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Google Analytics Multi-Channel Funnels: An Overview


For several months now, I’ve been waiting for Google to formally launch Multi-Channel Funnels, its new attribution analysis package for Google Analytics. Today, at long last, Google announced that Multi-Channel Funnels (MCF) is beginning to launch to all users. This feature is a real game-changer, in my opinion; it’s on par with Advanced Segmentation and Custom Variables in terms of new feature launches from Google Analytics. In that spirit, today I’ll be sharing a step-by-step guide designed to get you up and running with MCF quickly.

Note: before we jump into the details, you may want to review my conceptual overview of Multi-Channel Funnels, where I explain the default attribution model of Google Analytics and the value of Multi-Channel Funnels. You can find that article here. That said, on to the new reports!

Finding Multi-Channel Funnels in Google Analytics

MultiChannel Funnels Menu

First things first: logistics. You’re going to need to be signed into the new version of Google Analytics, also known as “v5.” Once you’re there, hover over your “My Conversions” drop-down box, and notice the new option called Multi-Channel Funnels. In this new report module, you’ll see four brand new reports: Assisted Conversions, Top Conversion Paths, Time Lag, and Path Length. Today we’ll look at each one individually to explain what each report can tell you.

MCF Report Choices

Assisted Conversions

The first report you’ll see in MCF is the Assisted Conversions report. While fairly simple, this report reveals a wealth of data we’ve never before been able to get! As you can see below, we’re going to see a series of metrics in this report. First, we get “Assisted Conversions,” commonly known simply as “assists” in the online advertising world. Assists are simply the number of times a given traffic source (like “Direct” or “Organic”) brought a visitor to your website who later converted via a different traffic source. Next you’ll see “Assisted Conversion Value,” which gives you the financial value of the conversions that were “assisted” by the traffic source in question.


Here, what we can see is that Organic Search brought in 10,000 “Last Interaction Conversions.” This means there were 10,000 conversions where Organic Search was the final “touch-point” that brought a visitor to your website. In fact, this is exactly how Google Analytics has traditionally attributed conversions. We can see the value of the conversions was about $117K, but what you’ll want to be analyzing in this report is the number of assists.

What we can now see, for the first time, is that in addition to the 10,000 “traditional” conversions Organic Search brought in, Organic Search also assisted with an additional 8,228 conversions – which were worth practically another $110K! With Multi-Channel Funnels, we’re now able to more holistically evaluate the value that our various channels of traffic generate. Do you think the SEO manager is going to be showing this new data to his/her boss? You bet.

Tip #1: Look for traffic channels that bring in more assists than “Last Interaction Conversions.” These are the channels whose value, until now, you were almost certainly vastly underestimating! These channels are commonly things like display advertising (think Google Display Network!) and social media marketing.

Tip #2: Want to get more granular than just, say, Organic Search? No problem. Just toggle from “Basic Channel Grouping” to something like Source/Medium! Now you’ll be able to see not just Organic Search, but google/organic vs. yahoo/organic vs. bing/organic.

Top Conversion Paths

Now that you’ve had a chance to see all the “assists” that your traffic channels are driving, it’s time to start understanding the most common combinations of channels that your website’s visitors use to find you online. For example: do people simply type your URL into their browser and convert? Or do they click on your Facebook ad, Google you, then finally click through from Twitter before converting? Google Analytics could never give us this kind of insight in the past, but now it can! Take a look below.

Here, we can see that the most common “path to conversion” is two separate visits from advertisements. The next most common path is two separate click-throughs from organic searches. To analyze this data in more detail, we might want to see the paths laid out by the individual keyword or the individual referral source. No problem – that’s easy too!

Tip: Get specific insights my using the “Other” drop-down box to analyze paths by individual keyword, campaign, etc.

