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Take your social strategy to the next level with Learn with Google Hangouts and Webinars

Wednesday, 31 October 2012

Over the next few weeks, we’re offering four opportunities to learn more about Google+ for your business. We kick off with a Learn with Google Hangout on Air with bestselling author +Chris Brogan on November 5th at 10am PT / 1pm ET. Chris will cover tactics for successful social marketing and discuss his new book, “Google+ for Business: How Google's Social Network Changes Everything.” RSVP for the Hangout on the Google+ Event page


Learn Chris’s recipes for how to grow and engage your Google+ community to build your brand and drive your business’s visibility and conversions. Hear about Chris’s own experiences helping companies succeed in their content marketing and social projects. Chris Brogan is a New York Times bestselling author, CEO of Human Business Works, and advises companies on marketing, business strategy, communications and more.

If you have a question for Chris, leave your question as a comment on the Google+ Event.

Boost your success with Google+

Want to learn more about using Google+ for your business? Sign up for our Learn with Google webinars. Here are some great upcoming webinars to help you get the most out of social for your business:
  • Social that Adds Up: Performance and Measurement (Thurs, Nov 8, 10am PT / 1pm ET)
  • Supercharge your Social Media Initiatives with Video (Wed, Nov 14, 10am PT / 1pm ET)
  • Building a Digital Brand with Google+ (Thurs, Dec 6, 10am PT / 1pm ET)
Posted by the Google Analytics team

Return on investment analysis for all your digital channels

Tuesday, 30 October 2012

Google Analytics has been a great place to analyze the performance of your Google advertising programs, but a piece of the puzzle has been missing: analyzing return on investment across all your digital channels. That’s why we’re happy to announce our new Cost Data Import tool, now available in public beta. This tool allows Google Analytics users to import their cost data from any digital source -- such as paid search providers, display providers, affiliates, email, social and even organic traffic.

Your imported cost data can be viewed in two places: in a new report called Cost Analysis in Traffic Sources, and in the newly publicly available Attribution Modeling Tool. These reports show you how all your digital marketing channels are performing compared to each other, so you can make better decisions about your marketing programs.

To take advantage of cost analysis, you can upload data in two ways: via a self-service API, or using solutions created by independent application providers. These solution providers include:


Our early customers are already loving it! Here are some success stories:
“Most of our paid search and social advertising decisions were made strictly based on a conversion pixel and CPA. We really didn't have the resources or the energy to continue to pull data and work it backward for detailed analysis. Now that we can import raw data into Google Analytics using NEXT Analytics v5, we can quickly and easily look for insights - just as we do with Adwords."
-- Darcy Foster, President, Natural Wellbeing (with Cardinal Path
“Before, we used to manually match paid search cost to revenue data in Excel. With AutomateAnalytics.com GA Data Uploader, we have been able to automate this process, and can now much more accurately measure paid search campaign ROI within Google Analytics."
-- David Jaeger, Director of SEM, National Positions 
“Using the ‘In2GA’ cost data import tool from ShufllePoint, our partners at E-Nor can improve the performance of our paid search channel more efficiently.This translates into quicker insights comparing campaign metrics, ad effectiveness, and keyword performance at one glance instead of logging into multiple systems. Any application or feature that streamlines data collection for analysis, ultimately impacting the bottom line positively, is welcomed. Thanks for the continued innovations and look forward to more.”
-- Michael Rosito, Founder & President OEMPCWorld.com
Cost Data Import will be rolling out over the next month. If your account has been enabled, you should be able to see the Cost Analysis report show up in the Traffic Sources menu on the left-hand side of the Google Analytics interface (in the Standard Reporting tab). We hope this tool will provide a clearer view of your media performance across all your channels and help you make more informed budgeting decisions.


Attribution Modeling for Digital Success: Webinar this Friday + Public Whitelist

Last year, we launched Multi-Channel Funnels, giving marketers insight into how customers interact with multiple touch points prior to conversion. Since then, we’ve begun to see a great shift in the industry, as marketers move away from simple, last click attribution, toward a more holistic picture of how digital marketing channels work together to drive conversions.

