Using a permanent URL to share Custom Attribution Models & Custom Channel Groupings

The need to customize and fine-tune your marketing measurement solutions becomes a key discriminator in unlocking additional value which might have been missed when applying out-of-the-box views on your data. For this reason, the Multi-Channel Funnel Analysis within Google Analytics Attribution provides the ability to configure content based channel groupings, as well as customized attribution models. This allows you to better reflect how partial credit is assigned to the marketing efforts driving your conversions. Having the ability to develop these customized assets is great, and now you are able to easily share them with your organization, your customers, or your audience. Here is how sharing a custom channel grouping, or custom attribution model works: 

Step 1 - Build a Custom Attribution Model
Building a custom model is easy. Just go to the Model Comparison Tool report in the Attribution Section of Conversions. In the model picker you can select ‘Create new custom model’, which opens the dialog to specify rules which can better reflect the value of marketing serving your specific business model. As an example, we can develop a model to value impressions preceding a site visit higher within a 24 hour time window. We also set the relevant lookback window to 60 days, as we know our most valuable users have longer decision and decide cycles:

Click image for full-sized version
Ensure you opt-in the Impression Integration, enabling Google Display Network Impressions and Rich-Media interactions to be automatically added to your path data through the AdWords linking. Don’t forget to also check out the recorded webinar from Bill Kee, Product Management Lead for Attribution, providing more details on how to create a custom model.

Step 2 - Access the Model in Personal Tools & Assets Section
In the admin section you can now look at your personal tools & assets. The newly created model will show up in the ‘Attribution Models’ section. You can find custom channel groupings you created under Channel Groupings.

The table shows all assets available, and a drop-down allows you to ‘share’ these assets through a link.

Step 3 - Share the Link - Done!
From the drop-down Actions menu select ‘Share’, and a permanent link to the configuration of this object is generated. This link will point to the configuration of the shared asset, allowing anyone with a GA implementation and the link to make a copy of the asset config, and save it into their instance of GA. You maintain complete control over who you share your assets with. 

Include the link to your brand-new attribution model asset in an email, IM message, or even a Blog Post, such as this one.

Happy Customizing!

Posted by Stefan F. Schnabl, Product Manager, Google Analytics

Evaluate Marketing Spend Efficiency with our Conversion and Attribution Tools

You invest a lot to create your marketing campaigns, and it’s important to see how your spend impacts results. In addition to comparing the conversion performance of your marketing activities, you can now view your imported AdWords cost data directly in the Google Analytics Attribution Model Comparison Tool. By evaluating your AdWords cost data under various lenses offered through Attribution, you’ll get further insight into the effectiveness of your marketing spend. We will gradually roll out this feature out to all of Google Analytics.

Extended Set of conversion data
As previously announced, to make the analysis of your conversion path data even more meaningful, we extended the lookback window within Multi-Channel Funnels to 90 days. This functionality is now available through the standard lookback window selector. Please see our help center for more details.

Explore different attribution models to see revised performance figures
Cost Per Acquisition (CPA) is one of the strongest indicators for marketers. Our Model Comparison Tool now makes this important metric available to advertisers in Google Analytics. In addition to CPA, we also allow users to look at the Return On Ad Spend (ROAS) figure, which compares the value or revenue driven by conversions under different attribution models.

As described in the Customer Journey to Online Purchase, marketing channels influence the customer at multiple touchpoints on the path to conversion. Display touchpoints, in aggregate, appear 3.1 times more often in the upper funnel (awareness, consideration, intent phase) than in the lower part of the funnel (decision phase).*

Selecting Conversion Value & ROAS from the selector in the Attribution Model Comparison Tool allows you to contrast the value driven by your spend. Comparing the performance of a channel by looking at two different attribution models can uncover hidden performance of this channel. In the above example, the Display channel drives 20% more value under a First Interaction model.

