Showing posts with label Developer. Show all posts

Introducing the new Google Analytics Partner Gallery

Tuesday, June 24, 2014 | 6:58 AM

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Google Analytics has a vibrant ecosystem of analytics practitioners, advocates, and developers that drive great conversations, learnings, and sharing among passionate users. A central part of this ecosystem is partners, which can help users quickly increase the business value of Google Analytics through implementation expertise, analysis, and integrations.

To make it easier to find services and apps that are important to your business, we’ve re-launched the App Gallery as the Partner Gallery, the new destination to find partners and review their offerings. It includes:

Certified Partners are vetted by Google and meet rigorous qualification standards. This includes agencies and consultancies who offer web analytics implementations, analysis services and website testing and optimization services.

Ready-to-use applications that extend Google Analytics in new and exciting ways. This includes solutions that help analysts, marketers, IT teams, and executives get the most out of Google Analytics and complement functionality.



The Partner Gallery includes new features and improvements:
  • A brand new look and layout.
  • A combined view of both services and apps so you don’t need to visit multiple sites to find a solution.
  • New search capabilities and category selection making it easier to filter and find what you’re looking for.
  • Google Analytics Certified Partners are sorted based on your location to find partners that have an office near you.
  • Media assets like screenshots / videos / case studies that highlight customer success stories and illustrate app features.
  • Comments and ratings to review user experiences and provide feedback.
Visit the Partner Gallery to browse partner services and apps. If you’re interested in the Google Analytics Certified Partner or Technology Partner programs, learn how to become a partner.

Pete Frisella, Developer Advocate, Google Analytics Developer Relations team

New user and sequence based segments in the Core Reporting API

Friday, April 11, 2014 | 10:30 AM

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Segmentation is one of the most powerful analysis techniques in Google Analytics. It’s core to understanding your users, and allows you to make better marketing decisions. Using segmentation, you can uncover new insights such as:
  • How loyalty impacts content consumption
  • How search terms vary by region
  • How conversion rates differ across demographics
Last year, we announced a new version of segments that included a number of new features.

Today, we’ve added this powerful functionality to the Google Analytics Core Reporting API. Here's an overview of the new capabilities we added:

User Segmentation
Previously, advanced segments were solely based on sessions. With the new functionality in the API, you can now define user-based segments to answer questions like “How many users had more than $1,000 in revenue across all transactions in the date range?”

Example: &segment=users::condition::ga:transactionRevenue>1000

Try it in the Query Explorer.

Sequence-based Segments
Sequence-based segments provide an easy way to segment users based on a series of interactions. With the API, you can now define segments to answer questions like “How many users started at page 1, then later, in a different session, made a transaction?”

Example: segment=users::sequence::ga:pagePath==/shop/search;->>perHit::ga:transactionRevenue>10

Try it in the Query Explorer.

New Operators
To simplify building segments, we added a bunch of new operators to simplify filtering on dimensions whose values are numbers, and limiting metric values within ranges. Additionally, we updated segment definitions in the Management API segments collection.

Partner Solutions
Padicode, one of our Google Analytics Technology Partners, used the new sequence-based segments API feature in their funnel analysis product they call PadiTrack.

PadiTrack allows Google Analytics customers to create ad-hoc funnels to identify user flow bottlenecks. By fixing these bottlenecks, customers can improve performance, and increase overall conversion rate.

The tool is easy to use and allows customers to define an ad-hoc sequence of steps. The tool uses the Google Analytics API to report how many users completed, or abandoned, each step.

paditrack-horizontal-funnel.jpg

Funnel Analysis Report in PadiTrack

According to Claudiu Murariu, founder of Padicode, “For us, the new API has opened the gates for advanced reporting outside the Google Analytics interface. The ability to be able to do a quick query and find out how many people added a product to the shopping cart and at a later time purchased the products, allows managers, analysts and marketers to easily understand completion and abandonment rates. Now, analysis is about people and not abstract terms such as visits.”

The PadiTrack conversion funnel analysis tool is free to use. Learn more about PadiTrack on their website.

Resources

We’re looking forward to seeing what people build using this powerful new functionality.

Posted by Nick Mihailovski, Product Manager, Google Analytics team

Sending data from Lantronix to Google Analytics

Friday, March 28, 2014 | 9:33 AM

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The following is a guest post from Kurt Busch, CEO, and Mariano Goluboff, Principal Field Applications Engineer at Lantronix.

