Get social, mobile, and 40+ new data points with the Google Analytics API

Google Analytics Core Reporting APIs enable a powerful and flexible way to analyze, report on, and ultimately optimize such things as web and mobile experiences, conversions, and sales.



Today we’re adding over 40 new metrics and dimensions that can be queried through the Core Reporting API. This enables developers to create reports that are similar to what is available in the Google Analytics web interface for important areas such as social and mobile. See a full list of additions on the Core Reporting API changelog.

Here’s a rundown of what’s new and a few helpful questions the data can answer.



Social Data

Now you can get data for both on-site interactions with social buttons as well as off-site social data from social data hub partner networks.

• Which content receives the most comments on social networks?


• What are the conversion rates for visits from social networks?


• For social buttons embedded in my property, which ones get used most often and for which content?

Mobile Devices

For mobile visits to your site, get all the good stuff like like brand, model, and input type.

• What are the top 10 mobile devices used to visit my website?

Geo

We added a new dimension to indicate the Designated Market Area (DMA) where traffic came from.

• What are the Top 10 Campaigns for the San Francisco Bay Area DMA?

Page Path Rollups

Create your own drill down reports with these new dimensions that allow you to roll-up metrics to hierarchical levels of your property.

• What does the performance of my website look like across different sections?

App & Exception Tracking

If you’re using the Google Analytics SDK for iOS/Android v2 beta, you can now retrieve App View and Exception metrics.

• On a daily basis, how many views did my mobile app get?


• On a daily basis, how many exceptions occurred in my mobile app, and how many exceptions were fatal? 

User Timings

New ways to report on all things related to user timing data.

• What were the time measurements for all user defined timings?

Related Resources:

• Dimensions & Metrics Reference for a list of all available metrics & dimensions. 


• Google Analytics Query Explorer to help you build queries and try out the Core Reporting API.


• Core Reporting API changelog for a list of the 40+ new dimensions & metrics.

Posted by Pete Frisella and Nick Mihailovski, Google Analytics API team

Combining a User Problem with a Desire to Learn: the Story of Quicklytics

This article is part of our Developer Spotlight Series that promotes new tools and applications built using the Google Analytics Developer platform. To see other tools, check out our App Gallery. Interested in having us showcase your story? Let us know what you’re working on!



Eduardo Scoz is a software architect and self-proclaimed, “analytics addict.” In early 2010, he grew frustrated with his daily routine of checking in on his web analytics from several sites and personal blogs. Very quickly he found himself spending an overwhelming amount of time monitoring his key metrics from across his own content kingdom: he yearned for a way to keep an eye on his KPI’s without having it feel like a full-time job.


Eduardo was determined to find an iPhone application that gave him a high-level view of all of his sites in way that was easy to digest. After a few days of searching he realized that the only way for him to get exactly what he wanted was to build it himself. He had never built an iPhone application but his “learn by doing” mentality prevailed: after a few weeks of prototyping, he had come up with something he was proud of. He showed it to a few friends and gauging their reaction, he realized he might be onto something. He incorporated their feedback, finished building it out and decided to release it publicly. In February 2010, Quicklytics was born.


Quicklytics allows users to rapidly check the status of multiple websites in a matter of seconds and visually understand how their site is performing for both current and historical timeframes. It has full support for both iPhone and iPad as well as custom filtering that allows for quick deep dives into areas of interest. While its primary views focus on top-level metrics, Quicklytics also provides detailed reports with most of the data also available through Google Analytics.

“All apps were about either showing as much data as possible, or focusing on less-useful stuff, like browsers and screen sizes, which are only really necessary when you’re doing deep analysis, not when ‘checking the weather’,” says Eduardo.


As soon as Quicklytics hit the App Store, it spread like wildfire. In the 2 ½ years since it was released, Quicklytics has received over 40,000 downloads - most of which were paid. This has translated into a significant source of side revenue for Eduardo’s business that has allowed him to continue building new features for Quicklytics while looking for new projects to learn from.  Now, Eduardo finds great joy in using Quicklytics to measure the mobile app analytics on - you guessed it - Quicklytics.


Quicklytics leverages the Analytics Core Reporting APIs Objective-C library and OAuth 2.0 for user authentication. Although this was Eduardo’s first experience with the Analytics APIs and Objective-C, he was able to take full advantage of the Developer Forums for support: “In the few cases I found issues with the tool, Google developers were actually very helpful and fixed some issues from their side. It was a great experience.”


Armed with a clear user problem and a willingness to learn, Eduardo was able to turn one of his biggest pain points into a viable side business and a solution that is enjoyed by many. According to Eduardo, “It’s great to know that a lot of people find it as useful as I do.”


To learn more about Quicklytics, check out his App Store listing.


Posted by John Milinovich, Google Analytics API team

Automate Google Analytics Reporting using Google Apps Script

Many people have been asking for a simple way to put Google Analytics data into a Google Spreadsheet. Once the data is inside a Google Spreadsheet, users can easily manipulate Google Analytics data, create new visualizations, and build internal dashboards.



So today we released a new integration that dramatically reduces the work required to put Google Analytics data into any Apps Script supported product, such as Google Docs, Sites, or Spreadsheets.



Here’s an example of Google Analytics data accessed through Apps Script and displayed in a Google Spreadsheet.

Custom API Dashboards - No Code Required

We know that a popular use case of this integration will be to create dashboards that automatically update. To make this easy to do, we’ve added a script to the Spreadsheets script gallery that handles all this work - no code required. The script is called Google Analytics Report Automation (Magic).



This script is a great template for starting your own project, and we’ve had many internal Google teams save hours of time using this tool. Here’s a video demoing how to build a dashboard using this script:





You can find this script by opening or creating a Google Spreadsheet, clicking Tools -> Script Gallery and searching for “analytics magic”.

Writing Your Own Script

Of course many developers will want to write their own code. With the new Analytics – Apps Script integration, you can request the total visitors, visits, and pageviews over time and put this data into a spreadsheet with just the following code:

// Get Data.
var results = Analytics.Data.Ga.get(
    tableId,
    startDate,
    endDate,
    'ga:visitors,ga:visits,ga:pageviews',
    {‘dimensions’: ‘ga:date’});

// Output to spreadsheet.
var sheet = SpreadsheetApp.getActiveSpreadsheet().insertSheet();
sheet.getRange(2, 1, results.getRows().length, headerNames.length)
    .setValues(results.getRows());

// Make Sandwich.

To get started now, read our Automated Access to Google Analytics Data in Google Spreadsheets tutorial. Also check out the Google Analytics Apps Script reference docs.

Solving Business Problems

Are you ready to start building solutions using Google Analytics and Google Apps Script?



We’d love to hear new ways you use this integration to help manipulate, visualize and present data to solve business problems. To encourage you to try out this integration, we are giving out Google Analytics developer t-shirts to the first 15 developers to build a solution using both APIs.



To be eligible, you must publish your solution to either the Chrome Web Store or the Spreadsheets Script Gallery and include a description of a business problem the script solves. We’ll then collect these scripts and highlight the solutions in an upcoming blog post. After you publish your script, fill out this form to share what you’ve built.



We’re looking forward to seeing what you can do with this integration.

Posted by Nick Mihailovski   profile Nick is a Senior Developer Programs Engineer working on the Google Analytics API. In his spare time he likes to travel around the world.

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