Google Analytics

Advanced Segments: Conditional and Sequences

Why you should use Segments in Google Analytics

Looking at all of your Google Analytics data at once sucks like a sour lemon. If you don’t segment the data, you will never find the good, the bad, or the wonderful. Plus, we all know that customers take different journeys to, and on, your awesome website. So, it’s great to know how your marketing channels are performing, and how to find your best customers, as well as how to enhance channels and help those customers that are struggling. 

Ideally, you’d want to use Google Analytics to find answers to your question like an easy-peel clementine, so let’s dive into what you can do with these little gems. 

In particular, if you use the Advanced Segment options, Conditions and Sequences, you can really power up your work.

This post dives into those Advanced Segments. 

If you want to learn more about what Segments are, we have a handy, free PDF explainer ‘How To Use Segments’

Segments in Google Analytics from The Coloring In Department

Google Analytics reports are all built on the basis of Dimensions and Metrics. Segments are looking at your data set to find a match for the Dimensions and Metrics you want to focus on. 

You can create user Segments on the following terms: 


You can look at your data – and dive into people, places, ages and language. 


Isolate users or sessions by device, so things like mobile/tablet/desktop. The browser they are using or the size of screen resolution. 


This is all down to recency and frequency, so the number of sessions. The days since their last session, how many transactions they had.

Date of First Session 

Create a Segment based on cohorts, that match a definition, for instance, the dates between their first and last visit to your website. 

Traffic Sources 

How do your users find you? Which campaigns, channels, mediums, sources, paid keywords etc.

Enhanced Ecommerce 

Segment your users by their shopping actions. Revenue per user, the product they bought, the brand they purchased etc.

Advanced Segments: Conditions and Sequences 

These options allow you to really build out and power up your work. This function gives you more flexibility, as you can layer Dimensions and Metrics, and mix things up. For example, you can create a Segment for Traffic Sources, but if you wanted to look at a Traffic source AND the page a user viewed you would need to use an Advanced Segment to do that.

They both work on the basis of you defining what the dimensions and metrics are; and you can opt to include or exclude dimensions and metrics. Then define what the conditions are, so which dimensions and metric values are we looking for, and then, if the next part of the Segment is to be included as an and/or.

Please note – And / Or statements behave differently. You are putting together two or more Dimensions and Metrics. You use AND to say that both conditions are required, the OR means that only one condition must be met.

Condition Based Segments

This is where you are building a set of conditions. You can pick what you want, provided that the dimension, metrics and their values actually exist in your data already. Segment your users and/or their sessions according to single or multiple-session conditions.

Sequence Based Segments 

This gives you the same flexibility as Conditional Segments, the difference here is that you are segmenting your users and/or their sessions according to sequential conditions. Specific steps in a journey rather than conditional ones.

You do this by  Filtering> Include or Exclude> Sessions or Users> then define the Sequence Start > Any User Interaction or First User Interaction.  Then you put in your Dimensions or Metrics and assign a value for each step.  That value uses basic math symbols (greater than, less than, etc) you also get the option to use And/Or statements to further qualify this.

You need to make sure that you select the correct type of Advanced segment as they behave a little differently overall.

Scope of Segments 

We’ve talked about getting the scope of the segment correct, but the difference between a user based segment and session-based segment are equally – super important. 

In your Condition and Sequence Segments, you can filter between Sessions and Users. As you might expect, this has an impact on your data, even more so when you are using the And / Or statements.

Let me explain.

If you create a Condition Segment that is Session based on Source = organic and, say for example Event = info pack downloaded and Event = Free resources sign up. This will only pull in an answer if these two criteria happened within the same session.

But what if the traffic from Organic doesn’t always assist in these events happening? You would need to swap this out to a User based segment.

Hold up, when we do this, look what happens to our data. Zero ? That can’t be right surely? There must be users that came from organic and downloaded content to fire our event tracking. What’s going on?

Well, if you change it to a User based in this Condition Segment, here’s the kink, it will only pull the data if the conditions happened within the same Hit.

That is down to the criteria box. This Segment works on what is in the box specifically.

So you need to change this by adding a new box (we will demo this in our Google Analytics Course).

Basically, if you want to see two conditions for a user based segment but not the same hit, then you have to split the box to capture the two respective criteria.

Now, to further emphasis the Sequences point. Here you can change the filter to have Session or User. But – for each of the steps, GA will look at each step as a single hit. This can be quite handy when you want to look back over a 90 day period (which is the limit for User Segments). When you build a session based sequence segment, it will give you the number of users too.

Found this post interesting?


We have a whole module on Segments in our Online Google Analytics Course.

You’ll work through all the types of Segments available to you, and understand the pros and cons of Segmentation in general, as well as some issues that come along with using it.

And, as no one likes a blank sheet of paper, we’ll walk through a process to work out the types of Segments you may want to consider for your business.

You know you want to have a look 👀

Head this way my measurement loving friend.

Google Analytics

Attribution Across the Customer Journey

Right, as marketing folk we -know- that our customers take their own unique journey, and their intent at each stage of their journey will change –only– when they are ready to move to the next stage in the relationship.

The problem is that reporting and Return On Investment (ROI) for our marketing skews to the last channel, campaign or page that scored the goal. So that interaction, ends up getting all the credit. Let’s call them your quarterback, see every high school drama, ever made.

Lately, we have been doing some talks that dived into how you can use Google Analytics (GA) to measure user intent and the effectiveness of your campaigns at each stage of the journey, as well as highlighting some freaky little quirks within GA that may have cost you dearly.

