Introducing the Multi-Channel Funnels Reporting API

Measuring how marketing efforts influence conversions can be difficult, especially when your customers interact with multiple marketing channels over time before converting. Last fall, we launched Multi-Channel Funnels in Google Analytics, a new set of reports that help shed light on the full path users follow to conversion, rather than just the last click. One request we’ve had since the beginning was to make this data available via an API to allow developers to extend and automate use cases with the data. So today we’re releasing the new Google Analytics Multi-Channel Funnels Reporting API.

The API allows you to query for metrics like Assisted Conversions, First Interactions Conversions, and Last Interaction conversions, as well as Top Paths, Path Length and Time Lag, to incorporate conversion path data into your applications. Key use cases we’ve seen so far involve combining this conversion path data with other data sources, such as cost data, creating new visualizations, as well as using this data to automate processes such as bidding.

For example, Cardinal Path used the new Multi-Channel Funnels API, Analytics Canvas ETL (Extract, Transform, Load) and Tableau Software to help their client, C3 Presents, uncover how time and channels affected Lollapalooza ticket sales in an analysis dubbed “MCF DNA.” The outcome was a new visualization, similar to a DNA graph, that helped shed light on how channels appeared throughout the conversion funnel.

MCF DNA Visualization in Tableu Software

In another case, Mazeberry, an analytics company from France, helped their client 123Fleurs decrease customer acquisition costs by 20% by integrating data from the Multi-Channel Funnels API into a new reporting framework. Their application, Mazeberry Express, combines media cost and full conversion path data to provide new Cost Per Acquisition (CPA) and Return on Investment (ROI) metrics that provide a more complete understanding of how online channels are working together to influence conversions.

Mazeberry Express Screenshot - Focus on a Channel

Please note that this functionality only works with the new v3.0 API libraries, so you should upgrade now if you haven’t already (see our migration guide). We look forward to seeing how you make use of this new data source.


Posted by John Huang, Software Engineer

Upgrade now to the new Core Reporting API

Core Reporting API Migration Update
Back in December we launched the Core Reporting API to replace the Data Export API. We also announced that we would be shutting down the old Data Export API and that all applications should migrate to the new version.

The time has come for us to shut down the old version. So this is our last reminder to migrate to the new Core Reporting API.

Starting next week, we’ll begin redirecting a portion of Data Export API requests to the Core Reporting API as we prepare to shut down the Data Export API on July 10th. So you'll begin to see Data Feed requests return a Core Reporting API response, and requests for the Account Feed will produce an error.

If you do not migrate, your application will experience service outages.

For more information, visit:
Reminder: Migrate to the new Core Reporting API
Migration Guide: Moving from v2.3 APIs to v2.4 & v3.0



New Guides To Get You Started Fast
It’s important for the Google Analytics APIs to be open and accessible to all developers. It’s common practice for developers learning a new API to start off with the basics and incrementally build from this foundation.

So with that in mind, we wrote a new Hello Analytics API tutorial to give you that basic foundation. The tutorial includes sample code for Java, PHP, Python, and JavaScript. It also walks you through the basic steps of using the Google Analytics API, including registration, authorizing users, retrieving account and profile information, and querying for a report. Once complete you will have a working example that you can customize.

To make it even easier to build applications, we’ve also updated the developer guides for both the Core Reporting API and Management API. Examples for a variety of programming languages have been included, but more importantly the basic concepts have been highlighted.

So whether you’re just starting, updating, or migrating to the new version, you should check out the Hello Analytics API tutorial and Developer Guides before settling down to write that awesome application.


Posted by Pete Frisella, Nick Mihailovski, and Jeetendra Soneja, Analytics API team

Reminder: Migrate to the new Core Reporting API

At the end of 2011 we announced the Google Analytics Core Reporting API as a replacement for the Data Export API. We also announced a 6 month deprecation period for the Data Export API version 2.3, after which all v2.3 queries will return a v2.4 response. Well, it's almost been 6 months since the announcement was made. If you haven't already moved to our shiny new APIs, and we know there are quite a few of you out there who haven't, we urge you to get movin' or risk your application not working come June.