Earlier this year, in Google Analytics Premium, we added the Attribution Modeling Tool, which lets marketers build models that distribute the credit for conversions across channels and touchpoints, and quickly compare multiple models side by side. We’ve received great feedback about how the tool provides fast and easy insight into channel value.



Yesterday at the Google Analytics Summit, we announced wider availability for the Attribution Modeling Tool through a public whitelist. We also shared our plans for a new 90-day lookback window, better sampling controls, and the ability to import cost data for use in attribution models.  To help you get started, this Friday we’ll host a webinar, Attribution Modeling for Digital Success, giving an overview of the tool. We’ll cover the opportunities and challenges of attribution modeling, how to interpret and build models, and ways to take action on the results.

Webinar: Attribution Modeling for Digital Success
Day: Friday, November 2
Time: 10am PST / 1pm EST / 6pm GMT
Webinar sign-up: goo.gl/YTulu
Whitelist sign-up: goo.gl/uHckk

A recording of the webinar will be available on the blog and YouTube soon afterward. You can also check out our attribution playbook and product fact sheet for more background -- and you can view earlier webinars in our Attribution webinar series.

Hope to see you at the webinar, and happy modeling!

Google Analytics Summit: What’s New And On The Horizon For 2013

Monday, 29 October 2012

Every year, Google Analytics Certified Partners and Premium customers descend upon Mountain View for our annual summit. Google Analytics team members share a glimpse into the future of Analytics, and GACPs network and share ideas. Previously what happens at the summit stays at the summit. But starting this year we decided to share the latest and greatest with our wider community. Following is round up of the cool things we're working on which we shared at the Summit.


Paul Muret, Google Analytics Engineering Director, delivering opening keynote

Universal Analytics
This morning, we announced the launch of Universal Analytics, which helps customers tailor Google Analytics to their needs, integrate their own datasets and ultimately get a more complete vision of the entire marketing funnel. Read more in our announcement blog post

Attribution Modeling Tool Public Whitelist
Since April 2012, Premium customers have been using the Attribution Modeling Tool to build models that give credit to all of their digital channels, providing insight into the impact of various marketing programs as they work together to drive sales and conversions. Today, we’re beginning a gradual public rollout of the Attribution Modeling Tool. Please register for our webinar this Friday to learn more, or request early access to the whitelist.

Cost Data Import
Google Analytics now allows users to import their cost data from any digital source -- such as paid search providers, display providers, affiliates, email, social and even organic traffic. This allows you to measure performance of all your digital programs side-by-side. Cost data import will be rolling out over the next month.

Customer Lifetime Value (CLV)
Customer Lifetime Value is a feature being worked on for 2013, and shows the dollar amount of money that an individual customer will spend with a given business in the future. Its a very powerful feature, putting the types of analysis marketers need to drive smart decisions into their hands. 

Our CLV reports will help you:
  • Value segments or all of your customer base
  • Decide how much to spend acquiring new customers in a given segment
  • Decide how much to spend retaining certain customers (e.g. remarketing)
  • Rank customers
  • Measure success of marketing actions
Recency & Frequency
Finding your most valuable customers leads to smarter marketing decisions, improving your spend allocation and customer relationship management. Recency, Frequency, and Monetary Value (RFM) are three powerful behavioral metrics that savvy marketers have been using for decades to identify exactly these customers. With these forthcoming reports, we are bringing the power of RFM to Google Analytics. Watch out for these reports in 2013. 

Custom Dimensions / Metrics 
Dimension widening (a feature activated by Universal Analytics) enables you to easily add information like CRM data to your Google Analytics account. You can, for example, widen an advertising campaign by adding cost data to get a clear picture of the ROI on your marketing effectiveness.

Note that custom dimensions and custom metrics are just like the default dimensions and metrics in your Analytics account, except you create and define them yourself. You can use them to collect and segment data such as demographic data, which isn’t automatically collected.