Background
Google Analytics makes it easy to create custom dashboards to present data in the format that most helps to drive business processes. We’ve put together a solution that will make several of our devices (networking and remote access devices) easily configurable to enable delivery of end device data to Google Analytics. We use the Lantronix PremierWave family of devices to connect to an end device via a serial port like RS-232/485, or Ethernet, intelligently extract useful data, and send it to Google Analytics for use in M2M applications. 

What you need
To get started, grab the Pyserial module, and load it on your Lantronix PremierWave XC HSPA+. You’ll also want a device with a serial port that sends data you want to connect to Google Analytics. A digital scale like the 349KLX is a good choice.

Architecture overview
With the Measurement Protocol, part of Universal Analytics, it is now possible to connect data from more than web browsers to Analytics.

Lantronix integrated the Measurement Protocol by using an easy to deploy Python script. By being able to natively execute Python on PremierWave and xSenso devices, Lantronix makes it very easy to deploy intelligent applications leveraging Python’s ease of programming and extensive libraries.

The demonstration consists of a scale with an RS-232 output, connected to a Lantronix PremierWave XC HSPA+. The Python script running on the PremierWave XC HSPA+ parses the data from the scale, and sends the weight received to Google Analytics, where it can then be displayed.

The hardware setup is show in the picture below.


The technical details
The Python program demonstrated by Lantronix uses the Pyserial module to parse this data. The serial port is easily initialized with Pyserial:
class ser349klx:
# setup the serial port. Pass the device as '/dev/ttyS1' or '/dev/ttyS2' for
# serial port 1 and 2 (respectively) in PremierWave EN or XC HSPA+
def __init__(self, device, weight, ga):
while True:
try:
serstat = True
ser = serial.Serial(device,2400, interCharTimeout=0.2, timeout=1)
except Exception:
serstat = False
if serstat:
break
self.ser = ser
self.weight = weight
self.ga = ga

The scale used constantly sends the current weight via the RS-232 port, with each value separated by a carriage return:

def receive_line(self):
buffer = ''
while True:
buffer = buffer + self.ser.read(self.ser.inWaiting())
if '\r' in buffer:
lines = buffer.split('\r')
return lines[-2]

The code that finds a new weight is called from a loop, which then waits for 10 equal non-zero values to wait for the weight to settle before sending it to Google Analytics, as shown below:
# This runs a continuous loop listening for lines coming from the
# serial port and processing them.
def getData(self):
count = 0
prev = 0.0
#print self.ser.interCharTimeout
while True:
time.sleep(0.1)
try:
val = self.receive_line()
weight.value=float(val[-5:])*0.166
if (prev == weight.value):
count += 1
if (count == 10) and (str(prev) != '0.0'):
self.ga.send("{:.2f}".format(prev))
else:
count = 0
prev = weight.value
except Exception:
pass

Since the Google Analytics Measurement Protocol uses standard HTTP requests to send data from devices other than web browsers, the ga.send method is easily implemented using the Python urllib and urllib2 modules, as seen below:

class gaConnect:
def __init__(self, tracking, mac):
self.tracking = tracking
self.mac = mac
def send(self, data):
values = { 'v' : '1',
'tid' : self.tracking,
'cid' : self.mac,
't' : 'event',
'ec' : 'scale',
'ea' : 'weight',
'el' : data }
res = urllib2.urlopen(urllib2.Request("http://www.google-analytics.com/collect", urllib.urlencode(values)))

The last piece is to initialize get a Google Analytics connect object to connect to the user’s Analytics account:

ga = gaConnect("UA-XXXX-Y", dev.mac)

The MAC address of the PremierWave device is used to send unique information from each device.

Results
With these pieces put together, it’s quick and easy to get data from the device to Google Analytics, and then use the extensive custom reporting and modeling that is available to view the data. For example, see the screenshot below of real-time events:


Using Lantronix hardware, you can connect your serial devices or analog sensors to the network via Ethernet, Wi-Fi, or Cellular. Using Python and the Google Analytics Measurement Protocol, the data can be quickly and easily added to your custom Google Analytics reports and dashboards for use in business intelligence and reporting.

Posted by Aditi Rajaram, the Google Analytics team


New tools to grow your mobile app business

Tuesday, March 18, 2014 | 6:30 AM

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Today at the Game Developers Conference in San Francisco we will be announcing two key launches powered by Google Analytics and Google Tag Manager. You can follow the livestream today at 10:00AM PDT (5:00PM UTC) with the Google Analytics sessions from 2:30PM PDT.