The good news is that we published a new, easy to follow migration guide to help you make the transition and ensure your application continues to work after we shut down the Data Export API sometime in June.

If you are building a new application, we highly recommend using the Core Reporting API v3.0. For existing applications, we also recommend moving to v3.0 but it may be easier for you to migrate to v2.4 as an intermediary step, since it is backwards compatible with the Data Export API v2.3.

The great news is that if you make the move to v3.0, you'll be able to take advantage of any new features, and the compact JSON format that reduces response size by 10x!

To get started, check out the Migration Guide: Moving from v2.3 APIs to v2.4 & v3.0.

Additional details and support:

• Core Reporting API Forum - for any questions you may have
• Core Reporting API Changelog - for details on the change

Posted by Pete Frisella, Google Analytics API team

New Google Analytics Easy Dashboard Library

Many developers save time by using the Google Analytics API to automate Analytics reporting tasks. For example, you can use the API to create a dashboard to report data across multiple profiles. The Google Analytics App Gallery includes many 3rd party solutions that do this.

What if you want to build something quickly that’s custom-tailored  to your business? You would typically have to spend time learning the API, figuring out how to handle authorization, then deciding how to integrate this data with a visualization library. You could build a custom solution, but it took a lot of effort – until now, thanks to the Google Analytics Easy Dashboard Library.

Four months ago we started a project with a team of University of California Irvine students to simplify all of these steps. As part of this project, together we built the Google Analytics Easy Dashboard Library. This library makes it easy to use the Google Analytics API by distilling the process into three easy steps:

1. Register with Google APIs Console.
2. Copy and paste the JavaScript code.
3. Configure this code to query your data and choose a chart type to visualize it.

So now you can create custom Google Analytics dashboards very quickly, with minimal code.

Here’s a quick example. Say you want to create a line chart plotting visitors and visits for the last 30 days. Besides including the library, the only code required is:

<div id=”chart1”></div>
<script>
var chart1 = new gadash.Chart({
  'type': 'LineChart',
  'divContainer': 'chart1',
  'last-n-days':30,
  'query': {
    'ids': TABLE_ID,
    'metrics': 'ga:visitors,ga:visits,ga:pageviews',
    'dimensions': 'ga:date',
    'sort': 'ga:date'
  },
  'chartOptions': {
    hAxis: {title:'Date'},
    vAxis: {title:'Visits'},
  }
}).render();
</script>

Using the code above will create this chart.



It’s that easy! To find out more about using the Easy Dashboard Library, read our Getting Started guide.

While the current library is very useful, we think we can add more features and make it even easier to use. To reach this goal, we’ve started working with another group of UC Irvine students, this time for three academic quarters. This new project’s main goal will be to further simplify the library. We want the students we’re working with to engage with you and implement your feature requests, if possible. If you use this library, we'd love to hear how you think it can be improved. Feel free to send any feedback to through our new GA-easy-dash-feedback google group.

We hope this library saves you time and helps you get more out of Google Analytics.

Posted by,
Jeetendra Soneja and Nick Mihailovski, Google Analytics API Team

More ways to measure your website's performance with User Timings

As part of our mission to make the web faster, Google Analytics provides Site Speed reports to analyze your site’s page load times. To help you measure and diagnose the speed of your pages in a finer grain, we’re happy to extend the collection of Site Speed reports in Google Analytics with User Timings.

With User Timings, you can track and visualize user defined custom timings about websites. The report shows the execution speed or load time of any discrete hit, event, or user interaction that you want to track. This can include measuring how quickly specific images and/or resources load, how long it takes for your site to respond to specific button clicks, timings for AJAX actions before and after onLoad event, etc. User timings will not alter your pageview count, hence,  makes it the preferred method for tracking a variety of timings for actions in your site.