Premium International Expansion
It’s been a year since we launched Google Analytics Premium to better meet the needs of our enterprise accounts. With the strong demand we’ve seen for Premium in the United States, United Kingdom and Canada, we are now planning to launch in at least 8 more countries: Japan, Brazil, France, Germany, Netherlands, Italy, Spain, and Norway for 2013. 

Mobile 100%
With ever-expanding mobile application marketplaces and a shift in focus to mobile, measuring apps is more important now than ever. With this, we’re excited to be moving Google Analytics Mobile App Analytics out of closed and into open beta. We’ve listened to feedback from more than 5,000 mobile app developers during the closed beta, improved the product and are now making it available to all developers and marketers.  

We’re excited to push Analytics forward into the future with new features and reports which help marketers and businesses become more data-driven. 

Posted by the Google Analytics team

Re-imagining Google Analytics to support the versatile usage patterns of today's users

A typical consumer today uses multiple devices to surf the web and interact in many ways with your business. For most large businesses, already swimming in many sources of hashed data, it’s an enormous challenge, but also an incredible opportunity. 

Measurement today is evolving from technology that counts site traffic into a broader system that measures your effectiveness in advertising, sales, product usage, support, and retention. Ultimately, this sort of integrated measurement can help you deliver the best service, products, and experiences for your customers.

We’ve been developing solutions, like Google Analytics Premium and Mobile App Analytics to advance this vision. For large enterprises, such as Premium customers and those who want to work with APIs, we're now starting to offer “Universal Analytics.” This will help these customers tailor Google Analytics to their needs, integrate their own datasets and ultimately get a more complete vision of the entire marketing funnel.

The new tools offered by Universal Analytics via the new Measurement Protocol (an API that enables you to send your data to Google Analytics) can help you measure the how people actually become and remain loyal customers:
  • Consumers use multiple devices.
Mastering data on your website is no longer sufficient - larger clients are increasingly asking for a cross platform view of their data in Analytics. The tools from the Measurement Protocol allow you to seamlessly send your own data about your customers  and business (from any digital device that you are measuring) to your Analytics account. This can help you see how users interact with your brand from multiple touchpoints - phones, tablets, laptops or more - in one place. 
  • The world is mobile.
We announced Mobile App Analytics at I/O in 2012 as a beta. It’s been delivering great results for clients. Universal Analytics now enables you to measure your marketing more holistically by integrating this data with your Google Analytics account. 
  • Cross-channel measurement is essential.
Cross-channel information is more important and more diverse than ever before. Universal Analytics, via the Measurement Protocol, lets you sync your own data from across various marketing channels, so you can discover relationships between the channels that drive conversions.
  • Your business is unique. 
Not every campaign (or app, or website!) is the same, and sometimes, depending on your business and goals, you want to learn more about a particular aspect of the way visitors interact with your business. With Universal Analytics, you can integrate your own data and can customize the metrics that matter to you - beyond website visits.  Google Analytics can deliver the custom metrics you want, in the same report you’re used to, based on the customized data you provide.

As a Google Analytics user, Universal Analytics won’t mean any changes in your account. But if you’re a large enterprise that is interested in exploring the integration options, you can learn about getting started in our help center.

Posted by Manav Mishra, Group Product Manager, Google Analytics

How to Prove the Value of Content Marketing with Multi-Channel Funnels

Friday, 26 October 2012

The following is a guest post contributed by Josh Braaten, Senior Online Marketing Manager at Rasmussen College, Google Analytics enthusiast, and avid content scientist.

Conversion is rarely straightforward, especially for products or services with lengthy or complicated buying cycles. Working for a college has made it clear to me that every consumer is different, and so are their research needs as they navigate their unique buying process. 

It takes a holistic content strategy to address the extensive information needs of potential students, and rarely do blogs and other types of content marketing get the credit they deserve for the role they play in influencing conversion.

Luckily, Google Analytics Multi-Channel Funnels provides marketers with amazing new ways to see how users interact with web content on their path to conversion and to prove the value of content marketing.

