more timely changes and more quickly achieve the client’s target number of leads per month.


Solution: Integrating Google AdWords and Google Analytics
Being a Google Analytics Certified Partner, we knew that one of the best ways to get near real-time insights about the performance of a website is to use Google Analytics. We worked with the client to implement Google Analytics on their website, and then integrate their AdWords account, so that we could attribute conversions to AdWords clicks.

Here is how we approached the creation of the reporting and analysis framework for the client:

Step 1: Link the Google AdWords account to the Google Analytics account
We first linked the client’s Google AdWords and Google Analytics accounts.

Step 2: Define goals within Google Analytics
We defined a goal in their Google Analytics account as visitors who arrived at a “Thank You” page after submitting their contact details.

Setting up the goal was easy: we took the URL for the “Thank You” page as the goal URL.

With Goals set, we were now able to more accurately assess how each keyword in the client’s AdWords campaign was converting visitors into sign-ups (leads). Better yet, we were able to assess these on a daily basis, and didn’t have to wait for the monthly reports.


Step 3: Setting up the reporting framework
We created a set of custom reports to to address the key performance indicators that were most relevant for the client. Below is one of our custom reports that lists keywords and the associated metrics for clicks, visits, cost-per-click, impressions, clickthrough rate, bounce rate, time on site, and goal conversion rate. If we were to rely on Google Analytics’ standard reports, we would need to combine three reports to get this information. You can get a copy of this custom report here.

Step 4: Taking action by optimising keywords
With the above in place, we are better able to drill down and do optimisation on the keywords instead of just depending on traditional statistics such as clicks, cost per click and clickthrough rates.

For example, when we first ran the campaign, the keyword “CCTV” generated the most number of clicks. We needed to find out if this keyword was effective in producing qualified leads.

On closer inspection, we saw that the keyword “CCTV” was performing poorly in terms of bounce rate and conversion rate.

The bounce rate for “CCTV” was 7.32% worse than the site average. Visitors coming from this keyword left the site without signing up or even visiting any other pages. It indicated a poor visit quality – visitors did not find the content on the landing page relevant.

To help optimise the performance of this keyword, we analysed the actual search query used by visitors that contributed to goal conversions. For example, visitors who searched for “CCTV Singapore” and clicked on the client’s ads were more likely to sign-up and convert.

Such search queries were immediately added as phrase match keywords in the client’s campaign and set with a higher bid to have their ads appear more frequently . This fine-tuning allowed us to only show the ads to an audience that is looking for security solutions rather than to non-relevant searches for “China Central Television” that was also know as CCTV. We also included such non-relevant searches as negative keywords to filter out irrelevant impressions and improve clickthrough and conversion rates.

Through the use of better defined keywords, such as with approproriate keyword matching for the “CCTV” root keyword, we obtained much better conversion rates – increasing the rates from 1.55% to a range of 1.96% to 25% and a corresponding increase in ROI of at least 66%.

Actionable insights on early data results in 114% lift
The time previously spent waiting for monthly reports was now put to good use optimising based on almost real-time data. The lift in leads demonstrates the benefits of this strategy – a 114% increase after the first three weeks of the campaign. The client is now ahead of schedule in achieving their target number of leads and meeting their revenue forecast.

We strive to replicate the above process in all our engagements:

• Setting goals allows us to measure site performance and understand whether we are being successful or where we need to improve.
• Linking AdWords and Google Analytics accounts allows us to assess paid traffic performance in terms of bounce rates and conversion rates.
• Last, but not least, we cannot emphasise enough how important it is to analyse your Google Analytics data on a regular basis and take immediate actions to experience real-time gains.

Posted by Adrian Tan, Co-Founder, clickTRUE Pte. Ltd.

This is part of our series of posts highlighting the new Google Analytics. The new version of Google Analytics is currently available in beta to all Analytics users. And follow Google Analytics on Twitter for the latest updates.

This week we’re going a bit meta with an overview of the new Overview reports in the new Google Analytics. Overview reports were part of the old version of Analytics, of course, but we’ve made some changes to help your analysis.

