Category Archives: Google Analytics Blog

The latest news, tips and resources straight from the Google Analytics team

Agilent Technologies Democratizes Data With Smooth Migration to the Google Analytics 360 Suite

Agilent Technologies provides laboratories worldwide with instruments, services, consumables, applications, and expertise. They are experiencing a shift as more of their buyers are turning to the web for information on healthcare equipment and services.

Image: AdvanceBio Columns Improve Laboratory Workflows (source) 
As part of a recent digital transformation to meet their audience’s needs, they sought to expand the analytics capabilities of the company. They worked with E-Nor, a Google Analytics 360 Services and Sales Partner, to develop a measurement strategy and support an analytics technology migration to the Google Analytics 360 Suite.
Below is a quick summary of how Agilent is democratizing their data with the Google Analytics 360 Suite, to learn more read the full case study.
The key challenge was to provide a solution with minimal technical overhead that encouraged analytics adoption within the organization. Agilent also needed a solution that would integrate well with data from other sources. 

Together, Agilent and E-Nor developed a measurement strategy incorporating business objectives, strategic initiatives, and key performance indicators. They then outlined a complete migration plan to meet many requirements, including implementation, dashboarding, data governance, and more.

Once the plan was in place, it was put to motion! E-Nor supported Agilent’s teams through a successful analytics solution migration. As a result, data from Analytics 360 is now used to help make both strategic and niche decisions throughout the organization. BigQuery and Data Studio expand capabilities by providing easy access to advanced analysis for key stakeholders.
“Google Analytics 360 has enabled an analytics culture where all digital teams have access to data in real time, and insights can quickly become business action.” Karen Brondum, leader of the Digital Analytics COE at Agilent
Thanks to Agilent and E-Nor’s collaborative efforts, the company has experienced a 400% growth in analytics users. They were also able to lower the cost of ownership for their analytics program, with less effort from all teams required to get to business insights. Learn more about how they achieved those results in the full case study.


Posted by Tara Dunn (E-Nor) and Daniel Waisberg (Google)

Data Studio now globally available

Last month we announced we removed the five report limit in Data Studio, allowing you to create and share as many reports as needed — all for free. Today we are opening up access to 180+ countries, enabling even more businesses to easily connect to data and create beautiful, informative reports that are easy to read, easy to share, and fully customizable.

New, powerful features

In addition to making Data Studio accessible in more countries, we’re also adding more powerful features to help you better analyze and report on your data, including:

Filters

You can now filter your data in more ways, and it's easier to reuse filters on multiple charts. This new functionality includes:
  1. Reuse – Create a filter once and then use it on as many different components on the report as you want. No more recreating identical filters!
  2. Compound filtering – Combine multiple AND and OR filter conditions together into one reusable filter.
  3. Metric filters – Filter metric values that are too large, too small, or within a specified range.
Learn more in the Filter Help Center article.

New Filters UI

Google Analytics segments

You can now apply Google Analytics segments to your charts!

A Google Analytics segment represents a subset of your data, for example, Returning Users. You can now see all your Google Analytics segments in Data Studio and apply them to any chart. And, if you update the definition of your segments in Google Analytics, those changes will apply to the segments in Data Studio.

Learn more in the Segments Help Center article.

Data Studio allows you to link to your Google Analytics segments.

More powerful data connectors

We’ve improved several of our most popular data connectors, YouTube, DoubleClick Campaign Manager, and AdWords, by adding many new dimensions and metrics. Some highlights include adding YouTube video title, DoubleClick Campaign Manager revenue and cross-environment conversions broken out by app, AdWords campaign ID, and keyword quality score. For a full list of all the new fields, please see the Data Studio release notes.

Google Cloud Platform integrations
We’re also announcing tighter integration with the Google Cloud Platform to enable faster data reporting at scale and more powerful functionality.

File upload

Not all your data resides within SQL or Google databases. Data Studio now has the ability to upload up to 2GB of CSV data for free enabling you to bring in data from anywhere. Have more data? Upload directly into BigQuery using your BigQuery account to take advantage of the scalable processing power of Google's infrastructure.

Tighter BigQuery integration

Not only can you upload data directly into BigQuery, Data Studio now supports Standard SQL in BigQuery for custom queries and partitioned tables.

Learn more about these new features
Not sure where to start? You can browse our gallery of Data Studio templates. Need more information on these new features? Visit the Help Center articles for more details:


As always, your feedback and questions are welcome in the Data Studio community forum.