Announcement #1: Bringing the power of Google Analytics to AdMob
We’re happy to announce that Google Analytics is fully available in the AdMob interface on a new Analyze tab. App developers now have a one-stop way to measure success and adjust their earning strategies based on what they learn.

Today’s app developers have to make decisions quickly and implement them seamlessly if they want to stay relevant. It also helps if every business decision is backed up and validated by reliable data. Until now, app developers using AdMob and Google Analytics had to use two separate tools to monetize and measure. Starting today, they’re now in one place.

More than just Google Analytics inside AdMob
The new tab is simpler, yes. But app businesses can also now make decisions faster without losing data accuracy. They’ll also benefit from a new set of features that make measurement the foundation of all monetization programs:
  • drop down menu to switch between individual apps reports
  • new home page with combined Google Analytics and AdMob reporting
  • new Analyze tab with all Google Analytics reports
To see the new feature in action, sign in to your AdMob account and look for the Analyze tab at the top of the page. 

click to enlarge

Your new home tab in AdMob will now incorporate data on how your app is monetizing as well as how it is performing overall with insights on in app purchase, traffic and ads metrics in your app: all in one tab - a unique feature just in Admob.

click to enlarge

Get started in one click with Google Analytics and AdMob 
1. Login or open a new account on AdMob and sign up for Google Analytics (GA) in the new Analyze tab. 
2. If you are already using Google Analytics for your apps, you can link your existing account with AdMob in the Analyze tab. 
3. If you are not using Google Analytics, you can sign up via AdMob and complete the process without leaving the interface.

Announcement #2: New Content Experiments with Google Tag Manager
People have a lot of choice when it comes to apps and keeping them engaged is a challenge. Businesses who experiment with different app layouts have a higher chance to find the best performing solution and keep users engaged. A few months ago we announced Google Tag Manager for apps, today we are enabling content experiments: an easy way to set up and run experiments to change anything from in-app promotions to menu layout. With Google Tag Manager you can modify app configuration for existing users without having to ship a new version.

But how can we always be sure that we are changing it for the best? Wouldn’t it better if you could validate business decisions with data? Now you can run content experiments on a subset of your users to choose the best option - where to show promotions? How often? Data in Google Analytics will answer your questions and you can now be sure your decisions will be backed by data.

Google Tag Manager has been built to be very intuitive, even for people not familiar with coding. Businesses can now let their marketers or business analysts run experiments without requiring a developer to be involved. App experiments are now accessible to everyone.


click to enlarge

Getting started with Google Tag Manager
  1. Sign up for an account at www.google.com/tagmanager and create a mobile container
  2. Download the SDK for either Android or iOS. 
  3. Start programming! Use the SDK to instrument configuration and events you care about in your app.
  4. When you’re ready to dynamically change your app, use the Google Tag Manager interface to start configuring. Remember to press the “Publish” button to push your rules and configurations to your users.
Posted by Russell Ketchum, Lead Product Manager, Google Analytics for Mobile Apps and Google Tag Manager

Storytelling with data using Measureful and Google Analytics

Friday, March 07, 2014 | 10:08 AM

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The following is a guest post from John Koenig, CEO at Measureful.

The democratization of data within organizations over the last few years has put data even more under the purview of marketers. This shift has created a necessary discipline in digital intelligence: data storytelling. Data storytelling strives to create a clear, more meaningful picture of complex metrics through effective storytelling techniques. 

Combining Measurable and Google Analytics brings together a powerful measurement and presentation tool to help quantify efforts and present a compelling case. Google Analytics is the vehicle for discovering stories, while Measureful brings these stories to life.

A Beginning, Middle and End

A top down, linear approach following these 3 steps helps keep your marketing reports focused and your audience tuned in.


1. What happened? 

If you’ve built even a basic Google Analytics strategy, you’ll have already identified your objectives or KPIs (key performance indicators). Start each report by covering these first. Be short and concise with KPIs and focus on basic performance to set the tone for the rest of the report.

These are most often a conversion event such as revenue or a user-defined goal such as a new lead. This is one portion of your report that should be fairly static. Objectives generally don’t change frequently and thus other portions of your report should roll up to these. The narrative of your report will largely be focused around explaining changes to this key group of metrics.

2. Why and what caused it?

This is where most reports fall into trouble. Even if you have access to large amounts of data and reports, it doesn’t mean you need to use all of it. The reality is you only have the attention of your audience for a small amount of time so be selective, focus on bringing together cohesive points, and leave everything else out.