Anatomy of the Overview Report
Each overview report consists of three sections. There's a timeline graph, some aggregate metrics, and a set of reports.

Whats inside of each of these sections depends on which report you’re looking at. For example, the Visitor Overview shows a graph of visits and metrics like New vs. Returning visitors, while Content Overview shows metrics like pageviews and average time on page.

The Graph
We’ve made a few changes to the graphs in the new Google Analytics, and we'll share them here. You can now make adjustments to the graphs you see in Google Analytics from the buttons on the top right of the graph:

• Switch a graph between Line Chart and Motion Chart
• Graph different metrics: Select from the dropdown or the scorecard

Metrics dropdown

Metrics Scorecard

• Compare two metrics: Graph an additional metric for comparison

• Graph By: Change graph from between Monthly, Weekly, Daily, and even Hourly for some reports

Reports
The bottom section of an overview reports lets you look through a subset of the reports available in that section. You can flip through these reports to see where you want to start your analysis. In the Traffic Sources Overview, we can start by looking at a report of Keywords.

From here we can go view the full report or look at another report, like Referral Sources:

Intelligence Overview
Google Analytics Intelligence automatically searches your website traffic to look for anomalies. When it finds something that's out of the ordinary it surfaces this as an alert. You can also setup your own alerts by defining custom alerts.

Now you can feel like the president of the principality of Analytica with your very own Intelligence Overview report.

The Intelligence Overview report shows you all of your automatic alerts (daily, weekly, and monthly) at a glance. From the Intelligence Overview, you can click on Details to see a graph of the alert and go directly into the GA report. You can also add or review an annotation right from the pop-up graph.

I hope you enjoyed this overview of Overview Reports. Please continue to send us feedback on the new Google Analytics. Stay tuned for next week’s installment in New Google Analytics series.

Posted by Trevor Claiborne, Google Analytics Team

Custom Variables allow website owners to extend Google Analytics’ measurement capabilities and track information that is meaningful to them. In this series of three articles, Barbara Pezzi, Director of Analytics and Search Optimisation for Fairmont Raffles Hotels International, shares how she makes use of custom variables to better understand how to better engage with her customers. You can familiarise yourself with custom variables in Part 1 and Part 2 of this series. – Ed.

Our hotels are located all over the world. As a result, our website visitors are just as geographically diverse. We are planning to expand our language offerings this year and want to understand how each language we currently offer is performing and which languages we should prioritise for.

On the Swissotel site we offer content in English, German, Russian, Spanish, French, Arabic and Chinese. We don’t have separate websites for each language and, in some cases, only part of the content is translated. For example, we only provide Chinese translations for content related to our hotels in China. Furthermore, the checkout pages are only available in German and English and located on a separate subdomain. As a result, it is very difficult to assess how our content is being consumed in different languages and the impact of language on our sales.


Content Languages – Page level custom variable
To help understand how our foreign-language content is consumed, I decided to use page-level custom variables in Google Analytics. Page-level custom variables apply to a single pageview and allow you to track attributes related to that page such as category, section, author, or, in our case, language. They are very useful for grouping together related pages in our reports.

The custom variables code used is fairly straightforward. On each page, we set a page-level custom variable called “content_language” and set its value to the language code for the language that the page content is written in.

For example, on all our English pages we have:

_gaq.push(['_setCustomVar', 1, 'content_language', 'EN', 3]);

On each of our German pages we have:

_gaq.push(['_setCustomVar', 1, 'content_language', 'DE', 3]);

With these page-level custom variables in place, I can see how popular each language is:

By creating an advanced segment based on this custom variable, I can now view which keywords are generating traffic for each language and make any necessary tweaks to our SEO and paid search campaigns.

Additionally, by applying the same advanced segment to our product report, I segment which hotels are being booked in a given language. We use this insight to coordinate our marketing strategies so that we are promoting the right properties in the right languages to the right markets.

We would not be able to gain such valuable insights without custom variables and I am looking forward to the day Google increases the maximum number of custom variables, since I have already used up all my slots.