Happy reporting!
Posted by Dave Oleson, Data Studio Product Manager

The life of a help center article

Google has dozens of help centers both for external and internal products. Our Technical Writers work hard to keep up with new features, constantly adding new articles, reviewing user feedback and usage metrics to improve existing content. They work closely with Product Managers, Engineers, Marketing and other parts of the company to make sure their content is accurate and in line with the messages Google wants to convey.

The Google Analytics 360 Suite publishes 8 Help Centers, including Analytics, Tag Manager, Optimize, Attribution and others. With so much knowledge being shared, we thought it would be interesting to our users to understand how we produce this content and where our ideas come from. So we decided to talk to one of our Technical Writers, Rick Elliott, who is responsible for content published in the Data Studio Help Center.


Basically, all help content comes from asking the question: what does the user need? We hope the product is intuitive and easy to use so that extra help is not required, but there are always concepts or flows that require more explanation. So that's the start of a new Help Center article. Depending on the situation, a new article usually stems from 1 of 3 sources:
  1. We launch a new feature and it requires documentation.
  2. We get questions from users on the help forum that can be answered by a new article.
  3. A writer gets a bee in their bonnet and decides we need to document something more fully.
    After that, it's a process of interviewing the subject matter experts and trying it through lots of sample reports to make sure the flows are right. Once the first draft is done, it is sent out for review and comments, but there may be another round of review and feedback before it gets published. Another big step in the help center content flow is localization: we usually get the translated content out a week or two after publishing the English version. 

    Watch the video to learn more about how Rick developed massive Help sections such as the  chart references and the "warm welcome report".

    Posted by Daniel Waisberg and Rick Elliott

    Real-time just got real: Google Analytics 360 offers fresher insight

    You’ve just launched a website or feature. Your toe is already tapping. Wait, wait, wait — you can hardly wait one hour to see exactly how it’s performing. Sound familiar? If you’ve been there, we have exciting news for you.

    Google Analytics 360 can now provide updated insights as quickly as every 10 minutes. We’re proud to give our customers the fastest access to the freshest first party data Google Analytics has ever offered.

    What did you just say?!
    If you need to know how your sites, microsites, or digital engagements are doing right now, we’ve got you covered. Most first-party data in Analytics 360 can now be collected, processed, and available — via our UI, API, and BigQuery integration (coming soon) — in as fast as 10 minutes. This means you can move faster to:
    • Fix things when they’re broken
    • Detect trends and react when things are popular
    • Understand and take action on the impact of cultural events or social memes
    To see how fresh the data is in your report at any time, just look for this icon in the upper right:
    When you see this icon, it means you’re looking at today’s data and the report is supported and super fresh. Hover over the icon to see how fresh the data is!

    This new level of freshness is only available to Analytics 360 users. To learn more about which reports, views, and properties support fresher data, and the factors affecting data freshness, check out our help center.

    Some site owners just can’t wait
    Brands and sites in the business of capitalizing on momentary consumer attention are excited about fresher insights. Take the case of publishers and retailers as an example.

    Publishers strive to put the richest, most interesting content in front of users at any given point in time. The trick is understanding what’s rich and interesting right now — and that’s a constantly moving target.

    Publishers have long referenced our real-time Google Analytics reports to make decisions, but sometimes they’re looking for deeper insight than what is provided in those reports. Fresher insights across additional Google Analytics reports help our publishers make even more informed content decisions, paving the way to better user acquisition, user engagement, and a stronger relationship between content consumer and publisher brand.

    Online retailers are in the same boat. When celebrities wear a product or mention a brand on social media, product interest may spike. Retailers may have just minutes to capitalize on purchase intent before it wanes.

    When a product’s popularity is on the rise, retailers can react by upping its prominence to capture interest, running focused promotions or recommending related products to expand consideration. With fresh insights available as soon as every 10 minutes, retailers move faster and turn trending interest into sales.

    Speed is good, but safety comes first
    As you know, Google Analytics has the ability to pull in data from other sources like AdWords and DoubleClick. We refer to these as “integration sources” and these sources operate with additional requirements, like fraud detection, that mean that the data in these reports are exempt from our enhanced freshness capabilities.

    For example, any report with Ads data, including a dimension widened by an Ads integration, will continue to be made available within hours. For further details on which reports are supported or not supported, please read the help center article here.

    Posted by Breen Baker, on behalf of the Google Analytics team

    Audience Data Mining Case Study: PBS & LunaMetrics

    Google Analytics 360 can be used to collect and process a wealth of data, and there are many opportunities to make use of it. But some companies want to take advantage of the powerful data mining tools offered by the Google Cloud Platform: enter the Google Analytics 360 export to BigQuery. Today we're publishing a new case study developed by LunaMetrics and PBS, showing how Google Analytics 360 and the Google Cloud Platform were used  to classify audiences to improve user experience design, personalization, and targeting for marketing and messaging. 