Introducing Google Analytics Multi-Content Funnels
Consumers begin any major investment in the awareness/discovery phase, are triggered into a search/consideration phase, and finally end up at their buy/close phase when they take the conversion action. Imagine how your content strategy could perform if you understood how consumers interact with your website content as they navigate their investment decision. 

That’s where the idea of Multi-Content Funnels started. To be clear, Multi-Content Funnels is not a new Google Analytics feature, but rather a specific application of the existing Multi-Channel Funnels reporting features that illustrates the direct and indirect effects of your website content instead of your marketing channels.

Multi-Channel Funnels launched a little over a year ago as a way to help show how users interact with your marketing efforts over multiple visits. By default, these reports are configured to report the relationships between marketing channels (e.g., paid search, social media, email), but we’re going to modify them to demonstrate the value of content marketing.

The key to this type of analysis is being able to use the Landing Page URL data attribute when you create Channel Groupings and Conversion Segments within a Multi-Channel Funnel report. When I first wrote on their inbound marketing benefits, Multi-Channel Funnels didn’t support this deep dive into your website content because they didn’t include landing page in the source data.

Turns out the Google Analytics team had it on the road map and added it to Multi-Channel Funnel reports within the last few months. Content marketers, get ready to geek out with these content-based applications of the Google Analytics Multi-Channel Funnel reports.

Building Content-Based Channel Groupings
The first major application of Multi-Channel Funnels for content marketing is to create Channel Groupings based on your content, which will demonstrate the most common content paths users take to conversion over the course of multiple visits.

Start off by creating a new Channel Grouping within the Top Conversion Paths report. You’ll want to group the major content sections of your website together into channels.

For example, here I’ve created this Channel Grouping that corresponds to the Degrees Catalog section of our website that includes any landing page URL containing “/degrees.”

Creating a Channel Grouping in Multi-Channel Funnels:

I also included channels that correspond to each of the major content sections of the website as I built out this content-based Channel Grouping. This is what the content-based Channel Groupings of a college website looked like when I was done with them:

Content-Based Channel Grouping:
Your own content-based Channel Groupings will likely be different for every website, but each should include major product directories or service listings, blogs, sections that answer specific questions or solve specific problems, whitepapers, ebooks, etc.

Top Content Conversion Paths
Once the content-based Channel Groupings are set up, we’re able to access the Top Conversion Paths report, which instantly becomes the content marketer’s best friend because it shows how many visits it takes before visitors convert, and how they start their website experiences for each visit.

You can use the Channel Groupings that correspond to specific content sections as with the screenshot above, or you can apply even broader Channel Groupings to provide a high-level view of the most common content paths towards conversion by marketing intent, consumer action, or both. 

Channel Groupings Based on Buying Cycle Path
Creating Channel Groupings based on marketing intent and the consumer buying cycle requires a deep understanding of how consumer interact with your website. These Channel Groupings can be created by combining multiple sections of the website when constructing each Channel Grouping, depending on which phase of the buying process they facilitate:

Pairing this information with traffic and conversion data makes it clear where to focus resources for new types of content, content edits, and expansion of existing website content, as well as demonstrates which parts of our content marketing strategy are driving results.

(Fascinating side note: Looking beyond the most popular conversion paths, some degree seekers’ research processes can see them returning to the website 50 times or more before they are confident in their conversion decision. As a student of web analytics, the next question is whether this conversion path is long because it should be, or is it fraught with unnecessary abandonment that can be overcome with improvements to the content?)

A Long Conversion Path:


Determining the Value of Specific Content with Conversion Segments
Channel Groupings are half the fun because they can only help to organize and present data. To determine the value of specific types of content, we need to create custom Conversion Segments to pair with Channel Groupings

Content-Based Conversion Segments in Multi-Channel Funnels:

Custom Conversion Segments are easy to create and work just like any other segments in Google Analytics, however, these also include the ability to segment-based interaction: First interaction, last interaction, any interaction, and assisting interaction.