That brings our series on custom variables to an end – for now. I hope that these posts have inspired you to take a closer look at your site, identify dimensions that are truly unique and important to your business, and adopt custom variables to measure them.

Posted by Barbara Pezzi, Director of Analytics and Search Optimisation, Fairmont Raffles Hotels International

This is part of our series of posts highlighting the new Google Analytics. The new version of Google Analytics is currently available in beta to all Analytics users. And follow Google Analytics on Twitter for the latest updates. This week we’re sharing a new feature, the Site Speed report.

At Google, we are passionate about speed and making the web faster, and we are glad to see that many website owners share the same idea. A faster web is better for both users and businesses. A slow loading landing page not only impacts your conversion rate, but can also impact AdWords Landing Page Quality and ranking in Google search.

To improve the performance of your pages, you first need to measure and diagnose the speed of a page, which can be a difficult task. Furthermore, even with page speed measurements, it’s critical to look at page speed in context of other web analytics data.

Therefore, we are thrilled to announce the availability of the Site Speed report in the new Google Analytics platform. With the Site Speed report you can measure the page load time across your site.

Uses for the Site Speed Report

• Content: Which landing pages are slowest?
• Traffic sources: Which campaigns correspond to faster page loads overall?
• Visitor: How does page load time vary across geographies?
• Technology: Does your site load faster or slower for different browsers?

One effective use of the Site Speed report is to measure speed for your most critical pages. For example, you might learn that the target audience of your site is located in a geographic region that experiences slower page speed. Or, you might learn that certain pages on your site run slower in some browsers. In addition to the Site Speed report, we’ve created a custom report that you can use to help answer these questions: view the Site Speed custom report.

Setting up the Site Speed Report
By default, page speed measurement is turned off, so you’ll only see 0’s in the Site Speed report until you’ve enabled it. To start measuring site speed, you need to make a small change to your Analytics tracking code. We have detailed instructions in the Site Speed article in the Analytics Help Center. Once you’ve updated your tracking code, a small sample of pageviews will be used to calculate the page load time.

We’re excited to bring this important metric into Google Analytics as part of the new Google Analytics platform. Please continue to send us feedback on Site Speed and the rest of the new Google Analytics.

By Zhiheng Wang, Phil Mui on behalf of the Google Analytics team and the Make the Web Faster team

This is part of our series of posts highlighting the new Google Analytics. The new version of Google Analytics is currently available in beta to all Analytics users. And follow Google Analytics on Twitter for the latest updates. This week we’ll be discussing how to use updated custom reports.

Every website is different, yet we focus much of our time on the standard reports in our web analytics tools. Custom reports have been an integral part of Google Analytics since 2008. With the new platform, we took a close look at how we could improve the custom reports to make them more usable and powerful.

The Custom Reports tab
For starters, custom reports now live under their own tab, which you can find next to My Site in the main menu bar.

The overview shows a list of all the custom reports available for your profile. You can also view, edit, or share a custom report, and, of course, you can also build a new custom report.


Building a custom report
As with the previous version of Google Analytics, you build a custom report by picking the metrics and dimensions you want. For the new platform, we’ve made some enhancements. Let’s walk through the creation of a custom report for measuring the effectiveness of content on this blog (borrowing from one of Avinash’s awesome custom reports).


Getting the right data
We saw that custom reports were most useful when focused on subset of data. For my blog report, I've decided that I want to only focus on referral traffic. In the old version, I’d have to combine an advanced segment with my custom report to do this analysis. With the new platform, we’ve made it possible to make the filter part of your custom report.

You can add multiple filters to the same report, and filter on dimensions other than those you’ve chosen to use in the report. Best of all, these filters are saved as part of your custom report. As soon as you (or your boss) opens the report, you’re looking at the data you need.


Organizing your report
Like the current version, you can build multiple report tabs into your custom report. This is helpful to organize your report, or build different views for people across your organization. In the new Google Analytics, you’re no longer restricted to using the same dimensions for each report tab, which allows you to truly get all of the data you care about in one custom report. There are two types of report tabs available: Flat Table and Explorer tabs.

