This is a great approach when you need to look for many values of the same dimensions in a quick-and-dirty sort of a way. For example, if I wanted to segment for visits that saw a specific set of 300 products and all I have is the list of products. Just concatenate all of these values together, delimited by a space (Link 1), and use that as the value with the "contains any of" criteria (Link 2).

Keep in mind that this uses a space as a delimiter so if the values you are wanting to look for have spances then see next note.

This is good for a very temporary but short list. If this is something you are doing regularly or you are getting into thousands of values it really is better to coordinate with your AA admin to set up a classification.

RELATED: Link 1 · Link 2

Another easy-but-so-good-it-makes-me-queasy segment (was that a stretch? nah!) is to look for visits that performed some key action on your site that you have tracked through your event variables. All you do is add the segment to your definition and change the criteria to "exists". This will then include any visit that triggered 1 or more of these events. See Link 1 for details.

RELATED: Link 1

Do you want to segment for something simple such as visits that saw the home page? Link 1 shows you how it's done. No problem, right? Well don't get too comfortable. Doing the inverse (visits that didn't see the home page) causes problems all the time. Whatever you do, don't use the "does not equal" criteria in this sort of scenario (Link 2). The reason for this is that as soon as the user goes to another page they will see a page that isn't the home page. This will result in their whole visit being included when you really wanted it excluded. The safest way to do this is using a positive criteria within a exclusion container (Link 3)

RELATED: Link 1 · Link 2 · Link 3

In Adobe Analytics, you can create a segment based upon any path that users take on your site. For example, in Link 1, you can see a typical page fallout report. From there you can click on the link to create segment from this path to see Link 2 which is a sequential segment that models that path. From there you can customize the segment any way you'd like and even make it span across multiple visits by switching it to a Visitor segment.

RELATED: Link 1 · Link 2

Using the IP-based City, State or Country dimensions in Adobe Analytics, you can create geographic segments. The linked segment here (Link 1) shows an example of segmenting traffic from the city of Chicago.  Adobe analytics captures country, state, city by default using the end-users' IP address. This information can be helpful when building segments since it allows you to narrow down your audience by country, state or city. This can be used to see where customers are searching for products or where training might be needed.

RELATED: Link 1

This segment looks for visits that are greater than one to isolate return visits. Return visits are useful for times that you want to only look at visits that have been to your site/app in the past. This can be used to see:

· How paths differ between first-time and returning visitors
· Which products first-time vs. return visitors view
· What content is viewed differently by first-time and returning visitors
· How landing page clicks differ between first-time and returning visitors

In addition, in Adobe Analytics, you can add segments to calculated metrics, so the Return Visits segment can be used to see any metric trended over time for returning visits.

To see an example of how this segment can be created, click on Link 1.

RELATED: Link 1

This segment looks for visits that are first-time visits. First-time visits are useful for times that you want to only look at visits that are new to your site/app in the past. This can be used to see:

· How paths differ between first-time and returning visitors
· Which products first-time vs. return visitors view
· What content is viewed differently by first-time and returning visitors
· How landing page clicks differ between first-time and returning visitors

In addition, in Adobe Analytics, you can add segments to calculated metrics, so the First-Time Visits segment can be used to see any metric trended over time for first-time visits.

To see an example of how this segment can be created, click on Link 1.

RELATED: Link 1

To better understand Cart Abandonment, you may want to do some analysis of those who Abandon Cart, vs. those who Abandon Cart but return to it later. You can use a segment like this:

Visitor

Cart Additions exists AND Orders does not exist*

THEN

Cart Views exists

To dive deeper, you can:

· Apply specific timeframes around the “THEN” (for example, “Then within 1 day”, “Within 1 week”, etc.
· Compare those who return to view the cart vs. those who return, view the cart and actually buy

* Note: Sometimes this acts a little bit funky - if so, you can always tweak it to something like “Orders is less than 1”

To backfill your goal data, simply create a segment with the same criteria was your goal. For example, let’s say your goal completion location was “thank-you.html” - create a session based segment for page=thank-you.html. The numbers for this segment should be identical to your goal (for the time period since the goal was created.) This is because goals are de-duplicated to 1x/session, so they essentially function the same as a segment.

“But can’t I just use unique pageviews?” Maybe. Unique Pageviews are actually unique based on just on the URL, but also the Page Title. So, let’s say you have multiple regions with a thank-you.hmtl page, but their Page Title is different (“BizWorld USA Confirmation”, “BizWorld DL Confirmation” etc.) These will be considered unique in your Unique Pageviews report, but not in your goal or your segment, since those only care about the URL. So, the most accurate way to backfill goal data is going to be a session-based segment, and using the sessions metric.

The core application of segmentation is to isolate a subset of traffic to the site. The risk, though, is that the traffic that is *not* included is often useful context for the main segment. In many cases, the way Google Analytics segments get created is such that it is very easy to use one segment to make a segment that is "everything else." This is done by simply switching the overall filter condition for the segment from its default of being an "Include" segment to being an "Exclude" segment as shown in the first figure, which is a simple example of "visits that entered the site on the home page."

