How To Setup Enhanced Ecommerce Impressions Using Scroll Tracking

A version of this post originally appeared on Google Analytics Certified Partner InfoTrust's site.

by Nate Denlinger, Web Developer at GACP InfoTrust, LLC

One of our specialities here at InfoTrust is helping ecommerce businesses leverage their web analytics to make better data-driven marketing decisions. This typically starts with installing Google’s Universal Analytics web analytics software and utilizing all of the functionality that is offered with Enhanced Ecommerce tracking capabilities.

Enhanced Ecommerce provides you with a complete picture of what customers on your site are seeing, interacting with and purchasing.

One of the ways you track what your customers are seeing is with product impressions (whenever a user sees an image or description of your products on your website).

Normally, you track what products users see or impressions by simply adding an array of product objects to the DataLayer. These represent the products seen on the page, meaning when any page loads with product images/descriptions, data is sent to Google Analytics that a user saw those specific products. This works well.

However, there is a major issue with this method.  Sometimes you are sending impressions for products that the user never actually sees. This can happen when your page scrolls vertically and some products are off the page or “below the fold”.

For example, lets take a look at a page on Etsy.com:

Sample page on Etsy.com (click for full size)

Here are the results for the search term “Linens”. Currently, you can see sixteen products listed in the search results.  However, in the normal method of sending product impressions, a product impression would be sent for every product on the page.

So, in reality this is what we are telling Google Analytics that the user is seeing (every single product on the page):

Sample page of Etsy.com (click for full-size)

Obviously, no one's screen looks like this, but by sending all products as an impression, we are effectively saying that our customer saw all 63 products. What happens if the user never scrolls past the 16 products shown in the first screenshot?

We are greatly skewing the impressions for the products on the bottom of the page, because often times, users are not scrolling the entire length of the page (and therefore not seeing the additional products).

This could cause you to make incorrect assumptions about how well a product is selling based off of position.

The solution: Scroll-based impression tracking!

Here is how it works at a high level:

1. Instead of automatically adding all product impressions to the DataLayer, we add it to another variable just for temporary storage. Meaning, we do not send all the products loaded on a page directly to Google Analytics, but rather just identify the products that loaded on the page.
2. When the page loads, we actually see what products are visible on the page (ones “above the fold” or where the user can actually see them) and add only those products to the DataLayer for product impressions. Now we don’t send any other product impressions unless they are actually visible to the user.
3. Once the user starts to scroll, we start capturing all the products that haven’t been seen before. We continue to capture these products until the user stops scrolling for a certain amount of time.
4. We then batch all of those products together and send them to the DataLayer as product impressions. 
5. If the user starts to scroll again, we start checking again. However, we never send the same product twice on the same page. If they scroll to the bottom then back up, we don’t send the first products twice.

Using our example on the “Linen” search results, right away we would send product impressions for the first 16 products. Then, let’s say the user scrolled halfway down the page and stopped. We would then send product impressions for products 18 through 40. The user then scrolls to the bottom of the page so we would send product impressions for 41 through 63. Finally the user scrolls back to the top of the page before clicking on the first product. No more impressions would be sent as impressions for all products have already been sent.

The result: Product impressions are only sent as users actually navigate through the pages and can see the products. This is a much more accurate form of product impression tracking since it reflects actual user navigation. 

Next steps: for the technical how-to guide + code samples, please see this post on the InfoTrust site.

Boost Conversions by Infusing Google Remarketing with Marketo Real-Time Personalization

Personalization is a hot topic for today’s marketers, a group that spends nearly half of their budget attracting new prospects. But customer expectations have risen; content must be relevant to acquire new customers and move them to convert.

Some pioneering marketers are seeing better performance by using real-time personalization and remarketing simultaneously. Knowing who a customer is and what they do is a big step toward providing the hyper-relevant content that customers crave.

Join Marketo’s Mike Telem and Mike Tomita on January 15th at 10am PT/ 1pm ET as they discuss the importance of real-time personalization for marketing results. Google’s own Dan Stone will give an overview of the ways Google Analytics technology can be used to power advanced remarketing, while the Marketo team will share the ways their company uses real-time personalization and Google Analytics to generate more leads at a lower cost.

Looking for tips on how to get your organization started? Reserve your spot today!

Posted by Kelley Sternhagen, Google Analytics Marketing

Refreshing “The Customer Journey to Online Purchase” - New Insights into Marketing Channels

Last year we introduced “The Customer Journey to Online Purchase” -- a tool that helped marketers visualize the roles played by marketing channels like paid search, email and display ads in their customers' journeys.

The goal was to help marketers learn more about the customer journeys for their industries. If social makes your customers aware, and email makes them convert -- or vice versa -- you can make sure you're in both places with the right kind of message.

Today we're happy to introduce a new improved version of the Customer Journey to Online Purchase, with a few key enhancements.  We’ve refreshed the data based on millions of consumer interactions, updated the industry classifications, and we’ve split out paid search so you can see the influence of brand and generic search terms on the purchase decision.

In each industry you can now see journeys for small, medium and large companies, which can often be quite different.

Click to enlarge image

For instance, the above image shows the journey for customers of small businesses in the shopping industry. Note that organic search is very often an "assist" interaction for these customers.

Click to enlarge image

Now here's the same journey for large shopping businesses. Note that display clicks and social are strongly assisting interactions -- while display didn’t even appear for the small businesses above. For both small and large businesses, a direct website visit is most likely to be the last interaction. Across industries, the differences from small to large businesses illustrate how different marketing strategies and customer profiles may lead to different buying behavior.

And there's more! Now you can drill down into each marketing channel for a closer look at the role it plays based on its position in the purchase path. Channels that occur more frequently in the beginning of the path are more likely to help generate awareness for your product, while the end of the path is closer to the customer’s purchase decision.