Explorer report tabs are similar to the report view that is used across Analytics. They allow you to drill down into data, as well as add a secondary dimension. When creating an Explorer tab, you can also create Metric Groups, which help further organize your report for easier analysis. For our example, I've built out an Explorer tab focused on content quality metrics with a drill down into where the traffic came from.

Flat Table report tabs allow you to look at two dimensions side by side, meaning you don’t have to click to drill down into your data. We’ve created this report view to make it easier to export the information you care about, email it to a colleague, or simply print it out. For the example report, I have a Flat Table tab focused on where the traffic came from and the quality of that traffic.

And here's the finished report:

Sharing your custom reports
Once you've finished creating your report, you might want to share it with your team. One of the most widely used features of Custom Reports has been sharing, which allows you to share a link to your custom report configuration with others.

Like the current version, sharing a custom report in the new Google Analytics only shares the structure of the report, not the data from your account. There is one difference to keep in mind, when you share a custom report in the new version, the link will always reflect the state of the report when you first created the link. So, if you create report, share it with your colleagues, and then make further changes, the link you shared will still point to the first version of the report. You can share your reports from the Custom Reports overview. Just click the share link:




And here’s a link to the custom report example we’ve referenced throughout this post: http://goo.gl/McSBl.


Finding a home for your old custom reports
Did you spend a lot of time creating the perfect custom report in the old version? Not to fear: we’ve created a migration tool to help you migrate your reports from the old version to the new Google Analytics. From the Custom Reports Overview, you’ll see a section called Migrate Custom Reports. It will let you know if you have reports to be migrated. Keep in mind that migration only works one way. Once you move your reports over the new version, you won’t be able to use them in old version.

Using standard reports to analyze your website can only take you so far, which is why we’ve put so much effort in making custom reports more powerful and easier for Google Analytics v5. Please continue to give us your feedback on the new Google Analytics. Happy analyzing!

Posted by Kate Cushing, Google Analytics team

Custom Variables allow website owners to extend Google Analytics’ measurement capabilities and track information that is meaningful to them. In this series of three articles, Barbara Pezzi, Director of Analytics and Search Optimisation for Fairmont Raffles Hotels International, shares how she makes use of custom variables to better understand how to better engage with her customers. You can familiarise yourself with custom variables in part one of this series. – Ed.

We recently introduced the option of booking more than one room within a single reservation on our Fairmont sites. In the past, if a visitor wanted to book three rooms, she would have had to go through the checkout process three times.

This new option greatly improved the booking experience for our customers. We knew this both intuitively and anecdotally, but we wanted to understand the impact of this change with data. We wanted to understand the popularity of this new feature, which group of hotels benefited the most (e.g. city hotels or resorts), and what the impact has been on our booking rates.

Booking types - Session-level custom variables
We used a session-level custom variable in Google Analytics to help us answer these questions. Session variables are applied to a single session and help you understand specific behaviours that happen during a particular session or visit.

As with all custom variables, the code to add to your Google Analytics snippet is very simple: a single function placed in the confirmation page above the _trackPageview() call. We set a custom variable called “booker” each time a booking was made, and its value would be “single” or “multiple” depending on the number of rooms booked.

_gaq.push(['_setCustomVar', 1, 'booker', 'single', 2]);


Analysing the data
Using this custom variable, we could conveniently assess the proportion of sales through our sites for single or multiple rooms.



We are also able to assess corresponding traffic and conversion data and even see the increased value of “multiple” booking visits. By creating an advanced segment, I could identify which traffic channels sent me these customers and adjust my marketing activities accordingly.




Identifying relevant keywords
Since organic search traffic from Google is sending us almost 45% of all multiple “bookers”, we decided to drill down deeper and look at the keywords that sent us the traffic. We do a number of things with these keywords: add them to our paid search campaigns, optimise for them in our SEO strategy, and use them as seeds for identifying new keywords. Our multiple room bookers, for example, seem to favour our more traditional hotels and resorts. With this information, we can now look at adding content to our websites that would appeal to this group.