This is a 4-step process (all four steps are shown in the first figure, Link 1):

1. Open the original segment and click "Copy" to make a copy of it.

2. Update the name of the new segment to make it clear that it is an "Exclude" segment (I like to pre-pend most of my segments with "Include:" or "Exclude:" if their nature is such that that makes sense).

3. Change the filter type to be "Exclude" rather than "Include."

4. Click "Save" to save the segment.

The example shown is a very simple one. This technique works any time the segment is a "Condition" segment with a single filter. More advanced segments require more care to create the "everything else" version, but it is still often a worthwhile exercise to do that.

The second image (Link 2) shows the two segments applied side-by-side within Google Analytics. It's generally a good idea to also initially include the "All Users" segment to ensure that, as intended, the sum of the main two segments equal the total.

RELATED: Link 1 · Link 2

The core application of segmentation is to isolate a subset of traffic to the site. The risk, though, is that the traffic that is *not* included is often useful context for the main segment. One nice thing about the way Adobe Analytics segments work is that it is very easy to use one segment to make a segment that is "everything else." This is done by simply switching the overall container for the segment from its default of being an "Include" segment to being an "Exclude" segment as shown in the first figure, which is a simple example of "visits that used site search."

This is a 3-step process (all three steps are shown in the first figure --- Link 1):

1. Open the original segment.

2. Change the name to make it clear that it is an "Exclude" segment (I like to pre-pend most of my segments with "Include:" or "Exclude:" if their nature is such that that makes sense.

3. Change the overarching container type to be an "Exclude" container rather than an "Include" container (or vice versa if the original segment was an "Exclude" segment").

4. Click "Save As" and save the segment.

The example shown is a very simple one, but this technique works on much more advanced segments -- even if the segment has a mix of include and exclude containers within it, simply "flipping" the overarching container type will make the segment "everything else."

The second image (Link 2) shows the two segments applied side-by-side in Analysis Workspace. It's generally a good idea to also view the first few reports with *no* segment applied as well to ensure that, as intended, the sum of the main two segments equal the total.

RELATED: Link 1 · Link 2

Some channels we can quickly and directly influence (paid search, paid social, display, email, etc.), while others are more difficult to quickly impact (natural search, direct, etc.).

At the same time, updating content on a page is one of the most easily modified (internal politics and systems notwithstanding) aspects of a site.

So, once you've identified the top (influence-able) channels and the top landing pages for those channels, a few quick segments to isolate the traffic from a specific channel and to a specific entry page then enables you to explore that traffic through any set of reports: pathing, devices, exit pages, site search terms, etc.

This segment typically makes the most sense as a visit-based segment with a simple "And" condition using Last Touch Channel (or First Touch Channel or something else) and Entry Page as shown in the figure (Link 1)

RELATED: Link 1

Some channels we can quickly and directly influence (paid search, paid social, display, email, etc.), while others are more difficult to quickly impact (organic search, organic social, direct, etc.).

At the same time, updating content on a page is one of the most easily modified (internal politics and systems notwithstanding) aspects of a site.

So, once you've identified the top (influence-able) channels and the top landing pages for those channels, a few quick segments to isolate the traffic from a specific channel and to a specific landing page then enables you to explore that traffic through any set of reports: flow navigation, devices, exit pages, site search terms, etc.

This segment typically makes the most sense as a visit-based segment with a simple "And" condition using Default Channel Grouping (or a Custom Channel Grouping or Medium) and Landing Page as shown in the figure (Link 1)

RELATED: Link 1

Useful context for evaluating one segment of visitors is often "all the other visitors (or visits)." This is very straightforward to do with Adobe Analytics:

1. Create the initial segment and save it.
2. Click on the arrow at the top right of that segment and select "Copy."
2. Name the segment and change the dropdown from "Include" to "Exclude."
3. Click "Save" and save the new segment.

This process is shown in the first image included here. What is shown is a simple example of "visits that entered on the home page." More often, there is a more involved segment .

I like to start names with "Include:" and "Exclude" to make it clear in the segment's name what type of segment it is.

The two segments can then be added to a report in Google Analytics or Data Studio. It can be reassuring to include the "All Users" segment, too, initially to confirm that the two segments, when combined, actually do equal "the whole." The second image here shows an example of that.

RELATED: Link 1 · Link 2

This segment looks for the names of major social networks. It can be customized for your business, to add any ones that might be missing (for example, to add more obscure social networks used in other countries or industries.) It is up to date as of mid-2017.

To download this to your Google Analytics account, use this link: https://analytics.google.com/analytics/web/template?uid=KPisySh9RiKvJd7WDiNFWw (Link 1)

You'll be prompted to choose which view you would like to apply it to. Once it's included in your account, you can optionally set it to share with other collaborators in that view, or share with all the views you have access to.

RELATED: Link 1