To collect User Timings data, you'll need to add JavaScript timing code to the interactions you want to track using the new _trackTiming API included in ga.js (version 5.2.6+) for reporting custom timings. This API allows you to track timings of visitor actions that don't correspond directly to pageviews (like Event Tracking).  User timings are defined using a set of Categories, Variables, and optional Labels for better organization. You can create various categories and track several timings for each of these categories. Please refer to the developers guide for more details about the _trackTiming API.

Here are some sample use cases for User Timings

• To track timings for AJAX actions before and after onLoad event. 
• A site can have their own definition of “User Perceived Load Time”, which can be recorded and tracked with user timings.  As an example, news websites can record time for showing the above fold content as their main metric instead of onLoad time. 
• Detailed performance measurement and optimization of sub components on a page, such as time to load all images, CSS or Javascript, download PDF files and time it takes to upload a file.

Want to check out User Timings Report in your account?
Go to the content section and click the User Timings report under Content section. There are three tabs within the User Timings report for you to review: Explorer, Performance, & Map Overlay. Each provides a slightly different view of user timings reported.

The Explorer tab on the User Timings report shows the following metrics by Timing Category, Timing Variable, or Timing Label (all of which you define in your timing code).

• Avg. User Timing—the average amount of time (in seconds) it takes for the timed code to execute
• User Timing Sample—the number of samples taken

The Explorer tab also provides controls that you can use to change the tabular data. For example, you can choose a secondary dimension—such as browser— to get an idea of how speed changes by browser.

To learn more about which timings are most common for user timings, switch to the Performance tab. This tab shows timing buckets, providing you with more insight into how speed can vary for user reported timings for selected category, variable and label combinations. You may switch to Performance tab at any point of navigation in the Explorer tab, such as after drilling down on a specific category and variable, to visualize distribution of user reported timings.  The bucket boundaries for histograms in Performance Tab are chosen to be flexible so that users can analyze data at low values ranging from 10 milliseconds granularity to 1 minute granularity with addition of sub-bucketing for further analysis.

The Map Overlay tab provides a view of your site speed experienced by users in different geographical regions (cities, countries, continents).

-  Satish Kambala & Mustafa M. Tikir, Google Analytics team

Measuring app engagement across device & platforms

There are more ways now to consume your favorite television shows, movies, and on demand content than ever before. People are turning to their smartphones, tablets, and Internet connected TV’s to watch what they want, when they want it. For broadcasters, agencies, and advertisers the question is how are users engaging with this media and how can it be monetized?

This measurement opportunity is what drove TV App Agency to be founded in 2011. The London-based software company designed a software application that works across a variety of viewing devices to help deliver on-demand media. They turned to Google Analytics as the platform to help them measure and analyze their data.

Why turn to Google Analytics?
TV App Agency opted to use Google Analytics’ server side APIs, which were more easily compatible with the on-demand media environment than JavaScript APIs. They were able to use their own in-house knowledge from previous mobile development to come up with a tagging strategy that highlighted exactly the data that mattered most to their business model. Learn more by reading the full case study.



“We are now able to track which adverts are being played and get an idea of which functions in apps are being used. Plus, the real-time reports show when people are actually using these apps.”
                          Bruno Pereira, co-founder of TV App Agency

Future Analytics goals

TV App Agency is working on expanding their Analytics to track more events, and understand more about viewer engagement from Analytics robust reports. By integrating Google Analytics they are able to offer richer data and analysis than other connected TV app developers, which gives them an incredible advantage in this exciting new space.

- The Google Analytics team

Sharing Personalized Dashboards using the Analytics API

Web agencies often rely on Excel and Word to create analytics reports for clients. It’s a manual process that involves a lot of copy and pasting. Yet an agency’s main value-add isn’t report creation, but analyzing data and providing key findings and recommendations to clients. And while Google Analytics provides the tools to slice and dice the data, many web agencies also want to present clients with personalized reports, complete with the agency’s logo. And they want to be able to deliver and share reports without requiring users to log in, especially in large organizations where report distribution can become an onerous administrative process.