I can also easily identify which hotels seem to be more popular with multiple room bookers and advise the property accordingly. They can then use this information to create new offers that might appeal to small groups or families who are likely to book multiple rooms.


Identifying key markets
We were interested in identifying the countries of residence of our customers, and in particular, which locations were more likely to provide us with multiple room bookings.



Based on the data, we can now run adjust our marketing campaigns in the best performing markets to include multi-room offers.


Applying our learnings
Session-level custom variables allowed us to effectively analyse a scenario that was unique to our websites and wasn’t immediately available in Google Analytics standard e-commerce reports. We are now in the process of introducing the multi-booking functionality to the Swissotel websites and feel that we have a head start in ensuring its success thanks to the learnings we gained from our Fairmont sites.

Stay tuned for part 3 in this series, in which I will discuss page-level custom variables.

Posted by Barbara Pezzi, Director of Analytics and Search Optimisation, Fairmont Raffles Hotels International

This is part of our series of posts highlighting the new Google Analytics. The new version of Google Analytics is currently available in beta to all Analytics users. And follow Google Analytics on Twitter for the latest updates.

I’m very excited to announce that the new version of Google Analytics is now available to all Google Analytics users in all languages. When you sign into Google Analytics you’ll see a link to the new version in the top right of your account.

If you haven’t, we encourage you to try the new version today. There’s a host of new features to help you do better analysis. We’re also constantly making updates to the new version.

Here’s a five things to try in Google Analytics v5:

• Create an additional dashboard to focus on your important metrics
• Set up an Event Goal to track interactions like downloads and video engagement
• Graph and compare any two rows over time with Plot Rows
• Check out your favorite report (Did it move? Our Report Finder can help)
• Flip between your different profiles and sites while staying focused on the same report

So what happens next? You’ll continue to have access to both versions of Google Analytics, and you can switch between them at any time. If you find anything that doesn’t work or could be better, let us know. We especially want to hear about issues that force you back to the current version. We’re still hard at work on enabling a few features from the old version including PDF export and email scheduling, and they’ll be coming soon.

Take some time this week to try the new Google Analytics, and let us know what you think. We’ll continue making improvements and adding functionality. Next week, we’ll be covering how to use custom reports in the new version.

Posted by Trevor Claiborne, Google Analytics Team

This is part of our series of posts highlighting the new Google Analytics. The new version of Google Analytics is currently available in beta to a number of Analytics users. We’ll be giving access to all users soon. Sign up for early access. And follow Google Analytics on Twitter for the latest updates.

We recently announced the new version of Google Analytics. If you’re one of the early users, you may have noticed that there is also a new help center dedicated to this latest version. You can get to the new help center via the Help links that appear throughout the user interface. But, regardless of whether you’re already using the new version, you’ll find the new help center at http://www.google.com/support/analyticshelp/.

In addition to addressing features for the new version (see What’s New), we’ve redesigned the Help Center completely. For this launch, we have:

• organized the help center into five topics, each addressing a key usage need,
• improved the organization of all topics, and
• reduced content duplication.

You can compare our new help center to the older version at http://www.google.com/support/analytics. Please post a comment to let us know what you think. We’d love to hear your thoughts and suggestions.

Also, look for a survey in a few weeks. We’ll be actively gathering your input on this Help Center in preparation for the next round of improvements.

Posted by Patricia Boswell, on behalf of the Analytics Education Team

Custom Variables allow website owners to extend Google Analytics’ measurement capabilities and track information that is meaningful to them. In this series of three articles, Barbara Pezzi, Director of Analytics and Search Optimisation for Fairmont Raffles Hotels International, shares how she makes use of custom variables to understand how to engage more effectively with her customers. – Ed.

One of the latest features of Google Analytics that I’m excited about is Custom Variables. Google Analytics has a very extensive list of default dimensions and metrics, such as time on site and traffic sources, that it tracks for your website. While these dimensions and metrics cover most websites’ needs, every website and business is unique, with its own set of objectives and goals. You might want to track certain visitor segments or user behaviour that is not reflected in the default set of metrics.

