maandag 23 september 2013

Building Your Marketing Funnel with Google Analytics

Posted by dohertyjf


Do you have an idea of the path a user typically takes to convert on your website? Or, are you simply building traffic from one channel (probably organic) and wondering why it’s not converting better? As I’ve grown up as a marketer, I’ve begun to really appreciate the insights that data can provide us on how users interact with our sites, and more importantly, on how they convert and where the experience can be improved to increase our conversion rates, and thereby our top-line revenue from online channels.


I’ve recently been very interested in building a full marketing funnel based on Google Analytics data. While it’s one thing to be able to identify where conversion discrepancies exist, such as low-converting types of visitors, it’s quite another to build a full and informed funnel from your site’s data. In order to do this and have an accurate view of where your conversions are actually coming from, you need to first have the following in place:



  • Email URL tracking: Check out Annie Cushing’s thoughts here in slides 11-14. (Actually, look at the whole deck.)

  • Social network tracking (tagging parameters and using a shortener to see clickthroughs by link)

  • Display tagging

  • Referral links tagged (or at least be aware of HTTPS sites linking to you, like Medium)

  • Paid search campaigns tagged

  • Tagging on affiliates (if applicable)


You can build your campaigns here using Google’s tool.


What’s a funnel?


Before we get too far into the meat of this post, I want to make sure we’re all talking about the same thing. I’m not referring to one of these. Rather, I’m referring to one of these:



The funnel is typically broken into three sections:



  • Top of funnel (TOFU)

  • Middle of funnel (MOFU)

  • Bottom of funnel (BOFU)


The goal of this post is going to walk you through how to identify the channels that are performing best for you in each of these areas. Once you know those, you know where to invest depending on your company’s needs or priorities. Also, knowing the different areas to which you can contribute will help endear you to the people running those channels, which will help you avoid being siloed as “the SEO.” Instead, you will start to be seen as part of the marketing team, which is what you are.


Another note: I’m not teaching you how to integrate into other marketing channels in this post. Stephanie Chang did a great job of it back in July when she wrote An Introduction to Integrated Marketing and SEO: How It Works and Why It Matters. Have a read there after you’re finished here.


Understanding attribution


You may already know this, but Google Analytics offers multi-channel attribution tools within the “Conversions” section:



In the “Assisted Conversions” section, you will see a number of columns. The ones to pay attention to are:



  • Assisted Conversions

  • Last Click/Direct Conversions


It’s important to understand the difference between assisted conversions and last click/direct conversions. According to Google’s own Answer Bin, a channel gets credit for an assisted conversion for any touch that they bring to the site where the interaction was not the one that led directly to a conversion. Google says:



This is the number (and monetary value) of sales and conversions the channel assisted. If a channel appears anywhere—except as the final interaction—on a conversion path, it is considered an assist for that conversion. The higher these numbers, the more important the assist role of the channel.



On the other side, a last click or direct conversion is a touch on the site that led directly to a sale. These are your closer, aka bottom-of-funnel channels. Google says:



This is the number (and monetary value) of sales and conversions the channel closed or completed. The final click or direct visit before a conversion gets Last Interaction credit for that conversion. The higher these numbers, the more important the channel’s role in driving completion of sales and conversions.



Make sense? Great. Let’s build a funnel.


Identifying channels based on funnel level


As I said above, we’re going to use Google Analytics to identify the channels in the different levels of your funnel. If you use a different Analytics platform, like Omniture or Piwik, write a guide using that and I’ll be happy to share it out.


Top of funnel


The top of your marketing funnel is where the first interactions with your brand take place. This is typically attributed to search or organic, but is that really the case for your website?


First, let’s identify the most common channels that people use to discover your site. To do this, go to Content > Site Content > Landing Pages. Set your secondary dimension to “Medium.” You’ll see something like this:



Now, export this data to Excel (I’ve provided a spreadsheet at the end that you can plug this data into) and pivot it to see which mediums are driving your best traffic. If you want to get super fancy, break it down by type of page as well.



Here’s how that pivot table is set up:



For the site shown in these screenshots it is indeed PPC and organic search. But just knowing the channel isn’t enough, so let’s take it a step further to see where the different channels are driving traffic. You’ll either need to manually classify your pages (if you have relatively few like in my example) or write an Excel script to do this automagically.


I now know that referral is the primary driver of traffic and that the majority goes to the homepage. One specific referral, which I tagged with a Medium of “Link,” sends the best traffic directly to conversion pages (which might not necessarily be the best place for people to land for their first interaction):



Middle of funnel


The middle of your funnel is the area where people are moving from a first brand interaction to an initial sale, or if they have already made a purchase, towards another sale. What we’re looking for in the data here is channels that are not necessarily our primary first- or last-touch drivers. Rather, these are the channels where the 2nd, 3rd, and 4th-time visitors come from in order to interact with your content again.