Custom Conversion Segment Setup:

This segment captures conversions where the last visit on the conversion path landed on the blog. Most of Google Analytics conversion reports are based on the last interaction, but this segment allows you to explicitly specify between first interaction, last interaction, any interaction, and assisting interactions.

As a content marketer, discovering some blogs assist 150 percent more conversions than they produce directly was a powerful revelation, one that was made possible by content-based Channel Groupings and Conversion Segments applied to Google Analytics Multi-Channel Funnels.

The Many Uses of Multi-Channel Funnels for Inbound Marketing
Understanding how consumers interact with your website content is the first step in providing them with the best experience possible – the primary goal of every modern SEO and content marketer. Those who understand and execute content strategy with this knowledge in mind continue to drive highly efficient campaigns.

The Google Analytics Multi-Channel Funnels with content-based segments and groupings, or Multi-Content Funnels as I like to call them, provides you with several new ways to leverage these amazing reports, boost your content marketing efforts, and better serve your current and potential consumers.

How have you used Multi-Channel Funnels in your content strategy?

(Note: Some screenshots were edited to remove site details.)

Mobile App Analytics Updates And Public Beta Launch

Thursday, 25 October 2012

With ever-expanding mobile application marketplaces (more than 600,000 apps on Google Play at the time of writing) and a shift in focus to mobile (more than 80 percent of marketers are planning to increase emphasis in mobile initiatives in 2013, according to recent research we conducted with ClickZ) measuring mobile is more important now than ever. With this, we are excited to be moving Google Analytics Mobile App Analytics (initially launched at I/O) out of closed and into open beta. We’ve listened to feedback from more than 5,000 mobile app developers during the closed beta, improved the product, and are now making it available to all developers and marketers. 

In addition to moving into public beta, there are some other exciting updates:

A New Sign-up Flow for all GA users
With the induction of mobile app analytics into the family of digital analytics at GA, we’ve introduced a new and improved sign-up flow that you will see whenever you setup a new entity on GA. In just 3 clicks, you’ll be able to set up your app analytics account, download the SDK, and be well on the way to tracking key metrics and finding valuable insights using our features.

New sign-up flow for Google Analytics
More powerful SDK for both Android and iOS, yet really easy to implement
The mobile app analytics solution is made possible with our new Android and iOS SDKs which have been rebuilt from scratch. They are lightweight, powerful, and super easy to implement. The majority of the mobile app reports are available out of the box after less than 5 minutes of work implementing our new SDK (check out our developer guides for more details).

New App Version Report
Find out about the long-tail of your old app versions. This report gives answers to questions such as:
  • How quickly are users migrating to the latest version of my app?
  • What’s the cannibalization effect among my multiple versions?
  • How many users would be affected if I deprecated an early version of my app?
App Versions report in Mobile App Analytics

A first-class customizable structure called “Custom Dimensions” 
For those of you who are savvy users of “Custom Variables,” consider this feature the next-generation Custom Variables: 
  • You can create your own dimensions by which to segment your hits in every standard or custom GA report.
  • Leverage your own business and customer data as custom dimension values to enable new possibilities for analysis and reporting.
  • Naming and scoping of Custom Dimensions can be configured through the administration UI - no retagging needed!
(Note: we are rolling out Custom Dimensions to everyone over the next few weeks)

Other improvements include: more accurate & up-to-date mobile device library, armv7s ( iOS6) support, support for social interaction tracking, a more accurate Google Play conversion report and more.

With this big step forward for Mobile App Analytics, we still have many more exciting features on the way and planned for the future that will add to the power and functionality of the platform. Look forward to improved integration with other Google properties like Google Play as well as brand-new reports that will provide a better understanding of your user acquisition, engagement, and outcome models.

We hope that our product will give app developers and advertisers a better picture of users’ interactions as well as the end-to-end value of your mobile app. And in the long run, make mobile apps more beautiful and engaging experience for all users.

Happy analyzing!