Interpret your analysis
The direction of the arrow in the % change column indicates the orientation of the shift. Please note that it matters which model is the reference model, and which model is the comparison model. A positive shift away from the valuation of the reference model will be visualized with an upwards arrow, a negative shift with a downwards arrow. The color of the arrows is used to indicate whether the alternative valuation of the comparison model has caused a favorable shift. Green indicates a significant shift in favor of the comparison model, and red indicates a significant shift in favor of the reference model. A gray dot symbol indicates that there is no relevant change between the reference and comparison model.

Get started today by linking your account to an AdWords cost data source. The more complete your cost data is for a given profile, the more stable and accurate are the insights you can gain from the analysis. Consider using the Cost Data Import service provided through the GA API to add cost data beyond AdWords.

*Source: Google Analytics, Q4 2012. N = US: 130M conversions (12K profiles)

Full Credit Measurement: Attribution with Google Analytics

As we’ve discussed in many previous posts, the customer journey is evolving — most consumers will interact with many different marketing channels before a sale or conversion. And marketers are recognizing this shift in consumer behavior. Instead of “last click” measurement, a strategy that only gives credit to the final interaction, they’re turning to full credit measurement. To help you make sense of the full customer journey, we’ve been focused on bringing you the very best full credit measurement tools in Google Analytics.

Nearly two years ago, we announced our first Google Analytics attribution product, Multi-Channel Funnels. With its ability to measure customers’ different paths to conversion, it quickly became one of our most popular reports for advertisers and publishers alike. We’ve seen great results from our users, including online travel agency On the Beach, who used data from the Multi-Channel Funnels reports and AdWords Search Funnels to explore and adjust their strategy for generic keywords. These attribution adjustments helped On the Beach to drive a 25% uplift in ROI — see the full case study here.

Beyond Multi-Channel Funnels, we also wanted to provide our users with an advanced platform for testing entirely new, more robust attribution strategies, including the ability to test alternative models or understand how metrics, such as site engagement, could impact their existing investments. So last year we released our Attribution Modeling feature — the Model Comparison Tool.

After several months of testing on a public whitelist, we're now in the process of rolling out the Attribution Model Comparison Tool to make it generally available to Google Analytics users without whitelist.  To reflect the importance of attribution, we also created a new “Attribution” section under the “Conversions” reports, so the tool will be found there.

Be sure to check out a previously recorded webinar with Product Manager Bill Kee for a complete walkthrough of the Attribution Model Comparison Tool, or view our multi-part attribution webinar series covering our entire selection of full-credit measurement tools.

See the full Impact of Unclicked Display and Video Ad Impressions using Google Analytics

Every customer journey is different — a customer may see your display or video ads, receive an email, and then click through to your site from a search ad or organic search listing. Often, viewing display ads can attract your clients’ interest in your product and brand even if no click occurs. Traditionally, measurement technology separated out impressions or “view throughs” from clicks, but this separation missed out on valuable data on the impact of display advertising.

Thanks to our integration with the Google Display Network (GDN), Google Analytics can now break down the separation between clicks and impressions and give a more complete view of the customer journey. When a user views display ads on the GDN, or video ads on YouTube, and later visits your website and converts, these interactions with your brand can now be captured in Google Analytics Multi-Channel Funnels reporting.

GDN Impression Reporting is now available through limited whitelist. You can sign-up through this form to participate. Please note that we cannot guarantee access, but we will do our best to provide this feature to as many users as possible. Please also note that this data will only surface in the Multi-channel Funnels reports in Google Analytics. For more information on how to enable the feature in GA please see our help center article.

Read on below for more tips on how to make the most of this new feature.

How does Display fit on the conversion path?
By enabling GDN Impression Reporting in Google Analytics, you can learn how your display impressions assist your conversions.

In the Multi-Channel Funnels Overview Report you will see two additional conversion metrics. Impression Assisted Conversions shows how many of your conversion paths were touched by a display impression. Rich Media Assisted Conversions shows how many of your conversions had a rich media interaction on the path to conversion. Rich media interactions are user interaction with YouTube or rich media ad formats, such as ad expansion, video control (such as play, pause, and resume), or switching a video ad to full screen.