We can figure out the most popular and most effective middle-of-funnel channels a couple of different ways. The first, and by far the easiest, is by comparing different types of attribution to discover which channels get more credit based on first click, linear (where each channel gets equal credit), and last-click. To learn what each of the different attribution models really means, check out the Google support page.


By sorting the Model Comparison Tool in Analytics by Linear (high to low), you can find the channels that perform best when given equal credit independent of where they are in the funnel.



But this doesn’t give us great insight into which channels perform best in the middle. Rather, it’s telling us which channels account for the most revenue overall (which is still important to know), and the place doesn’t matter. In the above example, for Distilled that’s Direct, then email, organic search, and referral, in that order.


To find which channels are the most popular for your users to come back, we need to do some manipulation in Excel (my favorite tool) to clean out the first- and last-touch interactions in the Top Conversion Paths report.



What you want to do now is expand the number of rows in Analytics to account for as many of your paths as possible. For most sites the 5,000-row limit in Analytics will suffice.


Download all of your conversion paths into Excel. You’ll have one column with the complete paths, followed by the following columns:



  • Conversions

  • Conversion Value


To wrangle the data into the format we need, I also added the following columns:




  • Steps in Conversion Path

  • First Touch

  • All Middle

  • Last Touch

  • $/Conversion


If you’re a visual person, this screenshot may help you out to see how the sheet is set up:


Note: the hardest part here is figuring out what your cutoff is for conversion amount. For Distilled, for example, I removed anything under $30, because we don’t do anything with the data underneath that. I also picked a minimum threshold for the number of conversions that channel brought.

In Distilled’s case, five seemed pertinent because it gives enough to get a decent idea of $/conversion but also eliminates the very long (20+) conversion paths that we’re not going to optimize for anyways. However, also keep in mind that the length of the path matters. For example, Distilled’s median # of steps before a conversion is eight. With fewer than eight steps, our average per conversion is 30% higher than it is with eight+ steps in the funnel.

So, to clean up the data, I removed the following:




  • Paths with conversions < 5

  • Paths with conversion value < $30

  • Paths with (unavailable) in the path

  • Paths with more than 15 steps in the path



After you clean up the data, it will pull into the “Common Middle” sheet within the Excel workbook I link to below. Then, you can see pretty quickly which channels are driving the most middle conversions, and which middle paths give the best $/conversion:



Here’s the setup for that pivot table:




Once again, this will automagically work for you in the Excel sheet.


Bottom of funnel


The bottom of the funnel is the last touch that occurs before someone buys. These channels are incredibly important to know about because you can then build your strategy around how to get people into those channels and convert them later.



This one is easy to find. It doesn’t take tricky Excel functions. It doesn’t involve crazy data analysis.

Assuming you have Analytics set up correctly, you can find this data in Conversion > Attribution > Model Comparison Tool. When you set the Model to Last Interaction, you’ll see something like this:




For Distilled, you can see that our highest last-touch channels are direct, then email, then organic search.


Applying the data


Remember this funnel from the beginning?






Based off the data, I now see that for Distilled, the sections of our funnel look this way:


  • Top

    • Direct

    • Organic Search

    • Social



  • Middle

    • Organic to Organic

    • Direct to Email

    • Direct to Organic



  • Bottom

    • Email

    • Organic

    • Direct




Now we can build out a marketing plan depending on our needs.


Excel sheet


I promised you an Excel sheet that I have put together for you. Note that it does not automatically clean out your very long conversion paths, but use the parameters given above to narrow down your data to make it actionable if that makes sense for your business.


That said, you can download the spreadsheet here .


Bonus Excel sheet to find profitability by # of touches


I mentioned above about finding the number of touches that perform best for you. Here is a quick and dirty spreadsheet that allows you to do just this. Basically, the sheet looks at the number of touches and averages the conversion amount for each bucket. You can see the results on the far right.


To use this sheet for yourself, download your Multi Channel Funnel groupings in Analytics (you need to have ecommerce enabled) and enter your data into the sheet.



Download this bonus spreadsheet here .


Example and conclusion


If we are trying to convert more people to DistilledU, through that goal I know that Organic converts best for us on the last touch. This means that we need to invest in content that drives people towards a conversion through organic, so either blog content with a call to action or larger content teaching people SEO. We know that email converts 4th best for DU, but it works well higher in the funnel to convert people eventually. Therefore, we need to get more people onto our DistilledU email list.


Direct traffic converts well, of course; people are coming to the site because they know about it. Therefore we need to get top-of-mind and convert them into email and RSS subscribers so that they become familiar with our content and eventually buy through email or search.


We’ve built our funnel. You should go and build yours. I’d love to hear what insights you have.


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