DashThis addresses these challenges with dashboards that combine simple automatic reporting with accessibility. Agencies spend less time creating reports and more time analyzing. Using the Google Analytics API, DashThis imports the client’s data and updates a set of dashboards with Key Performance Indicators (KPIs) for a specific job function or industry. The agency can also request a set of custom dashboards that meet exact specifications and requirements.

Alerts and warnings can be set to notify managers of changes in KPIs via email. All this is accomplished securely and without requiring the user to log in. There is also a white-label option for additional branding requirements demanded by agencies.

According to Kari Harju, CEO of SalesLion, an SEO and conversion agency in Helsinki, Finland. “Customers do not always understand how to read the results from web analytics products and see a tangible return on their investments. It's hard to show them without time consuming meetings. SalesLion opted for a custom dashboard to meet the needs of their clients. As a result of using DashThis, our clients now have a simple and easy way to understand what’s going on with their web properties as it relates to their KPIs”. SalesLion eliminated most of the reporting work, leaving more time to analyze, highlight key findings, and make actionable recommendations to clients.


DashThis was built by Trimali Technologies and uses the Google Analytics API. Stéphane Guérin, CEO describes DashThis’ experience with the Google Analytics API and the response from customers, “The API is really simple to use but extremely powerful. It allows developers to add even more value on a great tool such as Google Analytics. We’ve been able to develop strong business relationships with agencies and we’re proud to have made a tool that is useful for professionals. By opening the platform, Google Analytics allows smaller companies like ours to flourish in a rich eco-system.”


DashThis can be found in the Google Analytics App Gallery and on the DashThis website.
If you’re interested in developing solutions for the Google Analytics platform, visit Google Analytics Developers.


Posted by Pete Frisella, Google Analytics API Team

PBS saves time with automated reports

For most companies using Google Analytics, reporting on website traffic and performance for a few web properties is a straightforward task. However, if your company manages hundreds of web properties, delivering useful and timely reports can become a significant challenge. For many, the only apparent solution is to manually export analytics data for each web property, then combine and compare that data to answer relevant business questions. It’s a slow and costly process and you spend most of your time creating reports instead of carrying out meaningful analysis.

The Public Broadcasting Service (PBS) faced precisely this challenge when it made the decision to use GA Data Grabber by AutomateAnalytics.com. GA Data Grabber works within Excel and uses the Google Analytics API. Users create or choose reports and GA Data Grabber automatically retrieves the Google Analytics data from any number of websites. And with multi-login capabilities, users can seamlessly combine data between Google Analytics profiles that reside under different Google Accounts.

Designed for non-technical users, GA Data Grabber generates great-looking visualizations and can automatically highlight important changes in key metrics over a date range. It’s also possible to use Excel’s visualization and data processing features. For example, formulas can be added to calculate Key Performance Indicators (KPIs) based on any set of metrics.




Amy Sample, Director, Web Analytics, Public Broadcasting Service explains the challenges that PBS faced and how GA Data Grabber was able to help. “The PBS.org and PBSKIDS.org web sites are made up of hundreds of individual companion sites to broadcast programs.  From a business perspective, there is a need to evaluate performance of individual program sites relative to each other.” As is common for many large organizations, PBS has separate Google Analytics accounts for each program site. “While multiple accounts works well to evaluate the site content and performance, it makes it difficult to look at all of the sites side-by-side without a lot of manual effort.  Our previous attempts to create this type of report were time-consuming and often subject to data input errors.”

“Using Google Analytics, combined with GA Data Grabber, we were able to create a benchmark report for our program sites. The monthly report pulls a standard set of KPIs from each of the program accounts and ranks the programs by traffic. The report is used as a management tool by both the PBS.org and PBSKIDS.org teams to monitor monthly performance of programs. The teams have also used it to identify opportunities for programs that are no longer being broadcast but still getting significant online traffic.  Our program producers use the report to benchmark their performance against other sites of similar content or size and determine ways to improve audience engagement. As a result of using GA Data Grabber to pull the data, we can produce this report quickly and accurately on monthly basis.”