With the new Interaction Type selector you can now immediately filter your reports based how your users interacted with your marketing.

  • Select Impression to see conversion paths from customers who saw your GDN display ads but did not click on them.
  • Add Direct to the mix, to see who saw an ad and then visited your site directly to convert on a relevant transaction or Goal.
  • If you want to focus on Rich Media interactions, you can select this interaction type to see how your users convert after interacting with your rich media and YouTube ads.

How do I quantify the impact of display on the conversion path?
In the Multi-Channel Funnels Top Conversion Path report you can see two new path elements, which indicate the presence of a display interaction. The “eye” symbol indicates a pure display impression from a non-interactive display image. This means a user has been exposed to your display ad on the journey to conversion, without clicking on it. The “movie” symbol indicates a user has interacted with one of your Rich Media ads, such as a YouTube video ad.

Now you can see how many conversion paths, and how much associated value, has been driven through paths which benefited from a display impression or rich media interactions. To better quantify your brand targeted display efforts, consider breaking out these campaigns using custom channel grouping.

Assigning partial credit to valuable display interaction touchpoints
You can use the custom model builder from the Attribution Modeling tool to assign partial credit to these display events. Consider giving these events on the user’s conversion path more credit, and compare this against your baseline model.

We also added a new set of dimensions to help you define valuable custom segments for your analysis. Want to see how many users are watching your TrueView video ads fully? Just create a custom segment using one of our new dimensions, TrueView. The full list of new dimensions is:
  • Above the Fold: This dimension uses the Google Above the Fold measurement solution. The value is “Yes” if the ad was in the visible area of the screen when the page was loaded.
  • Video Played Percent: The value can be “>=25%”, “>=50%”, “>=75%”, and “100%”, allowing you to see how much of a video ad was watched.
  • TrueView: If a user has watched more than 30 seconds of an ad, or watched the ad completely, this will have a value of “Yes.” This is a payable event.
Enabling GDN Impression Reporting in Google Analytics
Once we have whitelisted your account, please ensure you have successfully linked your AdWords account to your Google Analytics account. Linking accounts takes just a few moments. Under ‘Data Sources’ > ‘AdWords’ you can then see an entry for each linked AdWords account. In the row there is a toggle switch named ‘GDN Impression Reports’, which turns the display impression data from the Google Display Network On and Off. Data is recorded from the time the switch is turned On.

We hope these new tools will help you understand the full impact of your display campaigns through Multi-Channel Funnels and Attribution. Sign up today for GDN Impression Reporting in Google Analytics.

Introducing “The Customer Journey to Online Purchase" — interactive insights on multi-channel marketing

Savvy marketers understand that you don’t always seal the deal with a single message, image, or advertisement. A user may see a display ad, click on a link from a friend, or do a search before buying something from your website — and all of these interactions can play a role in the final sale. It’s important to understand the entire customer journey so you can measure all of the elements that contribute to your campaigns, attribute the right value to them, and adjust your marketing budgets where appropriate.

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.

Advanced tip:
  • 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.

Advanced tip:
  • 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! finds that traditional conversion tracking significantly undervalues non-brand search

The following post originally appeared on the Inside AdWords Blog.

Understanding the true impact of advertising
Advertisers have a fundamental need to understand the effectiveness of their advertising. Unfortunately, determining the true impact of advertising on consumer behavior is deceptively difficult. This difficulty in measurement is especially applicable to advertising on non-brand (i.e. generic) search terms, where ROI may be driven indirectly over multiple interactions that include downstream brand search activities. Advertising effectiveness is often estimated using standard tracking processes that rely upon ‘Last Click’ attribution. However, ‘Last Click’ based tracking can significantly underestimate the true value of non-brand search advertising. This fact was recently demonstrated by, a leading travel brand, using a randomized experiment - the most rigorous method of measurement.