Custom variables allow you to extend Google Analytics’ default metrics and dimensions to track information that is meaningful to you by labelling interactions with your site at three levels: visitor, session and page. You can then segments and run custom reports based on these variables. You can learn all about the technical implementation of custom variables in the Google Analytics Code Site.

The possibilities are endless with custom variables. You could for example:

• identify segments of visitors based on a specific landing page that they visited
• identify staff-visits vs non-staff visits
• identify and analyse sessions during which a visitor posted a comment on your blog or subscribed to your newsletter

We use custom variables for a number of purposes on our Fairmont and Swissotel websites. Over the next few weeks, I will walk you through three examples, one for each variable type (visitor, session, page).


Loyalty Members – Visitor-level custom variables
A segment of our customers that we focus on because of their value to us are our loyalty program members. When a customer signs up to our Club Swiss Gold program, they start as a ‘Classic’ member, and then progress to become an ‘Elite’ member.

We want to understand the difference in behaviour and purchase patterns between our Classic and Elite members. Google Analytics can’t easily provide us with that insight by default, but with visit-level custom variables, we can answer this question.

Visitor-level custom variables allows us to distinguish categories of visitors across multiple sessions. We are essentially bucketing our users into our own custom categories. Visitor-level custom variables are best used for attributes of a visitor, such as their membership level or product preference, that you wish to track over multiple visits.

On our Swissotel site, we set the visitor-level custom variable whenever a member logs in by inserting a line of code into our Google Analytics tracking code. The code involved is very simple: a single function placed above the _trackPageview() call on the same page:

_gaq.push(['_setCustomVar', 1, 'Membership', 'logged_in_classic', 1]);

We are now able to distinguish between members and non-members as well as membership levels. Within the custom variable report, I can now see at a glance information like site usage, goal conversion data, and ecommerce data, which is broken down by membership levels.

I can use this custom variable to create an advanced segment for additional insights, such as countries of our classic members and conversion rates across countries. We use these insights to identify any potential deficiencies in language coverage or regional product preference.

Or, we can look at which property classic members book the most and use that insight to create more offers for popular hotels and increase bookings for less popular properties.

We are now in the process of updating our loyalty program, and these insights are invaluable in helping us make improvements based on our customers’ preferences.

Stay tuned for part two of this series, in which I’ll cover how we use session-level custom variables on Fairmont’s sites.

Posted by Barbara Pezzi, Director of Analytics and Search Optimisation, Fairmont Raffles Hotels International

This is part of our series of posts highlighting the new Google Analytics. The new version of Google Analytics is currently available in beta to a number of Analytics users. We’ll be giving access to even more users soon. Sign up for early access. And follow Google Analytics on Twitter for the latest updates.

Real Analytics ninjas use goals. Google Analytics has always had URL Goals (when a visitor reaches a specific page). In 2009, we added Engagement Goals to track success metrics around visit depth and time on site. With the new version of Google Analytics, we’ve added one more: Event Goals. This was one of our most requested features, and it gives you even more reason to use event tracking.

A brief intro to Event Tracking
You can use Event Tracking in Google Analytics to track visitor actions that don't correspond directly to pageviews. It's a great fit for tracking things like:

• Downloads of a PDF or other file
• Interaction with dynamic or AJAX sites
• Interaction with Adobe Flash objects, embedded videos, and other media
• Number of errors users get when attempting to checkout
• How long a video was watched on your site

Events are defined using a set of Categories, Actions, Labels, and Values. Here’s how you might set up event tracking for tracking downloads of whitepapers and presentations.

These interactions all have potential business impact, but until now you couldn’t track them as goals in Google Analytics. Let’s look at three ways you might use Event Goals on your site.

Tracking Downloads
Suppose you run a business to business (B2B) website and offer whitepapers (as a PDF download) in order to attract leads. You drive traffic to this page through advertising. You can track the number of downloads using event tracking. For example, we can use the category to designate the click was of type “download”. We can use the action to designate the download was a “whitepaper” and we can use the label to identify the actual whitepaper that was downloaded.

