Google Data

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.

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

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

^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

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

“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.

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

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

We have been making improvements to the admin section of Google Analytics 360 Suite to fit the needs of modern enterprises. Recently, we made account recovery easier. Today, we’re pleased to announce another feature we’ve heard users ask for: User policies for your organization. User policies are a user management feature to help Google Analytics 360 Suite organization administrators to better control who has access to their corporate data.

How user policies work
An organization’s user administrator can create a user policy specifying what users are allowed or disallowed to do within their organization’s Google Analytics accounts. For example:

• A domain may be entered to allow any users with email addresses on that domain 
• A single user email may be entered to explicitly allow that user 
• A single user email may be entered to explicitly disallow that user 

Click image for full-sized version

Auditing policy violators 
Any user who violates the policy will be highlighted on the Suite Admin User’s report. We check both primary and secondary Google User Account email addresses when considering if a user passes a policy; if any email on the Google User Account account passes a policy rule, that user is considered to be allowed.

Policy Auditing – note the red (!) icons next to policy violators

Adding Users that Violate Policy
At this time, we do not block the addition of policy violating users to suite products. Product account administrators may still add a user that violates the user policy, and that user will appear in the Audit report seen above with a red (!) icon. At a future time, we will allow policy administrators to choose to block violating users from being added.

Posted by David Wieser, Google Analytics team

Today, Google’s mission to organize the world’s information and make it universally accessible and useful is even more relevant and broad reaching. And last year’s launch of both free and enterprise versions of Data Studio, a new dashboarding and reporting tool, is a testament to our commitment to this vision. Over the past 9 months we’ve received positive feedback and seen tremendous demand for the product. And we’ve continued to enhance the product making it even easier to use via templates and adding many new data connectors.

To enable more businesses to get full value from Data Studio we are making an important change — we are removing the 5 report limit in Data Studio. You now create and share as many reports as you need — all for free.

This change combined with a very exciting roadmap for 2017 are designed to accelerate our goal to help you fully leverage all your data across your organization and to ultimately make better decisions.

Thank you for using Google Data Studio and as always, please share your thoughts and feedback as to how we can improve the product. We’re excited by what the future holds! 

Happy Analyzing.

Posted By Nick Mihailovski, Product Manager, Google Data Studio

It’s often said that marketing is both an art and a science. The science side is increasingly in the spotlight as companies use data to optimize the customer experience at every touchpoint. But, ensuring that insights surfaced from that data lead to action requires the arts of communication and collaboration.

Highly data-driven organizations are three times more likely than others to report significant improvement in decision-making.¹ Yet, 62% of executives still rely more on experience than data to make their decisions.² When the stakes are high, decision-makers need information they can trust, easily consume, and understand.

Below are three ways marketing organizations can take action on their data to better support decisions:

1. Organize
Whether you have trouble connecting teams or data sources, silos can prevent your marketing organization from reaching current and potential customers. Data silos prevent you from gaining a holistic view of the customer journey. Organizational silos slow down the flow of information and ideas. What’s more, organizational silos are the number one barrier to improving customer experience.³

Outline a data strategy to organize and integrate information sources so you have the complete picture to your customers’ journeys. Collaboration and communication between departments is also key. Better yet, make sure marketers and analysts all have access to the same data sets and technology.

2. Visualize
Good data storytelling means making data easy to process. By taking the time to visualize your data, you’ll be able to tell a compelling story at a glance.

The goal of a revenue chart, heat map, or bar graph should be to simplify a complicated idea or communicate a body of information in seconds. Tools can help make data quickly actionable by taking multiple data sources and turning them into interactive reports and dashboards. Focus on reducing misinterpretations of your data and making it easy for decision makers to act.

3. Share
If the data can’t be understood, its insights cannot be acted on. But just as important, if the data and ideas are not shared with the right people at the right time, decision makers can’t fully leverage the power of marketing data.

“Real-time data is critically important. Otherwise, business leaders may be making decisions off data that is no longer relevant. The business landscape changes so quickly, and stale data may inadvertently lead to the wrong decision,” says Suzanne Mumford, head of marketing for the Google Analytics 360 Suite.

Look for solutions that offer data visualization and built-in collaboration capabilities so you can start practicing all three steps right away:

• Organize workflow and integrate data from multiple sources 
• Visualize information by creating easy-to-digest, interactive reports 
• Share insights by setting up dashboards with real-time collaboration 

The companies that shine at optimizing the customer experience go beyond analytics and measurement. The whole organization collaborates in order to connect the data dots and communicate the meaning and impact of insights surfaced. Leading marketing organizations build a culture of growth — one that uses data, testing, and optimization to improve the customer experience every day — and share insights in ways that everyone across the organization can understand and act on. 

