Archive for the ‘Google Analytics’ Category
Google Analytics at Google I/O recap
It was a busy week in San Francisco at Google I/O. We unveiled new products and features, such as deeper mobile app analytics integration with Google Play and Google Tag Manager for mobile apps. If you missed the earlier announcement, you can learn about our new features here.
We also gave several great presentations on some of our new features. Our Developer Relations team also showed off some tools for multi-screen measurement here, so take a look if you didn’t manage to catch our livestream this past Thursday.
We also presented on dynamically configuring mobile applications using Google Tag Manager for mobile apps, and talked about Google Analytics and AdSense data analysis in BigQuery.
It was great to see so many GA users and developers– we can’t wait to see everyone next year at I/O!
Posted by Aditi Rajaram, Google Analytics team
I/O Announcement: Google Analytics Premium data in BigQuery is coming soon
- Leverage Google’s massive computing power to get business insights from big data in seconds rather than hours.
- Analyze massive amounts of data in the cloud with no up-front investments (hardware provisioning or software licensing investments).
- Share and collaborate quickly and securely using Access Control Lists.
- Store as much as you want, paying only for what you use.
- Protect your data with multiple layers of security from Google.
- Analyzing visitor behavior across very large date ranges. Answer the question: “From 2010 to 2013, which sections of my site had the most volatility in daily traffic volumes?”
- Joining against data from other sources. Make detailed, custom analyses, such as: “I have a database that contains all the metadata about each article posted on my site and would like to see the bounce rate, conversion rate and new visitors generated by author and topic.”
- Understanding complex queries. Answer the question: “Of the visitors to my site that used a voucher code, how many originally discovered my brand from a voucher code site and how many left the checkout process and returned within 10 minutes with a voucher code? Which codes were used in each case?”
- Integrating with Data Warehouses. Make detailed, custom analyses, such as: “On a weekly basis, for each of my logged in customers, I want to see the top 5 products that they viewed but did not buy and add that information into their record in our CRM.”
The Future of Measurement Starts at I/O: What’s New and on the Horizon for Analytics
The data sources you’ll be able to see include:
Google Analytics at Google I/O
We’ve been working hard getting ready for Google I/O! We’re livestreaming our presentation on how to optimize web and mobile apps across devices using Google Analytics on Thursday, May 16 at 1:40pm PT and we’d like to invite everyone to join us.
We recently launched Universal Analytics, a new way to measure user interactions across any device / platform / environment. By measuring this data, developers can better optimize their applications. In this session we’ll discuss how to measure user-interaction from any device as well as demo new reports and best practices to optimize both web and mobile apps.
For those of you who are going to be at I/O, please stop by the Ads sandbox and say hi to the Analytics team! We’ll be around to answer questions, and we may even have some pretty cool Analytics gear to give out. Be sure to check out all of our Analytics sessions. You can find the full schedule here.
Posted by Aditi Rajaram, Google Analytics team
New Google Analytics Filter Fields
- Is a mobile device
- Is a tablet
- Mobile brand name
- Mobile model name
- Mobile marketing name
- Mobile pointing method
- Mobile has QWERTY keyboard?
- Mobile is NFC supported?
- Mobile has cellular radio?
- Mobile has wifi?
- Social network
- Social action
- Social action target
- Hit type: (page, social, transaction, etc.)
- Internal search term
- Internal search type
- Browser size
- IP version
- Local currency code
Ariat Uses Data to Improve Customer Experience and Drive Results

See Your Conversions In Real-Time
Display Remarketing from Search Ads Out of Beta
Back in October, we announced the beta release of display remarketing from search ads, which allows advertisers to use insights from paid search clicks to remarket to audiences across ad exchanges via DoubleClick Bid Manager, or the Google Display Network (GDN) — all with a seamless, tagless workflow.
Display Remarketing from Search Ads Out of Beta
Back in October, we announced the beta release of display remarketing from search ads, which allows advertisers to use insights from paid search clicks to remarket to audiences across ad exchanges via DoubleClick Bid Manager, or the Google Display Network (GDN) — all with a seamless, tagless workflow.
Introducing “The Customer Journey to Online Purchase" — interactive insights on multi-channel marketing
That’s the philosophy behind Google Analytics tools like Multi-Channel Funnels and Attribution Modeling. Tens of thousands of our largest advertisers are gaining valuable insights from Multi-Channel Funnels every month, and we’ve collected these insights using aggregate statistics to develop a benchmarking tool — The Customer Journey to Online Purchase. This interactive tool lets you explore typical online buying behavior and see how different marketing interactions affect business success.

The tool draws on Ecommerce and Multi-Channel Funnels data from over 36,000 Google Analytics clients that authorized sharing, including millions of purchases across 11 industries in 7 countries. Purchase paths in this tool are each based on interactions with a single ecommerce advertiser.
You’ll find benchmark data for:
- how different marketing channels (such as display, search, email, and your own website) help move users towards purchases. For example, some marketing channels play an “assist” role during the earlier stages of the marketing funnel, whereas some play a “last interaction” role just before a sale.
- how long it takes for customers to make a purchase online (from the first time they interact with your marketing to the moment they actually buy something), and how the length of this journey affects average order values.
Channel Roles in the Customer Journey
The data shows that every industry is different — the path to purchase for hotel rooms in Japan is not necessarily the same as the path as for an online supermarket in Canada.
A few findings stand out, in particular:
- As you might expect, customers typically click on display ads early in their purchase journeys, but in some industries, such as US travel and auto, display clicks tend to occur closer to the purchase decision.
- Across industries and countries, paid search has a fairly even assist-to-last interaction ratio, implying that this channel can act both in the earlier and later stages of the customer journey.
- Once you’ve explored the benchmarks, look deeper into your own marketing data with the Multi-Channel Funnel reports, and consider defining your channels and campaigns to separate out categories that are specific to your business needs.
Purchase values and the length of the journey
We also see interesting patterns emerge when examining the length of the customer journey. While the majority of purchases take place within a single day or a single step (i.e., a single interaction with one marketing channel), longer paths tend to correlate with higher average order values.
For example,
- in US Tech, online purchases that take more than 28 days are worth about 3.5 times more than purchases that occur immediately. And while 61% of tech purchases take place on that first day, only 53% of revenue comes from single-day purchases.
- in Consumer Packaged Goods (CPG), on the other hand, most purchases (82%) are quick, likely because these are smaller and simpler purchases that don’t require much research.
- in Edu / Gov, 41% of revenue comes from multi-day purchases, but 60% of revenue comes from multi-step purchases — suggesting that even when customers make decisions in a relatively short time period, they often have multiple marketing interactions before purchasing.
- In Multi-Channel Funnels or the Attribution Modeling Tool, you can adjust the lookback window to reflect the typical length of the purchase path in your industry. For example, if your business tends to have shorter paths, you can zoom in on paths that take 5 days or less:

Putting the benchmarks to work
For marketers, it’s always a crucial challenge to design campaigns that deliver the right message at the right moment in a customer’s journey to purchase. We hope these benchmarks will provide useful insights about the journey and help you put your business into context. In particular, take a look at the final infographic, the “Benchmarks Dashboard,” to get a quick overview of your industry. Then, when you view your own data in the Multi-Channel Funnels reports in Google Analytics, you’ll gain a better understanding of where different channels impact your conversions and what your typical path looks like, so you can adjust your budgeting and marketing programs accordingly.
Try The Customer Journey to Online Purchase today on Google’s new Think Insights website.
Happy analyzing!
Posted by Paul Muret, Director of Engineering, Google Analytics









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