Experimental Approach recently conducted an online geo-experiment to measure the effectiveness of their non-brand search advertising on Google AdWords.  The study included offline and online conversions.  The analysis used a mathematical model to account for seasonality and city-level differences in sales.  Cities were randomly assigned to either a test or a control group. The test group received non-brand search advertising during the 12 week test period, while the control group did not receive such advertising during the same period. The benefit of this approach is that it allows statements to be made regarding the causal relationship between non-brand search advertising and the volume of conversions - the real impact of the marketing spend.

Download the full case study here.

The results of the experiment indicate that the overall effectiveness of the non-brand search advertising is 43% greater1 than the estimate generated by’s standard online tracking system.

The true impact of the non-brand search advertising is significantly larger than the ‘Last Click’ estimate because it accounts for
  • upper funnel changes in user behavior that are not visible to a ‘Last Click’ tracking system, and
  • the impact of non-brand search on sales from online and offline channels.
This improved understanding of the true value of non-brand search advertising has given the opportunity to revise their marketing strategy and make better budgeting decisions.

How can you benefit?
As proven by this study, ‘Last Click’ measurement can significantly understate the true effectiveness of search advertising. Advertisers should look to assess the performance of non-brand terms using additional metrics beyond ‘Last Click’ conversions. For example, advertisers should review the new first click conversions and assist metrics available in AdWords and Google Analytics. Ideally, advertisers will design and carry out experiments of their own to understand how non-brand search works to drive sales.

Read more about AdWords Search Funnels
Read more about Google Analytics Multi-Channel Funnels

-- Anish Acharya, Industry Analyst, Google; Stefan F. Schnabl, Product Manager, Google; Gabriel Hughes, Head of Attribution, Google; and Jon Vaver, Senior Quantitative Analyst, Google contributed to this report.

1 This result has a 95% Bayesian confidence interval of [1.17, 1.66].

Posted by Sara Jablon Moked, Google Analytics Team

Attribution Webinar Recap: Making Attribution work for Your Business

On Friday, November 2, following our public whitelist of the Attribution Modeling Tool, Bill Kee (Product Manager, Google Analytics) and Neil Hoyne (Global Program Manager, Attribution), came together to lead the 5th and final webinar in our series on marketing attribution. They identified opportunities in the customer’s journey from introduction to conversion, including:
  • Google’s recommendations for how companies should structure their own attribution programs.
  • Basics on the methodology and configuration of the Attribution Modeling Tool, and how to create custom models that can improve your business’ performance.
  • Identifying specific opportunities in attribution from brand-to-generic trends to position-based weighting.
If you weren’t able to attend the live webinar, Attribution for Digital Success, you can view a recording here:

You can also catch up with our entire attribution webinar series, which included:
  1. an overview of our research on how the industry approaches attribution (watch here),
  2. the foundational steps for attribution using Google’s tools (watch here),
  3. intra-channel attribution with Search Funnels in Google AdWords (watch here),
  4. cross-channel measurement with Multi-Channel Funnels (watch here),
  5. and finally, our most recent webinar on strategies for the Attribution Modeling Tool (watch here).
We’d like to thank all of our users who have joined us for some or all of these attribution webinars. You have provided invaluable questions, ideas and feedback to help shape the next generation of our product. Some of these requests have already been addressed, including the public availability of the Attribution Modeling Tool (now available via whitelist), longer lookback windows, and cost-data import, and others are sure to come in the future. Stay tuned and stay in touch!

As has been our tradition throughout this webinar series, we’d also like to provide responses to some of the most common and most interesting questions we received during the webinar.


What business variables influence the decision on an Attribution Model?
Any factor that could influence your business or marketing efforts, including weather, pricing and competitive behavior, could have an impact your attribution decisions. Still, we suggest that advertisers focus on those efforts that could have the largest effect on their business, usually by conversion volume as well as those that they can more easily control (paid search vs. organic search or direct traffic) for the basis of experimentation.

How is the social engagement metric calculated?
Social engagement is measured any time a user clicks from a known social network, such as Facebook, Twitter, Google+ or over 400 others, to the advertiser’s website. At this time, no interactions that occur within the networks themselves, such as a “like” are presented within the Attribution Modeling Tool.