This means your reports should be dynamic and change each month. That’s right, your reports should change. If they aren’t changing you’re not telling a story, you’re regurgitating data.

Focus on identify 2 to 3 subtle narratives to focus on but do not bypass exploratory and quantitative analysis. You still need to begin each period analyzing changes and interpreting data to determine the most effective points. This is analysis work, but if you’ve set up a strategy, this doesn’t have to be time-consuming or overly complex. 

I suggest looking at 3 areas to help build your storylines -

1. Attribution
2. Campaigns
3. Outliers

If Revenue (your KPI) increased last period, drill into theAll Traffic reporint in Google Analytics and begin to attribute why this change occurred. It is not importatnt to  report on every segment and dimension but instead focus on why this change occurred.


This is also the portion where you can outline any specific campaigns that were run during the period and include metrics specific to these and their performance.

Lastly, look for outliers. While these may not be immediately apparent, both Measureful and Google Analytics provide tools for helping with these. In Google Analytics, set up rules in Intelligence Events. With Measureful, use the Smart Reporting feature. This works similar to Intelligence Events, but runs automatically and covers trends for many different segments and time-periods. Turn it on and let it help you identify unique stories in your Google Analytics data.




3. What’s next?

Give your story an ending by reiterating your points, making recommendations and covering next steps. This is where you can push your agenda, ask for more budget or suggest some new strategy or tactics.

Storytelling in Practice

Gerber relies on a sophisticated measurement strategy using advanced Google Analytics features to quantify marketing efforts and drive campaign decisions. John Robbins is the Digital Marketing Manager at GerberGear.com and is responsible for a myriad of digital channels and campaigns and is expected to report on performance.

John leverages both Google Analytics and Measureful to help keep the whole team easily informed and knowledgeable of key findings and changes.

Tying it all together with Measureful

With analytics data in place, the linear approach is easily applied and the Gerber Monthly Marketing Report built using Measureful’s WYSIWYG editor.

For example, Gerber’s top-line of metrics were setup to provide a quick view of performance for the month while two over-time visualizations were add for context. Measureful’s reporting platform includes automated narratives with analysis on performance versus the previous month, year and compared to the 12-month average. 



After a bit of analysis, it’s clear that a few channels performed very well and thus the focus of the reports begin to take shape around these narratives. While Gerber’s digital strategy goes well beyond the contents of this particular report, it's most effective to report on the metrics that are important to business objectives. Measureful helps Gerber focus a report on the key take-aways and points and thus steer an audience’s attention to what’s most critical.

And finally, it’s helpful to end a report with clear points and next steps.



Gerber went from long and time-consuming marketing reports that were often overlooked to a 4-page, focused report that drives home the main points in their marketing and analytics strategies.

Data storytelling is an essential skill to effectively cross the chasm of understanding and ultimately action. Charts and tables do not necessarily mean you’ve done a good job of communicating important findings. Meausureful can help weave Google Analytics data into a coherent narrative, and turn your data into a powerful communication tool.

Posted by Aditi Rajaram, The Google Analytics team


Using Universal Analytics to Measure Movement

Friday, December 13, 2013 | 10:08 AM

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The following is a guest post by Benjamin Mangold, Director of Digital & Analytics at Loves Data, a Google Analytics Certified Partner.

Universal Analytics includes new JavaScript tracking code for websites and new mobile SDKs. But Universal Analytics is a lot more than that - it also gives us the Measurement Protocol, which allows us to send data to Google Analytics without the need to use the tracking code or SDKs.

Earlier this year, the team at Loves Data used Universal Analytics and the Measurement Protocol to measure their caffeine consumption and tie it to the team’s productivity. Our next challenge: measuring our team’s movement into Google Analytics. With the help of an Xbox Kinect, movement recognition software, and of course the Measurement Protocol, we started getting creative!



Business Applications and Analysis Opportunities

So measuring movement is fun and although we can measure total and unique dance moves you might be wondering about the business applications. This is where the power of measuring offline interactions can really start to be seen. The Measurement Protocol enables business applications such as:
  • Measuring in-store purchases and tying purchases to your online data
  • Understanding behaviour across any connected device, including gaming consoles
  • Comparing offline billboard impressions to online display ad impressions
  • Getting insights into your audience’s online to offline journey
Once you have tied your online and offline data together you can begin to analyze the full impact of your different touch points. For example, if you are collecting contact details online, you can use Google Analytics to then understand who actually converts offline, whether this conversion is attending an information session or making a purchase at a cash register. The analysis possibilities made available by the Measurement Protocol are truly amazing.