    PBS television programming reaches millions of people, and its website PBS.org is an online content hub that supports that television experience and provides online video streaming content. PBS.org, like many websites, strives to understand its users and their needs for features and content by developing personas and audience segmentation. Personas often begin with anecdotal knowledge of customers or users and can be informed by many kinds of data, including interviews and other qualitative ethnographic data as well as surveys and other quantitative market research.

    PBS was able to develop an additional approach with Google Analytics 360 and its BigQuery export: employing a data-driven method to classify audiences. PBS already had a robust Google Analytics implementation, with the default information enhanced by Event Tracking for on-page interactions and a wealth of internal information surfaced and stored in Custom Dimensions.
    A data mining algorithm classified clusters of similar users based on a number of behavioral factors.
    PBS partnered with LunaMetrics on a Data Science Solutions project to distill large and complex datasets like these into concrete, usable results. LunaMetrics applied data mining techniques to find patterns of audiences based on their website behavior. Using BigQuery along with Google Cloud Platform products such as Cloud Datalab and Cloud Storage, they were able to extract answers from over 330 million website sessions.

    The analysis identified six distinct groups of users, for instance those who primarily focus on either particular kinds of content (such as news or information for parents) or features (with different preferences for watching video online or on TV-connected devices). PBS was able to use these findings to reinforce and refine their existing personas, now based on behavioral data.  Moving forward, these personas can inform the creation of new audiences to be used in remarketing, advanced reporting and content experimentation.

    For more information, check out the full case study. For the technical details, check out Audience Modeling with Analytics 360 and Google Cloud Platform on the LunaMetrics blog.

    Posted by Jonathan Weber (Lunametrics) and Daniel Waisberg (Google)

    ‘All Killer, No Filler’: The Next Web finds the right message with Google Optimize 360

    In a world where consumer behavior can shift on a dime, marketers constantly ask themselves: How can we be more useful to our customers? With all the data businesses collect, the challenge becomes tuning out the noise to focus on insights your team can act on.

    Today’s most successful businesses have turned to a new approach: building a culture of growth and optimization. This is where everyone in an organization is using data to test and learn as a means to improve the customer experience every day.

    The Next Web, a technology-media company and online publisher, has embraced this testing culture and turned to Google Optimize 360 to help them find just the right message to drive readers to their conference website.

    The Next Web Case Study 


    The Next Web’s conferences bring tech leaders, entrepreneurs, and marketers together to innovate, share, and look ahead. The first TNW conference was created in 2006 by Patrick de Laive and Boris Veldhuijzen van Zanten, when they couldn’t find the kind of event they needed to showcase their own startup.

    That first event drew a respectable 280 attendees, but the founders knew they needed a better way to promote future TNW conferences. That’s when they launched thenextweb.com, a tech news and culture website that today attracts 8 million users a month. The Next Web’s two annual conferences in New York City and Amsterdam now draw over 20,000 attendees.

    The Next Web’s marketing team uses promotional messages within articles on thenextweb.com to drive potential attendees to the conference website and sell tickets. To find out which combination of messages works best, they used Google Optimize 360, an integrated part of the Google Analytics 360 Suite.


    "We want more people to read content on thenextweb.com as a first step," says Martijn Scheijbeler, who leads the marketing team's efforts. "If we can convince them to become a loyal user, we can try to interest them in different opportunities. In the end, we’d like them to join us at one of our events to experience what The Next Web is really about." 

    With one of its conferences coming up, The Next Web's marketing team wanted to compare different headlines and descriptions to see which combination would drive more readers to its conference page. Using Optimize 360, The Next Web team ran a multivariate experiment to discover the combinations that worked best.


    For The Next Web, the results were clear: The "All Killer, No Filler" headline with the "This one's different, trust us" description was the winner. During the experiment it performed 26.5% better than the original headline and description, with a 100% probability to beat baseline.

    Today The Next Web team tests and optimizes its conference messages day by day. Better messaging means more traffic to The Next Web conference site, and that means more attendees. It also gives the marketing team extra wins like higher awareness and more newsletter signups.

    “Optimize 360 and Analytics 360 make testing easy for us,” Martijn says. “They give us much better insights into how many clicks we’re getting for each message. We’re reaching more people who want to come to our conferences, and those better results are going right to our bottom line.”


    For more, read the full case study with The Next Web.