Could you further elaborate on how conversion paths are presented when a user converts multiple times within the 30-day lookback window?
Each conversion has a unique path, which includes all of the interactions the converting user had in the 30 days leading up to the conversion. When the same user converts multiple times, the conversions are treated separately. For example, is a user clicked through from Display, and completed conversion #1, this conversion would have a path length of one from the channel “Display.” If the same user subsequently clicked through from Paid Search, and completed conversion #2, assuming the original Display interaction occurred within 30 days prior to conversion #2, a second conversion path would be recorded with a path length of two: Display, followed by Paid Search.

If we submitted our account to the Attribution Modeling Tool whitelist, how long will it take until we begin to see this feature available in our Google Analytics account?
We understand how important attribution is to your business, and are incredibly grateful for all of the interest that has been shown in the modeling tool since the announcement of the public whitelist. As such, we are working as quickly as we can to add new customers to the tool and will continue to post any available updates directly on the signup form. Once your account has been whitelisted, you’ll see the Attribution Modeling Tool listed within the Multi-Channel Funnels reports, under Conversions.

Could you provide step-by-step details on how to build the models Bill described during the webinar?
We created two custom models to show examples of the types of weighting you can apply using the model builder. The first model, called “Upper Funnel” emphasizes interactions earlier in the path, from channels that are focused on introducing and informing customers, and discounts channels that may be more navigational, like branded search. The second model, called “Lower Funnel” gives more weight to marketing interactions at the end of the conversion path, but does not solely give credit to the last interaction, and excludes direct interactions that are last in the path, giving credit instead to other marketing touch points toward the end. By comparing both models to the Last Interaction model, you’re able to see the contrasts in credit given to channels, and see whether marketing efforts play the roles you think they do or not.

Here are the rules for the “Upper Funnel” model.

Upper Funnel Model, step 1: Click on the model selector then “create new custom model” to open the custom model builder, and enter details as pictured (click to enlarge the image):

Upper Funnel Model, step 2: Turn on “apply custom credit rules” in the custom model builder, then enter model details as pictured (click to enlarge the image):

And here are rules for the "Lower Funnel" model.

Lower Funnel Model, step 1: Click on the model selector then “create new custom model” to open the custom model builder, and enter details as pictured (click to enlarge the image):

Lower Funnel Model, step 2: Turn on “apply custom credit rules” in the custom model builder, then enter model details as pictured (click to enlarge the image):

Marketing attribution is a challenging yet worthwhile pursuit. Our hope is that this webinar series will help you as you begin (or continue) your attribution journey. For more information on the Attribution Modeling Tool, please visit our website and the Google Analytics help center.

Happy analyzing!

Sara Jablon Moked, Product Marketing Manager for Conversion and Attribution

Attribution Modeling for Digital Success: Webinar this Friday + Public Whitelist

Last year, we launched Multi-Channel Funnels, giving marketers insight into how customers interact with multiple touch points prior to conversion. Since then, we’ve begun to see a great shift in the industry, as marketers move away from simple, last click attribution, toward a more holistic picture of how digital marketing channels work together to drive conversions.

Earlier this year, in Google Analytics Premium, we added the Attribution Modeling Tool, which lets marketers build models that distribute the credit for conversions across channels and touchpoints, and quickly compare multiple models side by side. We’ve received great feedback about how the tool provides fast and easy insight into channel value.

Yesterday at the Google Analytics Summit, we announced wider availability for the Attribution Modeling Tool through a public whitelist. We also shared our plans for a new 90-day lookback window, better sampling controls, and the ability to import cost data for use in attribution models.  To help you get started, this Friday we’ll host a webinar, Attribution Modeling for Digital Success, giving an overview of the tool. We’ll cover the opportunities and challenges of attribution modeling, how to interpret and build models, and ways to take action on the results.

