Sometimes Google Analytics does things in a quirky way, or has technical limitations you don’t anticipate. Here are four such “surprises,” some of which come up commonly in reporting (the details of sequences maybe not so much). None of these are secrets, but they are all things you might expect to work differently than they do.

1. Exit pages have 0 time on page (if no event occurs).

GA calculates time on page via the timestamp of page load and the timestamp of the subsequent hit. When there is no subsequent hit, such as on an exit page where no engagement hit occurs, the time is 0. You can see this by applying the Bounced Sessions system segment to the Behavior > Site Content > All Pages report. You can set up an event to fire later on to give GA timestamp data if you want more accurate numbers, though you’ll never get it exactly without blowing up your event hit count.

Loves Data has a nice video explaining Google Analytics time calculation, or you can read Google’s session duration documentation page.

2. Revenue attribution is different in Conversions reports than in Acquisition reports.

In the Multi-Channel Funnels and Attribution reports under Conversions, Direct-channel sessions get credit for conversions that happen during them. In the Acquisition reports, that credit is given to the most recent previous session that was in some non-Direct channel (unless there isn’t one in the previous six months). Of course, there’s one exception as well: the Conversions report under Acquisition > Social uses MCF-style attribution.

Annielytics has a post on why Acquisition differs from MCF and some more details around it. If you need more comparable numbers, the Model Comparison Tool allows you to define your own attribution models, so you can give Direct a weight of 0.

3. Non-Interaction Events count as sequence steps.

A session with a single pageview is not bounced if it also contains a typical event – the event counts as a user action beyond the pageview. An event labeled “non-interaction” (the opposite of “engagement”), however, does not prevent bounced sessions, or affect the time on page calculation. That label is intended to be applied to “utility” events that are simply carrying data payload to GA for EEc or similar, not representing active choices by the user. However, in sequence segments they are counted as distinct steps, meaning in some cases bounced sessions can satisfy 2-step sequences.

I have no official references for this; I discovered it while experimenting to work out all the details of sequence segments.

4. Goal funnels have no effect on goal completions.

When you set up a destination goal in Google Analytics, you have the option to define a funnel of preceding pages. You can mark the first step of the funnel as “required” if you’d like to. However, this has no bearing on whether the goal is completed or not! If the destination page is reached, a goal conversion is counted – funnel or no funnel, required first step or optional first step. The only places in GA where the funnel matters are in the Funnel Visualization and Goal Flow reports (Funnel Visualization is a fantastic report, I hasten to add, although you can’t segment it). The only place a required or optional first step matters is in Funnel Visualization: only sessions that completed that first step will be included, which may not include all sessions in which a goal completion happened. All sessions that converted will be included in Goal Flow and the other goal reports.

Google’s page of destination goal examples seems to be the best reference for funnels, oddly. Their page comparing Goal Flow and Funnel Visualization may also be useful.

California ground squirrel photo by JoeBreuer on Pixabay.

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I recently finished compiling and writing a training series for my coworkers on Google Analytics. In the process of finalizing the section on Segments, I realized I didn’t know the details well enough to write confidently about sequence segments, and my hunts for someone else’s explanation came up mostly dry.* Having remedied my ignorance through carefully-planned visits to our dev server, investigation of the contents of hits in Google Tag Assistant, and creation of test segments to see what is included or excluded, let me pass the savings (read: big time nerdery) on to you.

* I did find partial answers in Reddit’s Analytics community and the Google Analytics Solutions Community, and later on Growth Addict. What you’ll find below is more obsessively complete than anything I’ve found online, though.

The main thing to understand is that hits in GA are comprehensive. If we stack dimensions by scope as follows:

• User
• Session
• Page
• Event/Social Action

then hits, which are the bottom two rungs only, carry not only their own specifics, but values for the dimensions above them as well.

In the context of segments, that means a filter condition like “Page contains /blog/” is satisfied not only by blog section pageviews, but by any and all events or social actions triggered on blog pages.

For non-sequence segments, it doesn’t make a difference: you can’t trigger an event on a page without also having triggered a pageview (well, unless your tracking is incomplete or very nonstandard), so the filter is going to pick out the sessions you expect.

