A reality every advertiser has to grapple with is understanding how your customers arrive at purchase, which is a process that has become less and less linear over the years. However, with Multi-Channel Funnels reporting in Google Analytics, you’re not totally left in the dark.
First unveiled in 2011 and polished over the years, Multi-Channel Funnels includes an extremely valuable set of reports for diagnosing users’ engagement with your site and their path to conversion.
Our goal is to help illuminate the functions of these reports to help you investigate and better understand your audience.
When approached tactically, you can easily pinpoint which channels are driving more upper or lower funnel activity (outside of directly converting audiences), and which have less impact.
Where do I find these reports?
These reports are all contained in the “Conversions” reporting section – note that you must already have conversion tracking or ecommerce transaction tracking in place with existing data. The bigger your data set (quarters, years), the more insight you will have.
What report settings do I use?
Before getting into all the reporting that is available, you should first consider what report settings are a best fit for your analysis.
Keep in mind that most reports in MCF are intended to focus on a subset of converters who have a longer path length (the number of site visits before purchase/conversion).
“Path Length” is a drop-down box at the top of most reports in MCF:
While the numbers above are obscured, the “2 or more” row is the sum of data for individual rows “2” through “10+”, and in my example they account for nearly 33% of all conversions.
As we’re concerned with repeat visits prior to conversion, the “1” visit row is less useful here. By default, Analytics shows you all data pertaining to the “2 or more” segment, but you’re free to concentrate on smaller subsets (3 only, 4 only, etc.).
You may also modify the “Conversion” box to eliminate certain goal types (such as newsletter sign ups, or other actions that don’t represent revenue action).
In my example above, I’ve eliminated Goals 1 and 2, as these are included in Goal 5 as an all-inclusive conversion goal. Your needs will vary – focusing on your key ecommerce goal (transaction) will be ideal.
Shown above, the “Lookback Window” is a report setting that is more useful for retailers with more involved, extensive sales funnel (big ticket items, for example). If you know it can take 6 to 8 weeks for a purchase decision, you may extend this back to 45 or 60 days, with 90 days being the upper limit.
Some reports may include “Interaction Type” – this is primarily useful for Display advertisers who have some amount of YouTube or Display Engagement Ads in their ad mix (which fall under “Rich Media”). By default, all types are included.
Multi-Channel Funnels Overview
The “Overview” report is a great top-level view you can forward to upper management, complete with percentage of assists per channel and a nice Venn diagram visualizing the overlap between channels.
Assisted Conversion Report
Assisted Conversion is also more summary-oriented in nature, but you have more flexibility to drill into specific dimensions. By default, Analytics groups your traffic into a few key top-level segments (“MCF Channel Groupings”):
The majority of these are intuitive to understand. For example, “Organic Search” will represent results where an interaction occurred in the “organic” medium.
One major departure from other Analytics reports is the division of Display and Paid Search. While most Analytics reports lump these together under the “Google / CPC” source medium, here Google already knows which AdWords campaigns contain Display and Search traffic, thus they are grouped individually.
To drill deeper into the channel segments, you can add a Secondary dimension, as you do with normal Analytics reports. If you want to slice into the keywords alongside your assist data, you can add the “Keyword” dimension.
One valuable metric here to focus on is “Assisted / Last Click or Direct Conversion”…
– If this metric is greater than 1, the more likely this channel is to have assisted in conversion.
– If this metric is less than 1 (or close to 1), this channel equally assisted and completed conversions.
– If this metric is closer to 0, this channel completed more conversions than assisted.
Google’s support documentation provides lots of useful information on how this and other metrics can be helpful.
Top Conversion Paths Report
This rests among my favorite reports in Analytics overall – if you’re trying to determine whether a generic keyword drove a branded conversion, this is a great place to look for those types on patterns.
In this view, you’ll see sequences of the most common paths – often this can include two paid search clicks, or a paid click followed by a direct visit.
If you want to take this a step further, adding a Secondary dimension for keyword, source-medium, or other slices can help you dig into the roots of what drives results from one channel to another.
A great extra dimension to use here is “keyword (or source/medium) path” – keywords will be shown when there is a keyword available, otherwise only the source medium will be shown. Direct, referral, and some organic data won’t have keywords to include.
Time Lag Report
Accounting for repeat visits by source is one thing, but what about time? The Time Lag report, while fairly basic overall, will show you the percentage of conversions (and revenue, if tracked) that occur from day zero (0) to day 30.
For most retailers, it’s not uncommon to see the upper 85% of results occur in days 0 to 1. However, more involved purchases may result in extended delays (3 to 7 days, 8 to 14 days, etc.) which can have some implications for how you tailor your remarketing strategy.
Path Length Report
The Path Length report is the counterpart to Time Lag, simply counting the concentration of sales (and revenue) by the amount of interactions.
How do I refine these reports to a more focused set of visitors?
There’s already a lot of insight at the surface level for each report, but some basic drilldowns via secondary dimensions can only get you so far. If you know there’s a particular segment of users (a device type, a given generic keyword, or other common origin point) you want to isolate in these reports, you can take your analysis further by leveraging Conversion Segments.
If you’re familiar with Custom Advanced Segments or Sequence Filtering, you’ll feel right at home here. There are many defaults segments to help you hit the ground running. For example, you can easily segment into and compare traffic that solely began or ended on a paid ad interaction.
You can also create your own segments, with complete freedom to define your segment by the first, middle, or last interaction:
The possibilities with this segmentation are nearly endless, so long as you’re careful to arrange the “And”/”Or” logic of these segments correctly. Google provides some great documentation to help walk through the details of creating your own Conversion Segments.
While this may seem exhaustive, this is really just the tip of the iceberg with Multi-Channel Funnels. With the right insight determined from these reports, you may easily identify a directly unprofitable channel (generic paid keywords, email blasts) are actually influencing purchases that are completed in more profitable areas of your advertising (branded ads, direct visits).
For more reports to help you mine your existing Analytics data, download our free quick reference guide, 5 Essential Google Analytics Reports for Ecommerce (it even includes a bonus guide to creating your own custom reports)!