Webinar: Attribution Modeling for Digital Success
Day: Friday, November 2
Time: 10am PST / 1pm EST / 6pm GMT
Webinar sign-up:
Whitelist sign-up:

A recording of the webinar will be available on the blog and YouTube soon afterward. You can also check out our attribution playbook and product fact sheet for more background -- and you can view earlier webinars in our Attribution webinar series.

Hope to see you at the webinar, and happy modeling!

How to Prove the Value of Content Marketing with Multi-Channel Funnels

The following is a guest post contributed by Josh Braaten, Senior Online Marketing Manager at Rasmussen College, Google Analytics enthusiast, and avid content scientist.

Conversion is rarely straightforward, especially for products or services with lengthy or complicated buying cycles. Working for a college has made it clear to me that every consumer is different, and so are their research needs as they navigate their unique buying process. 

It takes a holistic content strategy to address the extensive information needs of potential students, and rarely do blogs and other types of content marketing get the credit they deserve for the role they play in influencing conversion.

Luckily, Google Analytics Multi-Channel Funnels provides marketers with amazing new ways to see how users interact with web content on their path to conversion and to prove the value of content marketing.

Introducing Google Analytics Multi-Content Funnels
Consumers begin any major investment in the awareness/discovery phase, are triggered into a search/consideration phase, and finally end up at their buy/close phase when they take the conversion action. Imagine how your content strategy could perform if you understood how consumers interact with your website content as they navigate their investment decision. 

That’s where the idea of Multi-Content Funnels started. To be clear, Multi-Content Funnels is not a new Google Analytics feature, but rather a specific application of the existing Multi-Channel Funnels reporting features that illustrates the direct and indirect effects of your website content instead of your marketing channels.

Multi-Channel Funnels launched a little over a year ago as a way to help show how users interact with your marketing efforts over multiple visits. By default, these reports are configured to report the relationships between marketing channels (e.g., paid search, social media, email), but we’re going to modify them to demonstrate the value of content marketing.

The key to this type of analysis is being able to use the Landing Page URL data attribute when you create Channel Groupings and Conversion Segments within a Multi-Channel Funnel report. When I first wrote on their inbound marketing benefits, Multi-Channel Funnels didn’t support this deep dive into your website content because they didn’t include landing page in the source data.

Turns out the Google Analytics team had it on the road map and added it to Multi-Channel Funnel reports within the last few months. Content marketers, get ready to geek out with these content-based applications of the Google Analytics Multi-Channel Funnel reports.

Building Content-Based Channel Groupings
The first major application of Multi-Channel Funnels for content marketing is to create Channel Groupings based on your content, which will demonstrate the most common content paths users take to conversion over the course of multiple visits.

Start off by creating a new Channel Grouping within the Top Conversion Paths report. You’ll want to group the major content sections of your website together into channels.

For example, here I’ve created this Channel Grouping that corresponds to the Degrees Catalog section of our website that includes any landing page URL containing “/degrees.”

Creating a Channel Grouping in Multi-Channel Funnels:

I also included channels that correspond to each of the major content sections of the website as I built out this content-based Channel Grouping. This is what the content-based Channel Groupings of a college website looked like when I was done with them:

Content-Based Channel Grouping:
Your own content-based Channel Groupings will likely be different for every website, but each should include major product directories or service listings, blogs, sections that answer specific questions or solve specific problems, whitepapers, ebooks, etc.

Top Content Conversion Paths
Once the content-based Channel Groupings are set up, we’re able to access the Top Conversion Paths report, which instantly becomes the content marketer’s best friend because it shows how many visits it takes before visitors convert, and how they start their website experiences for each visit.

You can use the Channel Groupings that correspond to specific content sections as with the screenshot above, or you can apply even broader Channel Groupings to provide a high-level view of the most common content paths towards conversion by marketing intent, consumer action, or both. 