New Secondary Dimensions Provides Deeper Insights Into Your Users

Thursday, November 21, 2013 | 10:38 AM

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Today we’ve added many new secondary dimensions to standard reports, including the much-asked for Custom Dimensions.


Custom Dimensions is a new Universal Analytics feature that allows you to bring custom business data into Google Analytics. For example, a custom dimension can be used to collect friendly page names, whether the user is logged in, or a user tier (like Gold, Platinum, or Diamond).

By using Custom Dimensions in secondary dimensions, you can now refine standard reports to obtain deeper insights.



In the report above, Direct Traffic delivers the most traffic, but these are Gold users (lower value). At the same time, Google Search delivers the third and fourth most site traffic and these are Diamond users (high value). Therefore, data shows this site should continue to invest in Google Search to attract more high value users.

The new data in secondary dimensions gives analysts a powerful new tool. We’d love to hear about any new insights in the comments.

Posted by Nick Mihailovski, Product Manager,

The New Dimensions and Metrics Explorer

Friday, November 01, 2013 | 11:29 AM

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To make it easy to navigate all the 270+ data points the Core Reporting API exposes, today we launched version 2 of the Dimensions and Metrics Explorer.



Click to see the list view.

This tool makes it easy to browse all of the dimensions and metrics, identify valid combinations, and get comprehensive definitions and descriptions.



Click to see the description view.


No wonder it’s the third most visited page on the Analytics Developer site.

Today’s update to the tool added:

  • Modes - easily see how API names map to Web View Names, and App View Names.
  • ‘Allowed in Segments’ - Quickly see which data can be used in segments.
  • Updated descriptions- See more details like data type, index ranges, UI names, deprecation status, calculations. For example, see the Custom Variables and Columns group.
  • It’s fast! - No more page loads as you browse and switch between modes.
  • Deep links - Share details of a specific dimension or metric by copying the URL of any view.
  • Automatic Updates - The Metadata API is now used to power the Dimensions and Metrics Explorer. This is a big change and means the tool will automatically update with the latest dimensions and metrics as soon as they’re released.
Visit the Dimensions and Metrics Explorer and tell us what you think.

This tool is built completely using the Metadata API. If you’re thinking about developing your own tools with this data, get started here!

Posted by Pete Frisella, Developer Advocate, Developer Relations Team

Measuring Twitter with Universal Analytics

Wednesday, October 30, 2013 | 12:24 PM

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In between rolling out new features for Google Analytics, we also like to feature how users and companies are actually using our products. Matt Stannard of 4PS Marketing details how to easily monitor Twitter and see number of tweets, active users, and hashtags for a topic using Universal Analytics. We’ve excerpted parts of his post below, read on to see the results, and don’t forget to click through to see the technical details!

How?

Step 1 - Create a new account
First, we need to create a new account, which is accomplished easily through the new look and feel of Analytics. Remember this is under Admin and then in the Account drop down. I made a new Universal Analytics account for my particular experiment - you then need to note the UA number.

Step 2 - Install PHP / MySQL
I downloaded a WAMP stack called XAMPP as I wanted to use PHP as my Twitter monitoring library. XAMPP includes Apache, PHP and MySQL. You can use any tool of your choose provided you are able to edit the code and add the necessary Measurement Protocol requests. The library I used is was from 140Dev.

Step 3 - Create Twitter Application
In order to use the PHP monitoring library you need to have a Twitter Application. You can create this by signing in at https://dev.twitter.com/. Click My Applications:


Create your application and after you've done this you will need to note the Consumer Key, Consumer Secret, Access Token, Access Token Secret. 



Step 4 - Start Monitoring
So, now we've got our Twitter application we can begin monitoring, in the 140dev package you need to modify a few files, firstly the db_config.php. You can find the code here, on the original blog post.

Results
The reporting interface of Google Analytics is actually very effective at monitoring Twitter as you are able to look in Real Time, use Dashboards, or custom reports.

The Real Time Analytics is fantastic at showing how active the things your are monitoring on Twitter is. If you just look at the Real Time overview as this screenshot shows:

(click image for full-sized version)

You can use Dashboards to report on key areas of interest and apply whatever filtering you need, the dashboard below just shows the key hashtags, users, users mentioned and urls shared: 

(click image for full-sized version)
Custom Reporting also allows us to produce charts such as what times of the day users were active:

(click image for full-sized version)

The full post can be found here.