Download “Measuring Marketing Insights,” a collection of Harvard Business Review articles, to learn more about how to turn data into action.

A version of this article first appeared as sponsor content on HBR.org in August 2016.

¹ PwC’s Global Data and Analytics Survey, Big Decisions™, Base: 1,135 senior executives, Global, May 2016 
² PwC’s Global Data and Analytics Survey, Big Decisions™, Base: 2,106 senior executives, Global, May 2016 
³ Harvard Business Review Analytic Services, “Marketing in the Driver’s Seat: Using Analytics to Create Customer Value,” 2015.

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

A frequent feature request we receive is to make it easier to recover lost or orphaned accounts. Loss of administrative access can occur, for example, when an account administrator leaves the company without first assigning another administrator. The account continues to collect data, and users with non-administrative access are still able to log in and use the account per their assigned permissions, but the account remains in administrative limbo.

Of course, we hope brands have the right onboarding and offboarding processes in place to ensure this doesn’t occur, but we understand this isn’t always possible. If you lose administrative access to an Analytics account that is linked to an organization, you can have the organization Owner restore that access. Administrative access to Analytics consists of having Manage Users and Edit permission.

If you need to regain administrative access to your Analytics account, contact your organization Owner.

If you are an organization Owner who needs to restore access to an Analytics account:

1. Visit http://360suite.google.com 
2. Open Products > Analytics.
3. Select the account to which you want to restore access.
4. In the right pane, under User Management, click ACCESS PRODUCT. 

The User Management page for that Analytics account opens.

5. Under Add permissions for, enter the email address for the Google account you want to give administrative access.
6. Select the Manage Users and Edit permissions.
7. Optionally, remove any stale administrators from the account.

Please view our Help Center document on this feature for more information.

This is one of many user and account management improvements we’ve launched; we’re working on more, so stay tuned for future updates.

Posted by Matt Matyas, Google Analytics team

Over the past months, we’ve been hard at work adding and enhancing all of our connectors. After our recent launch of the MySQL connector, many users asked for a PostgreSQL connector.

So today we’ve launched a new PostgreSQL connector in Google Data Studio!

Visualizing your data hasn’t been easier.

PostgreSQL data visualized in Data Studio

To get started, create a new Report, add a new Data Source, and select the PostgreSQL Connector. Then use the wizard to configure access to your PostgreSQL database. Create a new Report, add a new Data Source, and select the PostgreSQL Connector. Then use the wizard to configure access to your PostgreSQL database.

The new connector in our ever expanding list

Once connected, you will see a list of all your columns and you can create custom aggregations and calculations over your data directly in Data Studio!

Calculations on top of fields accessed from postgreSQL

We’re excited to learn about what you do with this connector. Visit the Data Studio PostgreSQL connector help center article, for more details on how this connector works.

Finally, we prioritized this connector directly from your feedback. If there are any additional connectors you would like added, please fill out the Data Studio Data Integrations Survey.

Posted By Anand Shah, Product Manager, on behalf of the Google Data Studio team

Looking to sharpen your Google Analytics skills as you kick off 2017? A new full-color book is now available for analysts, marketers, front-end developers, managers, and anyone who seeks to strengthen their Google Analytics skills.

“In Google Analytics Breakthrough: From Zero to Business Impact, we strive to provide a step-by-step resource to help readers build a solid foundation for analytics competence. It starts at strategy and core concepts, extends to advanced reporting and integration techniques, and covers all the nuts, bolts, tricks, gaps, and pitfalls in between,” says coauthor Feras Alhlou, Co-founder and Principal Consultant of E-Nor. “The book is structured to offer a succinct overview of each topic and allow more detailed exploration as the reader chooses.”

 The book includes contributions straight from the Google team.  Avinash Kaushik’s foreword starts things off with a constructive mindset, and Paul Muret’s cover piece takes a unique perspective on the evolution of Google Analytics from the days of Urchin.  Krista Seiden lends her top reporting tips, and Dan Stone shares insights on remarketing. Industry experts such as Jim Sterne, Brian Clifton, and Simo Ahava also offer key takeaways.

At nearly 600 pages, the book is quite comprehensive, but the authors outline a few main themes below.

1- Define and Measure Success 
It still bears repeating: identify your KPIs as part of your measurement strategy. Map your marketing and development initiatives to the KPIs and center your analytics around your success metrics and specific improvement targets. You’ll be much more likely to drive, detect, and repeat your wins, both big and small, if you always know what you’re aiming for.

2- Keep Your Focus on User Journey 
This has multiple meanings. From a Google Analytics reporting standpoint, take advantage of the reports and features – such as Multi-Channel Funnel reports, custom segments, custom funnels in Analytics 360, and calculated metrics – that go beyond session scope and begin to approach a more complete picture of user journey.