Channel Groupings Based on Buying Cycle Path
Creating Channel Groupings based on marketing intent and the consumer buying cycle requires a deep understanding of how consumer interact with your website. These Channel Groupings can be created by combining multiple sections of the website when constructing each Channel Grouping, depending on which phase of the buying process they facilitate:

Pairing this information with traffic and conversion data makes it clear where to focus resources for new types of content, content edits, and expansion of existing website content, as well as demonstrates which parts of our content marketing strategy are driving results.

(Fascinating side note: Looking beyond the most popular conversion paths, some degree seekers’ research processes can see them returning to the website 50 times or more before they are confident in their conversion decision. As a student of web analytics, the next question is whether this conversion path is long because it should be, or is it fraught with unnecessary abandonment that can be overcome with improvements to the content?)

A Long Conversion Path:

Determining the Value of Specific Content with Conversion Segments
Channel Groupings are half the fun because they can only help to organize and present data. To determine the value of specific types of content, we need to create custom Conversion Segments to pair with Channel Groupings

Content-Based Conversion Segments in Multi-Channel Funnels:

Custom Conversion Segments are easy to create and work just like any other segments in Google Analytics, however, these also include the ability to segment-based interaction: First interaction, last interaction, any interaction, and assisting interaction.

Custom Conversion Segment Setup:

This segment captures conversions where the last visit on the conversion path landed on the blog. Most of Google Analytics conversion reports are based on the last interaction, but this segment allows you to explicitly specify between first interaction, last interaction, any interaction, and assisting interactions.

As a content marketer, discovering some blogs assist 150 percent more conversions than they produce directly was a powerful revelation, one that was made possible by content-based Channel Groupings and Conversion Segments applied to Google Analytics Multi-Channel Funnels.

The Many Uses of Multi-Channel Funnels for Inbound Marketing
Understanding how consumers interact with your website content is the first step in providing them with the best experience possible – the primary goal of every modern SEO and content marketer. Those who understand and execute content strategy with this knowledge in mind continue to drive highly efficient campaigns.

The Google Analytics Multi-Channel Funnels with content-based segments and groupings, or Multi-Content Funnels as I like to call them, provides you with several new ways to leverage these amazing reports, boost your content marketing efforts, and better serve your current and potential consumers.

How have you used Multi-Channel Funnels in your content strategy?

(Note: Some screenshots were edited to remove site details.)

Multi-Channel Funnels: Webinar, Checklist, Tips & Tricks

Understanding the customer journey, from consideration to conversion, is no easy feat. But with tools like Multi-Channel Funnels (MCF) in Google Analytics, we’re working to make it easier to uncover new insights and opportunities to improve marketing performance. As Google’s Global Program Manager for Attribution, I recently led a webinar that highlighted opportunities to:
  • Improve keyword coverage to reach customers at all stages of the conversion path.
  • Identify those channels that directly contribute to the growth of your business.
  • Learn how metrics like average order value can be influenced by early-stage marketing.
This webinar is the 4th in Google’s ongoing series on attribution and is designed for newcomers and seasoned veterans of Google Analytics alike. If you’re just starting with the tool, we do recommend that you take a look at our MCF Implementation Checklist below as well as our earlier webinar, Building Blocks of Digital Attribution to ensure you are capturing all the data to maximize these analyses. And please read on for answers to some interesting questions that came up during the webinar.


What do I need to use Multi-Channel Funnels properly?

MCF Implementation Checklist:
  1. Install Google Analytics! Make sure that all of your webpages are tagged, and if you happen to have more than one website ( and yoursite.2com) or multiple domains ( and that you are set up to use Multi-Domain tracking. This last step will ensure that you are tracking all interactions across your sites into a single customer path.
  2. Set up E-Commerce Tracking or Goals. MCF needs to know what action represents the very end of the customer path - the conversion. The conversion may be a sale, or it could be another action that’s valuable for your business, like filling out a lead form or downloading a brochure. For businesses selling products online, you can measure conversions (sales) through e-commerce tracking. If you’re measuring visitors that take a specific action, such as completing a form, setting up goals will suffice. 
  3. Get your tags in order. For AdWords customers, make sure that your advertising account is linked to your Google Analytics profile and that auto-tagging is enabled. For other channels, such as e-mail or advertising run on other networks, our custom URL builder will help you build the tags necessary for each campaign. If you’re new, be sure to learn more about channels and channel grouping.
  4. Start using the MCF reports. Once you’ve followed the steps above, you can find the Multi-Channel Funnels reports in the Standard Reporting tab of Google Analytics: click on “Conversions” at the left-hand side of the user interface, then click “Multi-Channel Funnels.”