Posted by JiaJing Wang, Google Analytics Team

Building A Centralized Digital Marketing Platform With Google Analytics

Tuesday, 23 October 2012

The following is a guest post contributed by Google Analytics Certified Partner Daniel Waisberg.

Think about your business as a train. It has a locomotive and several wagons, each with its own function and importance (e.g., a restaurant wagon, a restroom wagon, and a luggage wagon). Now, let's say Google Analytics is the locomotive of the train, it is used to drive the business forward in a data-driven way. Together with it we find several important wagons: AdWords, AdSense, Webmaster Tools and others. How would you like those wagons to be tightly integrated?

This is the idea behind Google Analytics Integrations, an eBook that describes the official integrations available on Google Analytics. Currently it is possible to integrate the data from several Google tools into Google Analytics such as AdWords, AdSense, Webmaster Tools and YouTube. This enables marketers and analysts to import a wealth of information into Google Analytics, presenting a broad picture of their digital marketing efforts. 

In the eBook you will find a step-by-step guide to linking those tools as well as an explanation of what you can do with the resulting data. Let's suppose you are a new advertiser using both Google Analytics and AdWords, but the accounts are currently not linked. While you can use AdWords reports to analyze effectiveness of your campaigns, by linking the accounts you will be able to understand the bigger picture of website behavior in comparison to your AdWords campaigns. This information can help improving campaign performance by shedding light on which campaigns are failing as a result of suboptimal targeting, poorly designed landing pages, or poor ads; and which campaigns are succeeding. 

For example, let's look at the "Day Parts" report on Google Analytics (if your accounts are already linked here is a direct link to the report). 

The Day Parts report is for exploring hour-of-day and day-of-week dimensions. This report is useful for gaining insights into optimizing ad scheduling in campaign settings within AdWords.  

Click image for full-size

In the figure above, we see that this advertiser sees its traffic peak between 5 and-8 P.M. When adding a secondary dimension of per visit value, however, we see that the per visit value of visitors is highest during the morning hours of 6-9A.M: 

Click image for full-size
If this was your report, the practical next step you would take would be to adjust the ad scheduling settings in your campaigns to drive more traffic to the site during those morning hours, as that traffic is more valuable. Here is how to do it:
  1. Navigate to a specific campaign in the AdWords interface.
  2. Choose the Campaign Settings tab.
  3. Under Advanced Settings, click the plus (+) box next to Schedule: Start Date, End Date, Ad Scheduling.
  4. Next to Ad Scheduling, choose Edit.
  5. Change mode from Basic to Bid Adjustment.
  6. Under Time Period (next to day of week), click to reveal an overlay.
  7. Adjust the bid settings (by a percent multiplier to increase or decrease bids). There is a button to copy to other days to speed up making these changes.
  8. Click OK and then save.
If you are interesting only in the AdWords integration, check the Google Analytics For PPC eBook, which includes only information about integrating and analyzing AdWords using Google Analytics. This eBook had an important contribution from Yehoshua Coren

Daniel Waisberg is author of Google Analytics Integrations and Founder of Online Behavior, a Marketing Measurement and Optimization portal.

Real Time Analytics Supports Profiles

Wednesday, 17 October 2012

(Update: Please note that this rollout will be happening over the next couple of weeks so be patient with us as we ramp this feature up.)

 Last year we announced the beta launch of Real Time Analytics. We knew it would be an addictive feature but we were blown away seeing the growth and usage. In fact, we now have over 7 years worth of engagement with the feature every day!

One of the biggest requests we received was to show real time traffic per profile, which would also allow non-admin users to view real time reports. So today, we are really excited to announce that we are beginning to roll out Real Time support for your profiles! What this means is that the data you see in real time is profile specific and obeys the filtering you set up for that profile. And this means any user with access to a profile can view the associated real time reports. You can choose and move between profiles using the standard profile-picker feature available in the upper left hand corner.

When viewing your real time reports keep in mind these changes. If the numbers are lower than you are used to, check your filters to see what traffic is being excluded. And if you use real time for debugging, be sure to use an unfiltered report for that purpose.