    Posted by Tiffany Siu, Product Marketing Manager, Optimize 360

    A Love Story for the Ages: Marketing Commits to Measurement

    Marketing and Measurement have been flirting for a long time now. But if these two finally get past the awkward stage and form a lasting bond, beautiful things can happen.

    Working together, Marketing and Measurement can uncover insights that will improve your marketing, your customer experiences, and ultimately your business. To reach that next relationship level, Marketing can’t just casually date Measurement when it’s convenient. They need a real commitment.


    The secret to a strong relationship
    “For growth-driven marketers, measurement isn't an afterthought. It's one of the key reasons they’re succeeding and growing in an ever-changing, mobile-first world,” said Matt Lawson, Google's Director of Performance Ads Marketing.

    Leading marketers are 75% more likely than the mainstream to have moved to a more holistic model of measurement in the last two years.1

    When Marketing and Measurement “put a ring on it,” the future looks bright. Leading marketers are 75% more likely than the mainstream to have moved to a more holistic model of measurement in the last two years, according to a recent study from Econsultancy and Google. What’s more, the same study shows leading marketers were more than twice as likely to have significantly exceeded their top business goal in 2015.2

    Don’t expect ‘happily ever after’
    Engagement isn't where the story ends, of course.

    Along the way, Marketing and Measurement may experience setbacks or failures as they test and learn from each other. In a recent survey of marketing decision makers with analytics initiatives, 61% of respondents said they struggled to access or integrate the data they needed last year.3

    As with any relationship, Marketing and Measurement will need to “work on it.” And as this love story evolves, they will need to let go of traditional measurement practices and embrace a growth mindset that rethinks and remakes marketing measurement for the future.

    If Marketing and Measurement are ready for a serious commitment at your company, here are three keys to a successful partnership:

    1. Collaborate to identify and measure what really matters to your business
    2. Communicate key insights uncovered from your data to help support decision making
    3. Take action to ensure those insights lead to better customer experiences


    Download “Driving growth with marketing measurement in a mobile world,” a new report from Econsultancy and Google, for more best practices for marketing leaders.

    1,2 Econsultancy and Google, Analytics and Measurement Survey, 2016, Base: n=500 marketing and measurement executives at North American companies with over $250MM in revenues 
    3 Google Surveys, U.S., "2016–2017 Marketing Analytics Challenges and Goals," Base: 203, marketing executives who have analytics or data-driven initiatives, Dec. 2016. 

    Posted by Karen Budell, Content Marketing Manager, Google Analytics 360 Suite

    Data Studio: Enhanced AdWords MCC Support

    An AdWords manager account (MCC) is a powerful tool for handling multiple AdWords accounts. Manager accounts allow users to link several accounts so they can be viewed in a single location, and are frequently used by third-party advertisers such as agencies and marketing professionals.

    Today the Data Studio team is releasing an enhanced AdWords connector, giving users the ability to select MCC sub-accounts and set up reports for accounts containing multiple sub-account currencies.

    Click image for full-size version
    New capabilities

    There are two major enhancements to the AdWords connector:

    1. Selecting sub-accounts: prior to this release it was only possible to connect to an entire MCC account as the data source for a Data Studio report. This enhancement allows users to define a data source by selecting up to 75 individual sub-accounts within an MCC account.

    2. Filtering on currencies: one common challenge with MCC accounts occurs when sub-accounts are set to different currencies. While metrics such as impressions and clicks can be aggregated correctly across these sub-accounts, currency fields like Cost and Average CPC cannot. The enhanced AdWords connector allows MCC account holders to filter sub-accounts by currency to avoid this problem, and removes currency fields from the connector if multiple currencies are present.

    Connecting to AdWords MCC accounts
    To connect to MCC accounts, create a new Data Studio data source and select the AdWords connector. If you have access to an MCC account, a “MANAGER ACCOUNTS” option will appear. The account holder can then select sub-accounts they are interested in, or use the pull-down menu in the upper-right corner to filter for sub-account currencies.

    Note that existing Data Studio connections to MCC accounts must be edited and reconnected or recreated from scratch to take advantage of the new enhancements.

    Your feedback and questions is welcomed in the Data Studio community forums. 

    Happy Reporting!

    Posted by Alon Gotesman, Google Data Studio team

    What does a good website test look like? The essential elements of testing

    "Test! Test! Test!" We've all heard this advice for building a better website. Testing is the heart of creating a culture of growth ― a culture where everyone on your team is ready to gather and act on data to make the customer experience better day by day.

    But how do you run a good test? Is it just a matter of finding something you're not sure about and switching it around, like changing a blue "Buy now" button for a red one? It depends: Did you decide to test that button based on analytics, or was it a wild guess?