Is it possible to integrate the data from Multi-Channel Funnels directly into our own systems?
Absolutely. Not only are all of these data points available for export from the Google Analytics interface in commonly-used formats, we also just announced the release of the Multi-Channel Funnels API so that developers can tap directly into this incredibly powerful data source. See our recent blog post for more information.

How do we ensure we are tracking all our channels in a way that is optimal for these reports?
By default, all inbound clicks that are part of a conversion path are captured by Multi-Channel Funnels. The default channel groupings that we provide then make a series of fairly reasonable assumptions to group traffic into their respective buckets. As a user, you have two approaches to ensure that all traffic is ending up in the right place:
  1. The first option is tag all of your marketing activities in a way that matches the logic of the default channel groupings. You can find the rules behind the groups in this help center article. There is also a simple URL builder so that you can append the proper tags to your other campaigns.
  2. The second option is to create channel groupings that match the way you are currently naming and tagging your campaigns. This approach tends to be favored by those companies that want to utilize all of their historical data in MCF right away, or have technical limitations preventing them from changing the actual campaign tags. Implementation details for this approach can be found on the Analytics Help section, in this article on channel groupings.

Does MCF have to be a true purchase or it will it work for a Business-to-business company looking for qualified leads?
Companies that are pursuing leads tend to have much shorter conversion paths than those that are tracking purchases. It's not entirely uncommon to see lower assist / last ratios and, equally, to have the perception of less opportunity when reviewing the MCF reports around a single goal. As a better practice, we suggest that advertisers implement multiple goals to measure customer activities along a wider path.

For instance, goals could be set up at points before filling out a lead form but after becoming a slightly more qualified customer, either by increasing time or page depth on your website, reviewing a whitepaper or looking at cost information. These would help to measure performance even if there is a more significant lag before becoming a lead, lending insight to the very early parts of the journey.

After the lead form is filled out, any unique action that you could encourage to bring the now qualified customer back to the site again, such as completing a signup process, reviewing a contract or qualifying for a promotional offer, can then be used to go all the way back through to the beginning of the journey to find that initial contact point.

Why is (not set) so high for AdWords Keyword?
When you select a primary dimension in the Assisted Conversions report of Multi-Channel Funnels, it is not filtering the information as much as it is adding a different view to it. As such, when I move from that basic channel grouping view to AdWords Keyword, the report still shows 100% of the data but now groups each interaction by its respective keyword. However, since not all interactions have AdWords Keyword data associated with them, including Direct, E-Mail and Social Network visits, they are grouped into their own (not set) bucket.

During the webinar, my colleague responded to this question by saying that “not set” may also appear due to broken AdWords tags. This response is also technically correct as broken AdWords tags can also prevent keyword information from being passed through, but in many cases it’s more likely that it’s just because the visits don’t have keyword data associated as described above, and AdWords tags are probably OK -- so consider this first before trying to troubleshoot.

What devices are in place to prevent Spiders and Bots from inflating data and thus causing a possible "bad" business decision?
Multi-Channel Funnels measure specific goal or conversion actions that are hopefully beyond the grasp of bots or spiders that are just mining content. For instance, it probably wouldn't be likely to find one that tries to fake e-commerce orders.

If you have found bots coming through these conversions on your website (i.e. Store Locator), it may be practical to filter those visits out at the profile level in Google Analytics to make sure that they are not impacting any of your resulting analyses. Although we don’t recommend a specific set of criteria for limiting bots, there are dozens of articles online that you should be able to find with individual opinions on what is best.