Click to enlarge image

In these charts, for example, we see the different roles that different channels play in the Shopping industry. One interesting insight is that all channels -- even those traditionally thought of as “upper funnel” or “lower funnel” -- occur throughout the purchase path, but a given channel may be more common at particular stages depending on its role (and depending on the industry).

Each marketing campaign and channel may have a different impact on customers depending on when they interact with it. Using what you learn from this tool, you can help adapt your marketing messaging to be more relevant and useful for your customers.

Try the Customer Journey to Online Purchase today. And for more helpful marketing insights, check out Measure What Matters Most: our new guide chock-full of suggestions on how to measure the impact of your marketing -- across channels -- to complement what you learn from the Customer Journey tool and take action to improve your marketing.

Happy analyzing!

The Customer Journey to Online Purchase »

Posted by Sara Jablon Moked, Product Marketing Manager, Google Analytics

Analytics Pros helps Avvo Gain New Insights with Data Import

Companies use many systems to run their business. These may include multiple web advertising networks, CRM and content publishing systems, point of sale systems, inventory databases, etc. Integrating the data from these systems with Google Analytics provides a better understanding for how your customers behave on the web. 

At the 2014 Analytics Summit we announced the new Data Import. Data Import helps unify data from your different business systems, allowing you to organize your data the same way your business is organized. This will allow for more accurate analysis and bringing together previously disparate datasets into one complete picture. Using Data Import, you can upload your brand’s existing data into Google Analytics and join it with GA data for reporting, segmentation and remarketing.

By using the Data Import functionality in Google Analytics Premium and with the help of Analytics Pros, consumer legal services brand Avvo created clear, accurate data, which continues to impact decisions across their organization. While Avvo already had a successful and fast-growing business, the lack of visibility into advertising success made it hard to align key revenue opportunities with actual site usage. Read the full case study here.

“We’ve been very pleased with the results that were realized using Data Import in Google Analytics to analyze client behavior on our website. This exercise has given us better insight into valuable data that will ultimately impact how we segment the market for legal services.” 

- Sendi Widjaja, Co-Founder & CTO, Avvo, Inc.

Data Import also now supports a new Query Time mode that allows you to join your data with historical GA data. With this mode you can:

• Enhance existing, already processed GA data with imported dimensions and metrics.
• Upload calculated values after a transaction occurs, like total customer spend, last transaction date, or a loyalty score.
• Correct any errors in data you have uploaded to GA in the past.

Query Time mode is currently in whitelist release for Premium users. For more information, contact your Premium account manager. You can learn more about Premium here.

Illustration of a new Google Analytics report with data from multiple sources 

We are also introducing a new version of Cost Data import that provides more versatile support for importing historical data. Additionally, cost data  can now be uploaded directly  through the Google Analytics web interface (previously, data import  required using the GA API). Note: Users of the original cost data import  must migrate to the new version. Details can be found in the cost data migration guide.

How to get started using Data Import

For more information, read Data Import on the Google Analytics Help Center. Also check our new developer Data Import guides that will get you up and running in no time. Some features are currently not rolled out to all users. If you’d like to join the beta for full-access, sign-up here.

Posted by Nick Mihailovski, Jieyan Fan, Richard Maher, Rick Elliott and the Google Analytics Team 

Tailored ads, better results: Dynamic Remarketing powered by Google Analytics

Back in August, 2012, we launched Remarketing with Google Analytics, which enabled advertisers to create sophisticated remarketing lists using Google Analytics’ 250+ dimensions and metrics. 

Today, we’re excited to announce a deeper remarketing integration between AdWords and Google Analytics. 

A single set of tags can now power both Google Analytics and Dynamic Remarketing on the Google Display Network using the Google Merchant Center. Retailers (with other verticals in beta) will gain power and precision for their remarketing along with access to detailed product level reporting through this integration.

What is Dynamic Remarketing?

[original article here]

Every customer is unique. Dynamic remarketing takes this into account, letting you create and deliver beautiful customized ads that connect visitors with their past shopping experiences on your site. If you’re a retailer with a Google Merchant Center account, you can use dynamic remarketing to construct remarketing ads on the fly with the products and messages that are predicted to perform best based on visitors’ past actions on your site.

For example: Customers who browsed the winter tires category on an advertiser’s website might see an ad that includes the exact products they’ve already viewed, in addition to related products from the company’s catalog. In the Tirendo example above, the ad also shows details of recently viewed tires, including the prices.

Early users are seeing great results

"We've been thrilled with the performance of Dynamic Remarketing with Google Analytics and Conversion Optimizer, which has so far driven a 203% increase in conversions and 100% increase in conversion rates vs. our display average. Combined with Google Analytics' powerful reporting on these same metrics, we've been able to derive actionable insights which we've put to good use throughout our other campaigns."

- Janina Rix, SEA Manager, tirendo.de

To begin using Dynamic Remarketing

1. Create one or more remarketing lists using Google Analytics
2. Update your tags to track Product ID, Cart Value, and Page Type as custom variables (or dimensions)
3. Enable the Dynamic Link in Admin > Property > Dynamic Attributes. This will let Google Analytics send attributes to your AdWords account. [more below]
4. Create a Dynamic Remarketing Display campaign in AdWords

Here’s a quick visual guide to the new interface.

Step 1: Configure account details

Step 2: Make sure the attribute names match your custom variables

Step 3: Click ‘Save’ and finish by creating your first Dynamic Remarketing campaign in AdWords

Want more help? Download a remarketing starter pack from the solutions gallery. 

Please stay tuned for more remarketing-related updates in the near future!

Happy Analyzing, Dan Stone and Lan Huang on behalf of the Google Analytics Team