Even more fundamentally, remember to always relate your data to user experience.  Contributor Meta Brown offers specific advice on crafting a hero story to make your analytics data more accessible and impactful for all stakeholders.

 3- Take Full Advantage of Google Tag Manager 
“When we were first outlining the book, we briefly considered dual-track native and Google Tag Manager examples ,” recollects coauthor Eric Fettman, Senior Consultant and Analytics Coach at E-Nor. “Shiraz steered us to a basically GTM-only approach, which  streamlined the implementation chapters and really highlighted GTM’s flexibility and power.”

In addition to in-depth discussions about GTM’s triggers, variables, and data layer, the book examines the relatively new and perhaps underutilized Environments feature.  While the publication schedule didn’t allow direct inclusion of GTM Workspaces, the supplemental online materials offer a detailed Workspaces walkthrough. 

As an illustration of Google Tag Manager’s flexibility, this Lookup Table variable will allow a single Google Analytics tag to populate into different properties based on hostname.

4- Help Google Analytics Tell Stories in Your Own Language 
From both an implementation and reporting standpoint, Google Analytics provides a range of capabilities for customizing your data set and optimizing the reporting experience so your data speaks clearly and relevantly.  Custom dimensions and data import for your content, products, and back-end user classifications will let you build more meaningful and actionable narratives. Custom channels – for paid social traffic, as an example – will certainly yield much greater insights than default channel reporting. Alternate report displays and custom reports allow you to combine and isolate the metrics that are most important for the analysis at hand.

And don’t fail to take full advantage of basic features such as secondary dimensions. The Landing Pages report is good by default; Landing Pages with Source/Medium applied as a secondary dimension might reveal a whole new secret.

5- Master the Basics for Advanced Benefits in GA 360, BigQuery & Integration 
The fundamental Google Analytics data collection and processing tactics remain as important in 2017 as ever.  You still need to implement event tracking, with a meaningful naming convention, to really understand user interaction. You must maintain consistency in campaign tagging for clarity in your Acquisition reports. In many cases, you still must apply view settings and/or filters to insure data quality in all of your Google Analytics reports.

The benefits of clean data, however, extend beyond the Google Analytics user interface.  If you’re exporting to BigQuery (integration with BigQuery is enabled for Analytics 360 organizations) to analyze conversions over multiple sessions by different traffic channels, the campaign tagging and channel grouping work that you have already performed for your GA reporting will again prove critical.  If you’re also pulling your CRM data into BigQuery to integrate with GA data and measure the effect of specific interactions – such as downloads, video views, or live chats – on customer lifetime value, you’ll be doubly glad that you took the time to properly implement your Google Analytics event tracking from the start.

Going forward, as we begin to navigate through dynamic visualizations in Google Data Studio and look towards advanced solutions such as Attribution 360 and Audience 360, the competitive advantage of good, consolidated Google Analytics data, as a dataset for complementary tools and environments, will only magnify.

“We dedicate the book to our contributors, to our clients, to the team at E-Nor, and especially to our coauthor and E-Nor cofounder Shiraz Asif, who passed away in March 2016 and will always be keenly missed.” For more about Google Analytics Breakthrough: From Zero to Business Impact, visit www.gabreakthrough.com.

Posted by Feras Alhlou,  Principal Consultant and Co-founder of E-Nor, Inc., Google Analytics Partner

Making important business decisions is often a slow process, regardless of industry or company size. In a world where innovation is increasingly important, speed is a necessity. But how does an organization streamline its decision-making process? For many companies, the answer is data. In fact, highly data-driven organizations are three times more likely than others to report significant improvement in decision-making, according to PwC research.¹

When looking for meaningful insights to drive innovation and growth, market research is often a go-to data source. The problem many companies face is that market research can feel like a roadblock because it can take months to get the data.

At Lenovo, the leading PC manufacturer worldwide, constantly evolving and improving products is required to remain competitive. “We have to make decisions today for products two years from now,” says Sarah Kennedy, User Experience Researcher at Lenovo. To keep the decision-making process moving, Sarah’s team uses Google Surveys 360 for fast and accurate data. Bringing consumer insights to the table in the early stages of product development helps her team get buy-in from senior stakeholders at a faster pace. “Within seven days, we can get results that would normally take us a month,” says Sarah. 

Google Surveys 360 provides businesses with the data they need quickly, accurately, and affordably. Choose your target audience, write your survey, and get answers in as little as three days. Get started today.

Happy surveying!