    Assuming the former, a good test also means that even if it fails, you’ve still learned something. A bad test may make your website performance worse than before, but it’s even worse if you don’t take those learnings into account in the future.

    The key to running good tests is to establish a testing framework that fits your company.

    Join us for a live webinar on Thursday, March 9, as Krista Seiden, Google Analytics Advocate, and Jesse Nichols, Head of Growth at Nest, share a six-step framework for testing and building better websites.

    Frameworks vary from business to business, but most include three key ideas:

    Start with an insight and a hypothesis.
    A random "I wonder what would happen if …" is not a great start for a successful test. A better way to start is by reviewing your data. Look for things that stand out: things that are working unusually well or unusually badly.

    Once you have an insight in hand, develop a hypothesis about it: Why is that element performing so well (or so badly)? What is the experience of users as they encounter it? If it's good, how might you replicate it elsewhere? If it's bad, how might you improve it? This hypothesis is the starting point of your test.

    For example, if you notice that your mobile conversion rate was less than on desktop, you might run tests to help you improve the mobile shopping or checkout experience. The team at The Motley Fool found that email campaigns were successfully driving visitors to the newsletter order page, but they weren’t seeing the conversions. That led them to experiment on how to streamline the user experience.

    Come up with a lot of small ideas.
    Think about all the ways you could test your hypothesis. Be small-c creative: You don't have to re-invent the call-to-action button, for instance, but you should be willing to test some new ideas that are bold or unusual. Switching your call-to-action text from "Sign up now" to "Sign up today" may be worth testing, but experimenting with "Give us a try" may give you a broader perspective.

    When in doubt, keep it simple. It's better to start with lots of small incremental tests, not a few massive changes. You'll be surprised how much difference one small tweak can make. (Get inspiration for your experiments here.)

    Go for simple and powerful.
    You can't test every idea at once. So start with the hypotheses that will be easy to test and make the biggest potential impact. It may take less time and fewer resources to start by testing one CTA button to show incremental improvement in conversion rates. Or, you may consider taking more time to test a new page design.

    It may help to think in terms of a speed-versus-impact grid like this. You don't want quiet turtles; the items you're looking for are those potential noisy rabbits.


    The best place to begin a rabbit hunt is close to the end of your user flow. "Start testing near the conversion point if you can," says Jesse Nichols, Head of Growth at Nest. “The further you go from the conversion point, the harder it gets to have a test that really rocks — where the ripple effect can carry all the way through to impact the conversion rate,” says Jesse.

    Stick with it
    A final key: Test in a regular and repeatable way. Establish an approach and use it every time, so you can make apples-to-apples comparisons of results and learn as you go.

    A clear and sturdy framework like this will go a long way toward making your team comfortable with testing — and keeping them on the right track as they do.

    Download the eBook How to Build a Culture of Growth to learn more about best practices for testing and optimization.

    Posted by Tiffany Siu, Product Marketing Manager, Google Optimize 360

    Data Studio: Search Console Connector

    Google Search Console is a free service offered by Google that helps webmasters monitor and maintain their site's presence in Google Search results. Search Console helps users understand how Google views their site and allows them to optimize their performance in search results.

    Search Console’s Search Analytics feature shows webmasters how often their site appears in Google search results for various keywords. This data is extremely powerful but currently lives in Search Console’s Search Analytics Report and is hard to combine with other data sources.

    Today we are announcing a new Data Studio connector for Search Console. With this launch users can pull their data into Data Studio to build reports that include impressions, clicks, and average position broken out by keyword, date, country, and device.


    Search Console users can now build Data Studio reports to understand how their search traffic changes over time, where traffic is coming from, and what search queries are most likely to drive traffic to their sites. Users can also filter reports for mobile traffic to improve mobile targeting, and to analyze clickthrough rates for various organic search terms.

    As always, Data Studio report creators can add components from other data sources into a single report. With this new connector, users can use the Search Console and AdWords connectors to compare performance across paid and organic search, or add Google Analytics data to analyze site-side performance.

    Note that Search Console metrics can be aggregated by either site or by page (URL). This is configured in the Data Source creation flow, where users can select either “Site Impression” or “URL Impression”. To learn more about the distinction between these two methods please see the Search Analytics Report Help Center article.

    Want to learn more? Looking for a new connector in Data Studio?

    To learn more about the new Search Console connector, please visit our Help Center or post your questions in the Data Studio community forums.

    Is there a specific data service you wish to be able to access and visualize through Data Studio? We welcome your feedback via the connector feedback form — we read all responses and use them to prioritize new connectors.

    Happy reporting!

    Posted by The Data Studio team