For pages in sequences, it’s likely a benefit. You probably wouldn’t want to exclude a session from the filter “Page 1 is immediately followed by Page 2” just because the visitor shared Page 1 to Facebook.

This is especially true because Non-Interaction Events still count as hits for the purposes of sequences: if Page 1 includes an internal promotion for which impression data is sent to GA as an event right after page load, even a Non-Interaction Event (as it should be), then it will be impossible for a pageview of Page 2 to immediately follow the pageview hit of Page 1.

If you have Non-Interaction Events set up, this makes “Event X is immediately followed by Event Y” sequence segments unreliable. An impression of a product list or internal promotion in between the two events breaks the “immediately” part of the condition.

The inclusion of Non-Interaction Events also has the strange consequence that, in certain circumstances, bounced sessions can meet sequence segment criteria. If your sequence is “Source A is followed by Page 1”, and Page 1 sends its internal promotion impression event, then someone who lands on Page 1 via Source A and bounces will still have their session included in the segment.

Let’s back up. The dimensions stack as follows:

• User
• Session
• Page
• Event/Social Action

User-level filter conditions will hold of either every hit in every session for a given user, or none of them; putting a User-level filter condition into a sequence is equivalent to saying “some hit, any hit, has to happen here.” Unless that’s what you need, your segments will be more clear if you put any User-level filtration outside of the Sequences panel.

If you are creating a Session segment, the same applies to Session-level filter conditions: they will hold of every hit in a given session, or none, so their value as part of a sequence is minimal.

In a User segment, a Session-level filter condition makes for a complicated description of what’s being captured. For example:

“Filter Users, starting with any interaction, so that Source A is followed by Page 1.”

This will capture people who visit from Source A, and have a pageview of Page 1 or event/social interaction on Page 1 in that session (but not as the very first hit) or in a later session (perhaps as the first hit).

If you change “is followed by” to “is immediately followed by,” you capture people who have activity on Page 1 during a session from Source A (but not as the very first hit), or as the very first hit of a non-Source-A session that immediately follows a Source A session.

In both cases you’ll also potentially include bounced sessions, because of Non-Interaction Events.

The same applies if you replace Page 1 with Event X or Social Activity Y, although the bounces will no longer be included. The upshot for me is that “is immediately followed by” isn’t useful when mixing Session- and Hit-level filters – the combination of flexibility and extreme specificity makes it unlikely that it is selecting a meaningful cohort.

Even with all-Session filter conditions in a User-level sequence segment you have to be careful of whether your filter conditions could be met simultaneously. If your filter is “Channel A is immediately followed by Channel B,” then you will grab the users you intend: those who visited via Channel B in the next session after a visit via Channel A. If your filter is “Channel A is immediately followed by Landing Page 1,” though, any User who had a session that was via Channel A, landed on Page 1, and contained at least 2 hits will also be included.

Well! Glad we got that cleared up.

To recap:

• Every hit in GA includes page, session, and user-level data, and will meet filter criteria for those dimensions: events meet page filters; pageviews meet session filters.
• Non-Interaction Events count as hits even though they do not prevent bounces.
• “Followed by” sequences probably behave how you expect, as long as you realize Session to Hit and Hit to Session filters could be met within a single session.
• “Immediately followed by” Page to Page sequences probably behave how you want them to; for Session to Session sequences, consider whether the filters can be met by the same session.
• For other “immediately followed by” sequences, think through your filters carefully!

Window photo by skeeze on Pixabay.

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Goals in Google Analytics are intended as a generalization of transactions: actions you wish to think of in terms of conversion rate, and which you are specifically looking to increase (you could potentially use them for the opposite, but that’s a different blog post).

What are goals and why should I have them?

Having an action tracked as a goal adds basically two things onto the standard event or pageview tracking: first, GA will automatically calculate the conversion rate for you, and second, you can view goal conversions as part of other reports, making it easy to see what audience traits and acquisition channels convert at higher rates and therefore are perhaps more worth aiming your marketing dollars and website optimization towards.