GA Data Grabber
Mikael Thuneberg, Founder & CEO of AutomateAnalytics.com has been using the Google Analytics API since its launch. “I’ve been very happy with the API. Having developed for several other APIs, I can say that the Google Analytics API is by far the easiest to develop for. It’s logically structured and flexible, the documentation is excellent, and it’s easy to get help through the forum. I’ll certainly continue developing for the Google Analytics API. I’ve expanded to other APIs as well, but Google Analytics is still by far the most important one for my business.”

GA Data Grabber can be found through the Google Analytics App Gallery and can be downloaded from the GA Data Grabber website.

If you’re interested in developing solutions for the Google Analytics platform, visit Google Analytics Developer Program.

Posted by Pete Frisella, Google Analytics API Team

The power of visualization with the Google Analytics API and Google Earth

Does your organization have several websites, each serving a particular geographic region? If so you know how challenging it is to analyze the data across these regions in a meaningful way.

Visualizations can help, but they can be difficult to design. Newland communities, a developer of residential and urban home communities, manages numerous web properties for each community and is no stranger to these challenges. To address them, Newland used the query tool from ShufflePoint. The tool enabled the combination of data from Google Analytics and Google Earth, allowing Newland to visualize the data in new ways.

ShufflePoint implemented a pilot project after discussing the idea with Chief Ingredient and their client Newland Communities. Their goal: deal with some of the problems associated with clarifying large amounts of data in a visually appealing manner. The outcome of the project was an integration of Google Analytics data with Google Earth.

Using the Google Analytics API, the ShufflePoint query tool extracts metrics by location from Google Analytics for multiple Newland Communities web properties and creates static and time-animated geographic representations (using KML) viewable in Google Earth. The mashup provides advanced visual reporting on location based campaigns, showing their effect on pageviews, and highlighting any anomalies requiring further investigation. Additionally, the visualization is a great fit for promotional videos, or digital signage needs.



“ShufflePoint uses almost every feature and capability of the Google Analytics API. The API has all of the characteristics that a developer could hope for, including great performance, correct semantics, OAuth for authentication, and good community support. The Google Earth based application has given ShufflePoint recognition for doing innovative and challenging things with Google Analytics. This has been beneficial for promoting ShufflePoint’s offerings.” Chris Harrington, CTO

The ShufflePoint application can be found through the Google Analytics App Gallery and from the ShufflePoint website.

If you’re interested in developing solutions for the Google Analytics platform, visit Google Analytics Developer Program.

Posted by Pete Frisella, Google Analytics API Team

Introducing the Google Analytics Core Reporting API

Today we are announcing the new Google Analytics Core Reporting API as a replacement for the Data Export API. This is the second phase in a larger project we started a couple months back to upgrade our APIs to new infrastructure.

The Core Reporting API has two versions.

Version 3.0 is a brand new API, with a 10x reduction in output size and support for many new client libraries, like PHP, Ruby, Python, JavaScript and Java. All new features will only be added to this version.

Version 2.4 is backward compatible with the legacy Data Export Version 2.3.

If you are building a new application or maintaining an existing one, we highly recommend migrating to version 3.0.

One of the biggest changes in switching to the Core Reporting API is that you now need to register your applications via the Google APIs Console and use a project ID to access the API.

With this change, we are also announcing the deprecation of the Data Export API version 2.3. This API will continue to work for 6 months, after which all v2.3 XML requests will return a v2.4 response. Also, we plan to terminate the Data Export API Account Feed. All configuration data should be retrieved through the Google Analytics Management API.

See our Data Export API changelog for all the details of the change and read our developer documentation for more details about each API.

If you have any questions feel free to reach out in our Data Export API Google group.

Thanks,
Jeetendra Soneja and Nick Mihailovski, Google Analytics API Team