Real Time has always been great for rapid testing and debugging of your tracking code and now with profile support you can do the same when creating profile filters. When you change the filters in your profile, you should see the effects in the real time reports within a couple of hours. We are working to make this even quicker going forward. 

Profile support is not restricted to web-pages but also supports App profiles. This means, you can now see mobile SDK traffic in real time!  This can be a powerful end to end debugging tool for your Google-Analytics SDK implementation. For example, one way we tested our Google Analytics mobile app is to install a new version on our phones and check that the mobile hits for that version are showing up in real time as we interact with the app. On the phone mobile hits are batched to conserve battery life so you may see delays. Typically batching will occur on the order of minutes.

While real time is great for debugging, where it shines is when something goes viral about your site. Sometimes, this spike is totally expected. For example, Reddit used this to monitor the Obama Q&A, and Khan academy used it to monitor the effect from CBS’s 60-minutes show. We’ve seen that many clients have similarly used real-time to check effects of offline TV and radio campaigns.

Another common source of viral traffic is social networks and we recently added an implicit traffic sources medium of “social”. This is the same grouping that is used in the Social Reports and allows you to segment your traffic by your top social networks. I can access this breakdown by clicking the “Social Referrals” link highlighted in the screenshot below.


This takes me to a report where my traffic is segmented by traffic source type = “Social” and I can see the networks that are driving traffic.


Additionally, while it is interesting to see which page/screen your visitors are currently on, it is sometimes useful to see which pages have gotten the most page views. You can now get this real time view data from the content report.  Check it out now by clicking the Pageviews tab I’ve highlighted below. Clicking on Active Visitors allows you to toggle back and forth.


And as a final shout out we always love the unintended use cases for real time such as extending bedtimes for the little ones.

We’ve been hard at work improving these reports for you and have many more exciting features coming down the pipeline so stay tuned!


Make better decisions in AdWords with your Google Analytics data

Wednesday, 3 October 2012

A version of the following post originally appeared on the Inside AdWords Blog.

Google Analytics users already know how useful it is to analyze advertising and web data together. Now we’re making it possible to use your Google Analytics data right in AdWords. After setting up AdWords to import your Google Analytics data, you’ll have access to key metrics like Bounce Rate, Pages Per Visit, and Average Visit Duration directly in the AdWords interface. With more performance data available right where you’re managing your campaigns, you can make better informed decisions and improve your AdWords ROI.

Using your Google Analytics data
With Google Analytics you can find insights that matter, including how visitors arrive at your website, how they use it, and how you can keep them coming back. Here are some ways you can take advantage of the new Google Analytics data available in AdWords to improve your results.
  • Attract more engaged users. If highly engaged users are an important goal, sort your ad groups to find the ones that deliver visitors who stay on your site the longest (“Average Visit Duration” or “Pages Per Visit”), and bid more for these.
  • Discover opportunities to convert more engaged visitors. You might find certain keywords or ads that have relatively low conversion rates, but great engagement metrics. You could lower your bids by a little and move on. Or you could see this as a great opportunity to convert clearly engaged visitors into buyers. By adjusting your offer, adding an incentive (like a coupon or discount code), or making your call to action more obvious and accessible, you might be able to improve your ROI and your conversion volume. To look for these types of opportunities, create a filter based on conversion rate and sort by Average Visit Duration, Pages per visit, or Bounce Rate.
  • Identify ads with badly matched landing pages or inaccurate targeting. Pages with both low conversion rates and low engagement metrics (low Average Visit Duration or High Bounce Rate) could indicate a poor landing page for a particular ad or keyword. It might also suggest inaccurate targeting. To identify and troubleshoot these problems, set up a filter for low conversion rate and low engagement rate and regularly monitor it. Since you’re using Google Analytics, you can easily set up A/B testing on the landing page using a Content Experiment.
Success in action
Casamundo, the biggest vacation rental listing service in Europe, has been an early tester of this new feature. They've used Google Analytics since 2008 and over the past 5 years they've grown and refined their AdWords campaigns to over 50 million active keywords across 10 languages. Their analysis shows that converting visitors research vacation rentals over an average of 7.4 visits, so understanding whether their ads and keywords can create strong engagement is vital to their business and how they optimize their AdWords campaigns. Seeing high bounce rates and low average time on site for a keyword means that the offer or destination page might not be a good match for that keyword.