What does attribution and the customer journey have to do with each other? 

When we talk about attribution, remember it’s just a fancy way of saying who gets the credit. 

Who do we attribute success to?

We need to make sure that when we’re reporting on how our marketing channels are working for us, that we don’t make bad or biased decisions on that data. By that I mean just focusing on the superstar channels, that score most of the goals. *cue shameless plug to our Attribution Explainer*

Using Google Analytics to measure your marketing across the customer journey. from The Coloring In Department

Now, let’s imagine you have just scored a Goal on your website. High Five! That could be a physical sale, or someone filling in a form. Either way, someone did the thing you need them to do – in order for your business to survive. Always a good thing!

So, who gets the credit for scoring the Goal?

The answer will depend on the attribution model you are using. Or rather, which model Google Analytics is using in your reporting.

Now, in our hypothetical example, in our lovely picture. If this were a typical customer journey, the Acquisition reports in Google Analytics will give all of the credit to the Last Non Direct channel. Which is fine, but it does make the other channels look a bit useless when you read the reports.


It may seem obvious, but you can’t do any attribution if you don’t have any goals setup. 

Something we like to do here at The Coloring in Department is build dashboards in Data Studio. Now, provided you have more than 1 goal (you can have 20!), you can then select a mix of macro and micro conversions, as well as a heat map to help visualize the conversion rates across the goals that you have set up. If you list the sources, you then get to see how well your marketing is doing to drive your conversions. It also helps to show the role of that channel for you.

If you do this, your reports begin to paint a visual picture about the role your marketing channels plays in contributing to the growth of your business. And, it helps to manage the expectations and roles of your marketing.

For example, social media may be amazing at getting people to watch a video, and sending a newsletter will get them to sign up to a free trial. Don’t judge the success of all channels in the same light, they may not be the closer, that may not be the role of that channel.

Attribution Reports 

When you are in Google Analytics you get some really useful information, like which channels assisted in conversions, what the value of these assisted conversion is, how long it takes people to covert, and top path to purchase reports.

I like these reports because they help level the score card. We want to be a little fairer, a little more balanced, when reporting on our marketing channels.

The Assisted Conversions report in particular is going to show you how your marketing channels are assisting in driving conversions for you. This report became available, circa 2011, because people were making bad decisions on Google Ads. I remember being in a meeting with a client who said that, when they looked at the acquisition report, that paid search only accounted for two conversions, and that it cost them about £500 in Paid Search spend.

So, they were going to get rid of it. But – when they had a look at the assisted conversions report, it showed that the paid search channel actually assisted in 98 sales. So, that meant if they had closed off the budget of £500, assuming that it is only contributing to two sales, they would have actually been saying bye bye to 98 sales. Paid Search for them was a channel that started the journey, it was brand awareness, an exposure channel.

So, it’s a great little report, but how do we get these metrics and dimensions into a Google Data Studio report.

Now, for a slight challenge with Data Studio…

Data Studio (and I do love it very much) does not let you pull in my favorite reports, which are found in Multi-Channel Funnel reporting. There is a work around though. You need to use Google Sheets.

In this example, we have the top half of the report being pulled in from Google Analytics. Number of users, sessions, revenue. Lovely. We then have the Default Channel Grouping (DCG) listed with revenue next to it. Remember, the DCG is going to give 100% credit to the last non direct channel.

We want to make the report a little balanced. Using Google Sheets with the Google Analytics Add-On we can pull in the assisted conversions for our marketing channels. Yippie. Let’s talk through the steps on how to implement this, shall we?

What you need:

You need to fire up Google Sheets and get the Google Analytics Add On. Once you have this loaded, you can select from the top navigation in Google Sheets <Add-Ons> and then select ‘Create New Report’. Give your report a name and use the dropdown to select the GA Account, Property, and View that you want to use. Keep the Metrics, Dimensions and Segments empty . Click on ‘Create Report’.

You end up with a sheet that looks like this.

You still need to do some tinkering here to get our Google Sheet to do what we want.

For some reason rows 13-17 are squished together, so you need to click on the arrows to expand the row. In row 14 where it says ‘Report Type’ you need to type in mcf. This is super important. I banged my head against the table for ages trying to work out how to pull this in Google Sheets. You must change the ‘Report Type’ to ‘mcf’ in order to pull in the MCF API which is different to the core reporting API, which powers the Acquisition Reports.

Now, we need to type in the MCF Metrics and Dimensions in row 6 and 7. These are not the same as the typical GA Metrics and Dimensions, we need to specifically use the MCF Dimensions and Metrics Reference. 

When you know which MCF Dimensions and Metrics you want, type them into row 6 and 7. You can add more than one Dimensions and Metrics to each row. In this example we have 3 Metrics, Total Conversions, Assisted Conversions and Conversion Value. In the Dimensions row we have the Basic Channel Grouping and Day.

When you are happy with your selection, head to the top of your Google Sheet and click Add-On. Select Google Analytics > Run Report.

You should get a message that looks like this.

Once it has run the report you will find your data inside a new tab.

To get it inside Google Data Studio, log in, and select Google Sheets, which is already listed as a connector, and select the name of the Google Sheet file that has your MCF data in it. Then, work as normal in Data Studio and create your tables, charts etc. whatever takes your fancy.

If you enjoyed this post, you should check out our GA online course. We have a whole module dedicated to getting your attribution grove on!