Next, let’s take a look at another way to visualize this data. On the Overview report for MCF, you’ll have the “Multi-Channel Conversion Visualizer.” Here’s what it looks like:

Now, you’re probably thinking this is pretty cool just from looking at it. And it is! But let’s go through the details. The visualizer allows you to mix and match different traffic channels to see how they work together. For example, how do paid advertising campaigns interact with organic searches? That question alone has been the subject of hundreds of blog posts! Now you don’t have to rely on the gurus and self-proclaimed experts; you can simply leverage your own data. Do you see, for example, a lot of overlap between Paid Advertising and Organic Search?.

Tip #2: Look for channels that interact together in some way. They’ll have a lot of overlap when you select them in the Visualizer. These channels probably impact each other, meaning that if you pull the plug on Paid Advertising, for example, you might expect to see a drop-off in Organic Search as well. Imagine trying to get that type of insight from Google Analytics before now!

Time Lag

The Time Lag report is a little simpler than the first two we’ve looked at. In fact, it’s similar to the “Days to Purchase” report you might have seen in the E-Commerce section of your reports. However, the TIme Lag report applies to all conversions, not just e-commerce transactions (huzzah!). If you’ve never had the opportunity to use this report, here’s the skinny. You’ll now be able to see a breakdown of how long it takes, in days, for a user to convert. For example, do people come in and convert within 24 hours, or do they require days (or weeks) to make the decision to convert?

Here we can see that while 68% of our conversions occur within the first 24 hours of a visitor coming to our site for the first time, only 53% of the value of those conversions occurs in that time frame. This means that our most lucrative conversions require longer consideration by our potential customers – perhaps not too surprising, but nice to see backed up by hard data.

Tip: Do you have a lot of conversions (or value) that come in after 24-48 hours? Have you tried a remarketing campaign, through Google AdWords or another platform? Remarketing is a great way to get your message out to folks who have been to your site, but haven’t converted yet.

Path Length

You’ll often see a trend in the Path Length report similar to what we just saw in the Time Lag report. In fact, the Path Length report also has an analog in the “traditional” Google Analytics reports. If you’re an e-commerce business, you’ve probably seen the “Visits to Purchase” report, and that’s basically what the Path Length report is. But again, if you’re not an e-commerce business, you haven’t had the opportunity to use this report.

Now, here’s how the trends are similar. Above, we saw that the most lucrative conversions involved more than 24 hours of research before the user pulled the trigger. Below, we can see how the same trend materializes when we analyze how many visits it takes to convince someone to convert. While 54.5% of conversions happen after one visit (i.e., Path Length = 1), those conversions only account for 35.1% of the value!

Again, it’s possible that the research cycle for our more valuable conversions could cause users to need to visit our site twice or more before they decide to convert.

Tip: Don’t forget about remarketing! With AdWords, you install one piece of code on your website, and you can have a remarketing campaign up and running the same day.

That’s about it for today. I couldn’t encourage you more strongly to dive into MCF to start uncovering your own insights! Of course, there’s plenty of detail we couldn’t get into today, so play around with these reports on your own, and check back soon for more details on this illuminating set of new reports. You can stay up to speed by following Cardinal Path on Twitter here. Thanks for reading!

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  • Greg Klein

    Bad ass

    • Nick Iyengar

      +1, Greg :)

  • Jackson Lo

    Wow! Great post here Nick! This is proving to be a powerful tool for any business with an online presence.

  • Kristoffer Ewald

    Great article and overview. I think it’s relevant to ad that the MCF reports will become an excellent basis for a better understanding of how Marketing Channels interact and can form the basis of more advanced Attribution Modelling on the data.

    • Nick Iyengar

      Hi Kristoffer, thanks, and I completely agree. I’d really like to do a series of more detailed posts on this feature when I have time. I love MCF and there’s a ton to talk about.


  • Mike Snyder

    Great article.  I think you just convinced me to stick with the Analytics approach instead of spending dough on another solution.

  • Facebook Applications

    Another good addition to Google Analytics.

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