With the new Google Analytics, configuring this as a goal is easy. We simply match any event with the category of “download” and the action of “whitepaper”. Finally we set the goal value as 20.

Tracking Time Spent
Event tracking is powerful because you can track values, along with the category, action, and label. Going back to our B2B website, suppose you have a embedded product demo video on your page. With a little JavaScript, you can track the time a user spends watching the video and send that number back to Google Analytics as an event value.

With Event Goals, you can now set up a goal based on this value. In this example, we’ve configured a goal when a user spends over 180 seconds watching the product demo.

Using The Event Value As The Conversion Value
Traditionally, the only way to set goal values was when creating the goal in Google Analytics, or from the tracking code using ecommerce tracking. With Event Goals, you have another option: using the event value as the goal value.

Again putting yourself in the shoes of a B2B website owner, you realize not all your whitepapers bring in the same quality of lead. The lead value associated with downloading a certain whitepaper is $20, but the lead value from a different whitepaper is $35. Rather than creating a separate goal for each, you can pass the values 20 and 35 as the Event Value, and then set up the goal to use the actual Event Value:

Now when a goal is matched, the value passed in the event will be used as the goal value.

These are just a few examples of how you can take advantage of Event Goals in the new Google Analytics. You can read more on how to implement Event Tracking on Google Code and how to set up goals in the new Analytics. We’re constantly giving more of you access to the new version. If you don’t have the new version yet, you can sign up for earlier access.

Posted by Nick Mihailovski, Google Analytics Team

This is part of our series of posts highlighting the new Google Analytics. The new version of Google Analytics is currently available in beta to a small number of Analytics users. We’ll be giving access to more users soon. Sign up for early access.

The graph on top of most Google Analytics reports is designed to give you a quick overview of your site’s performance over time. From the graph it’s easy to spot trends and understand how your traffic has changed over time. One request we heard was the ability to quickly focus the graph on a particular row of data. While you could do this with a drill-down report or using an advanced segment, we saw this as an opportunity to provide an easy way to do quick comparisons in the new Google Analytics.

Say for example you’re examining your site’s traffic by traffic source. You can see there are peaks and valleys in the traffic, but if you want a sense of the major contributors, you need to dig into the table.

With Plot Rows, you can graph any two rows alongside the overview. You can then easily determine how much a row contributes to the whole. Or you can compare two lines against each other to look for comparison trends.

To use Plot Rows, just tick any one or two checkboxes next to the rows you want to plot, then at the bottom of the table, hits the Plot Rows button.

Remember, that some reports like New vs. Returning default to a Pie Chart view. This doesn’t mean you can’t use Plot Rows, just switch the view to Data, and you’re good to go.

Here’s a quick video showing this in action:

Usage Tips
When looking at continuous metrics, like Visits, Plot Rows is most revealing when exploring the rows of similar scale, for example to see how they contribute to the whole and change over time. When looking at rows at different scales the graph will be more informative when using percentage metrics like Bounce Rate.

In this example, we’re looking at organic search traffic driven to the Google Store from Google and Bing. One would not expect that Bing users are actively looking to buy Google merchandise (like this awesome t-shirt), so the number of visits is understandably low. Since the traffic from Bing is relatively low, the graph doesn’t share much we didn’t already know from the table.

In the new version of Analytics you can quickly graph any of the metrics in the scorecard (the bar on top of the graph) by clicking on the metric in the scorecard. Looking at Bounce Rate, we can see that over time the Bounce Rate from Google search (orange) has dropped, which has reduced the overall Bounce Rate of the site (blue), while the Bounce Rate from Bing (green) has more or less stayed constant.

You can use Plot Rows in just about any report that has a data table. Let us know if you find a place you want this functionality that doesn’t already have it. Also, we’re planning to give a bunch more of you access to the new version this week. Be on the look out!

Posted by Trevor Claiborne, Google Analytics Team