Having easier access to Google Analytics data right in AdWords has helped Torge Kahl, Online Marketing Manager, at Casamundo make better decisions and make optimizations more quickly. According to Torge: 
“The combination of using both Google AdWords and Google Analytics has proved to be the perfect set of tools for us to achieve our goals, and we're very happy to see this combination get more integrated and powerful. Using Analytics data right within AdWords has let me better optimize our account and significantly improve the return on our AdWords investment."
More details
Please visit the AdWords Help Center for step-by-step directions on how to connect your Google Analytics profile data to your AdWords account and for more details. 

To exchange tips and ask questions of others, please visit the AdWords community. You can always contact AdWords support for help if you need it.

Posted by Dan Friedman, AdWords Product Manager

Digital marketing made (much) easier: Introducing Google Tag Manager

Monday, 1 October 2012

Over the past few years, we’ve seen massive improvements in digital marketing sophistication and capabilities. Today there’s a rich suite of tools allowing marketers to gain better insights, reach audiences in new ways, and develop improved marketing campaigns so users have better web experiences. Yet many modern marketing tools—like web analytics, conversion tracking, remarketing, and more—depend on adding "tags" to your website.

Website tags help enable today’s sophisticated digital marketing technologies
Tags are tiny bits of website code that can help provide useful insights, but they can also cause challenges. Too many tags can make sites slow and clunky; incorrectly applied tags can distort your measurement; and it can be time-consuming for the IT department or webmaster team to add new tags—leading to lost time, lost data, and lost conversions.

We’ve been hard at work to help take the pain out of tagging for everyone. That’s why today, we’re announcing our first release of Google Tag Manager. We’re launching globally in English, and the product will soon be available in many other languages.

Google Tag Manager is a free tool that consolidates your website tags with a single snippet of code and lets you manage everything from a web interface. You can add and update your own tags, with just a few clicks, whenever you want, without bugging the IT folks or rewriting site code. It gives marketers greater flexibility, and lets webmasters focus on other important tasks. Take a quick look at how easy it is to set up an account and manage your tags:


Google Tag Manager is built to handle your tagging needs, and it works with Google and non-Google website tags. We’ve packed in lots of great features, including:
  • Asynchronous tag loading—so your tags can fire faster without getting in each other's way, and without slowing down the user-visible part of the page
  • Easy-to-use tag templates, so marketers can quickly add tags with our web interface, as well as support for custom tags
  • Error-prevention tools like Preview mode (so you can see proposed changes before implementing them), the Debug Console, and Version History to ensure that new tags won’t break your site
  • User permissions and multi-account functionality to make it easy for large teams and agencies and clients to work together with appropriate levels of access
  • Plus we have exciting plans to add great new features over the next several months
We’re also happy to announce our tag vendor program: If your company provides tag technology and you’d like Google Tag Manager to include a template for your tag, please contact us here to become a tag vendor.

Dozens of companies have already begun using Google Tag Manager and have seen great results. Ameet Arurkar, Director of Search Engine Marketing at QuinStreet, reports:
“Google Tag Manager took one big chunk of time out of the tagging process. What took 2 weeks now takes less than a day—sometimes just hours. We, the campaign managers, now make the call on which tags to use, and we can implement the tags ourselves.”

“Google Tag Manager just makes business sense. Why would we want to manually add hundreds of tags for our pages?”


Setting up Google Tag Manager is quick and easy—you create an account, add one snippet of code to your site, then start managing tags. If you want more help, contact a Google Certified Partner—they’ve been carefully vetted and meet rigorous qualification standards.

Get started today at www.google.com/tagmanager.

Posted by Laura Holmes, Product Manager, Google Tag Manager

 

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