Posted by Aditi Rajaram, Google Analytics Team

New AdSense Data in the Core Reporting API

Monday, October 28, 2013 | 11:02 AM

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Google AdSense is a free, simple way for website publishers to earn money by displaying targeted Google ads on their websites. Today, we’ve added the ability to access AdSense data from the Google Analytics Core Reporting API. The AdSense and Analytics integration allows publishers to gain richer data and insights, leading to better optimized ad space and a higher return on investment.

In the past, accessing AdSense data using the Analytics Core Reporting API has been a top feature request. We’ve now added 8 new AdSense metrics to the Analytics Core Reporting API, enabling publishers to streamline their analysis.


Answering Business Questions
You can now answer the following business questions using these API queries:

Which pages on your site contribute most to your AdSense revenue?


dimensions=ga:pagePath
&metrics=ga:adsenseCTR,ga:adsenseRevenue,ga:adsenseECPM &sort=-ga:adsenseRevenue

Which pages generate a high number of pageviews but aren't monetizing as well as other pages?
dimensions=ga:pagePath
&metrics=ga:pageviews,ga:adsenseCTR
&sort=-ga:pageviews

Which traffic sources contribute to your revenue?
dimensions=ga:sourceMedium
&metrics=ga:adsenseCTR,ga:adsenseRevenue,ga:adsenseECPM
&sort=-ga:adsenseRevenue

Reporting Automation
By accessing this data through the API, you can now automate reporting and spend more time doing analysis. You can also use the API to integrate data from multiple sites into a single dashboard, build corporate dashboards to share across the team, and use the API to integrate data into CRM tools that display AdSense Ads.

Getting Started
To learn more about the new AdSense data, take a look at our Google Analytics Dimensions and Metrics Explorer. You can also test the API with your data by building queries in the Google Analytics Query Explorer.

Busy? In that case, now’s a great time to try these Analytics API productivity tools:
  • Magic Script: A Google Spreadsheets script to automate importing Analytics data into Spreadsheets, allowing for easy data manipulation. No coding required!
  • Google Analytics superProxy: An App Engine application that reduces all the complexity of authorization.

We hope this new data will be useful, and we're looking forward to seeing what new reports developers build.

Posted by Nick Mihailovksi, Product Manager, Google Analytics API Team

An Easy Way to Upgrade to Universal Analytics

Wednesday, October 23, 2013 | 10:35 AM

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Last year we launched Universal Analytics, a new technology that allows you to measure customer interactions across platforms and devices. As we announced at the 2013 Google Analytics Summit, we’ve been working on a solution to help you upgrade your existing properties to the new infrastructure without losing any historical data.

Today, we’re announcing the Universal Analytics Upgrade Center, an easy, two-step process to upgrade your existing properties from classic Google Analytics to Universal Analytics.

Once you complete the upgrade process, you can continue to access all of your historical data, plus get all the benefits of Universal Analytics including custom dimensions and metrics, a simplified version of the tracking code, and better cross-domain and cross-device tracking support.

Getting Started

You can upgrade your classic Google Analytics properties into Universal Analytics properties by following these two steps:

Step 1: Transfer your property from Classic to Universal Analytics.
We’ve developed a new tool to transfer your properties to Universal Analytics that we will be slowly enabling in the admin section of all accounts. In the coming weeks, look for it in your property settings.



Step 2: Re-tag with a version of the Universal Analytics tracking code.
After completing Step 1, you’ll be able to upgrade your tracking code, too. Use the analytics.js JavaScript library on your websites, and Android or iOS SDK v2.x or higher for your mobile apps.

Universal Analytics Auto-Transfer

Our goal is to enable Universal Analytics for all Google Analytics properties. Soon all Google Analytics updates and new features will be built on top of the Universal Analytics infrastructure. To make sure all properties upgrade, Classic Analytics properties that don’t initiate a transfer will be auto-transferred to Universal Analytics in the coming months.

Upgrade Resources

To answer common questions, we’ve put together the Universal Analytics Upgrade Center, a comprehensive guide to the entire upgrade plan. This guide includes an overview of the process, technical references for developers, and a project timeline with phases of the overall upgrade.

We’ve also included FAQs in the Upgrade Center, but if you need more information, you can also visit the new Universal Analytics Google Group to search for answers and ask more specific questions.

We’re excited to offer you this opportunity to upgrade, and hope you take advantage of the resources we’ve created to guide you through the process. Visit the Universal Analytics Upgrade Google Group to share your comments and feedback. We’d love to hear what you have to say!

Posted By Nick Mihailovski, on behalf of the Google Analytics Team