¹PwC’s Global Data and Analytics Survey, Big Decisions™, Base: 1,135 senior executives, Global, May 2016

Posted by Kevin Fields, Product Marketing Manager, Google Surveys team

“As KASKUS is the leading digital community and social commerce platform, our vision is to drive data-driven monetization by making our first-party audience data actionable, we want to give advertisers ways to perform better in our sites and increase the effectiveness of our impression-based ads.” Ronny W. Sugiadha, Chief Marketing Officer for KASKUS

“Using the Google Analytics 360 Audience Segment sharing feature in DFP and AdX, we doubled our CTR and saw a 3.3X CPM uplift on this audience-targeted AdX inventory,” reports Ronny Sugiadha. “We are looking forward to even more positive impact moving forward.”

Hello, I’m Mark Edmondson and I have the honour of being a Google Developer Expert for Google Analytics, a role that looks to help developers get the most out of Google Analytics. My specialities include Google APIs and data programming, which has prompted the creation of googleAnalyticsR, a new R package to interact with the recently released Google Analytics Reporting API V4.

R is increasingly popular with web analysts due to its powerful data processing, statistics and visualisation capabilities. A large part of R’s strength in data analysis comes from its ever increasing range of open source packages. googleAnalyticsR allows you to download your Google Analytics data straight into an R session, which you could then use with other R packages to create insight and action from your data.

As well as v3 API capabilities, googleAnalyticsR also includes features unique to v4:

•  On the fly calculated metrics 
• Pivot reports 
• Histogram data 
• Multiple and more advanced segments 
• Multi-date requests 
• Cohorts 
• Batched reports 

The library will also take advantage of any new aspects of the V4 API as it develops.

Getting started

To start using googleAnalyticsR, make sure you have the latest versions of R and (optionally) the R IDE, RStudio

Start up RStudio, and install the package via:

install.packages(“googleAnalyticsR”)

This will install the package on your computer plus any dependencies.

After successful installation, you can load the library via library(googleAnalyticsR), and read the documentation within R via ?googleAnalyticsR, or on the package website.

An example API call — calculated metrics

Once installed, you can get your Google Analytics data similarly to the example below, which fetches an on-the-fly calculated metric:

library(googleAnalyticsR)

# authenticate with your Google Analytics login
ga_auth()

# call google analytics v4
ga4
                         date_range = c(“2016-01-01″,
                                       “2016-06-01″),
                         metrics = c(calc1=’ga:sessions /
                                            ga:users’),
                         dimensions = ‘medium’)

See more examples on the v4 help page.

Segment Builder RStudio Addin

One of the powerful new features of the v4 API is enhanced segmentation, however they can be complicated to configure. To help with this, an RStudio Addin has been added which gives you a UI within RStudio to configure the segment object. To use, install the library in RStudio then select the segment builder from the Addin menu. 

Create your own Google Analytics 

Dashboards googleAnalyticsR has been built to be compatible with Shiny, a web application framework for R.  It includes functions to make Google Analytics dashboards as easy as possible, along with login functions for your end users. 

Example code for you to create your own Shiny dashboards is on the website.

BigQuery Google Analytics 360 exports 

In addition to the v4 and v3 API functions, BigQuery exports from Google Analytics 360 can also be directly queried, letting you download millions of rows of unsampled data.

Aimed at analysts familiar with Google Analytics but not SQL, it creates the SQL for you to query common standard metrics and dimensions, using a similar interface as the API calls.  See the BigQuery section on the website for more details.

Anti-sampling 

To more easily fetch non-sampled data, googleAnalyticsR also features an anti-sampling flag which splits the API calls into self-adjusting time windows that are under the session sampling limit.  The approach used is described in more detail here.

Get involved 

If you have any suggestions, bug reports or have any ideas you would like to contribute, then you are very welcome to raise an issue or submit a pull request at the googleAnalyticsR Github repository, or ping me on Twitter at @HoloMarkeD.

Posted by Mark Edmondson, Google Developer Expert

• Digital analytics, such as optimizing email campaigns, testing content, and analyzing digital pathways to optimize website use and experience.
• Customer analytics, including lifetime value and loyalty calculations, response and purchase propensity modeling, and micro segmentation.
• Marketing analytics, such as demand forecasting, marketing attribution models, market mix modeling, and media budget optimization.
• Sales analytics, including pricing elasticity modeling, assortment planning, and sales territory design.
• Consumer analytics, including surveys/questionnaires, customer experience research, and customer satisfaction/advocacy modeling.

“Marrying digital and marketing analytics with consumer research from surveys gives marketers deeper insights and opens up the number of hypotheses a company can test.”
—Suzanne Mumford, Head of Marketing, Google Analytics 360 Suite

Posted by Kevin Fields, Product Marketing Manager, Google Surveys team