GA gives you 20 goals, and unless you have a full-time analyst or the equivalent, that should be plenty – in fact it should leave room to grow on. If you want to include a ton of micro-goals, though, you can set up additional views to contain them. Do that as early as possible; even if cloned from an existing view a new view will only contain data beginning at its creation. If you are lucky enough to be working from a clean slate or have the freedom to kill off existing goals, you can take advantage of the organization of goal sets. Those allow you to view up to 5 goals together within most Acquisition and Audience reports, which can be a convenience.

Note that you are limited to 4 kinds of goals: time on site, number of pages viewed, specific page reached, and event occurrence. You can use regular expressions to make goals that are reached via multiple events or multiple destinations, but you can’t combine across goal types or create goals that require more than one event or pageview to occur in order to be counted. The primary limitation imposed by this is that sequences of actions cannot be tracked as goals. GA lets you define a funnel for a destination goal and mark steps in the funnel as “required,” but “required” in that context is “FYI you can’t get skip this and get through,” rather than “only count this as a goal completion if the person visited this page.” Same destination + different funnels = goals that track identical activity. Sometimes the solution is to change the way you are tracking your goals, and sometimes it is to abandon that activity as a goal and look at it using a different tool such as segmentation (about which more another time).

Choosing goals

Concrete advice for what goals to set in Google Analytics is hard to come by, which is understandable, since the details of your site matter a lot. I’ve gathered some options that ought to apply to a broad swath of sites, though.

General Site Engagement

Time on site *
Number of pages viewed *
Social share of page (via on-site share tools only) **
Print page (if you have a pretty-print button)
Save page (if your site allows internal bookmarking)

* The duration and page depth goals lend themselves to tiering; I’m thinking especially of a content-heavy site aimed at selling a lower-volume/higher-cost product or service such as insurance. There may be one point that correlates well with people who are interested but possibly in an early stage of shopping, and a higher threshold that correlates to people who are interested and closer to purchasing.

** The social tracking found in the Acquisition > Social > Plugins report cannot be used for goals, unfortunately, so having that nice reporting and a social share goal together requires duplicating your tracking in Events. Also, although there’s nothing in this list that this specifically applies to, if you want to use clickthroughs on internal promotions for goals, they must also be tracked separately as events. Those reports both seem to be in early stages in many ways, so hopefully they will eventually be options in goal setup.

De-Anonymizing

Create site account
Sign up for email list
Request catalog
Initiate online chat
Submit contact form
Review product/content
Comment on blog post
Log in to account

Content Marketing for offline goods/services

[see also De-Anonymizing]
Submit inquiry form
Use store locator page/function
Subscribe to blog (via on-site functionality)
Register for course/e-course/webinar
Download free materials/coupons
Request gated materials/coupons
Watch videos (begin playing and/or watch till end)
Other actions promoted by marketing campaigns (enter contest; answer survey)

Ecommerce *

View product page
Take “more information” actions (view alternate photos, associated videos or informational documents, nutritional info/size chart/technical specs, etc)
Request notification for out of stock/forthcoming product
Add product to wishlist
Add product to cart
Add second (third, etc.) product to cart **
Act on upsell or cross-sell prompt
Initiate checkout
Additional checkout benchmarks as appropriate
Complete purchase

* Why would you want to duplicate ecommerce tracking outside Enhanced Ecommerce? To combine EEc tracking with non-EEc tracking, or to see particular actions in a different way than EEc allows (e.g. add to cart outside the context of Product Performance or Product List Performance).

** Your add to cart events would need to be distinguishable based on the number of items already in the cart, but if your margin on multiple-item orders is significantly better than on single-item orders this may be worth tracking.

Note that if out of stock notifications, product adds to cart, and product adds to wishlist are all tracked as events, you can combine two or three of them into a single “expression of product interest” goal. How’s that for macro-level?

Last thoughts

There may be more than 20 goals listed above that are relevant to your website, and they may still not cover everything you need to be tracking. The list is just a starting point.

To figure out what your goals should be, the first question to ask is, “what actions can a visitor take on my site?” Then, “what pages do I especially want a visitor to reach on my site?” To thin the list down, ask “Does this action/destination contribute directly to my business’s success? Would I spend money to try to make this happen more?” “Success” could mean financial success or hearts and minds; it is the directness that you want to worry about more (though – speaking from experience – it doesn’t much matter to win hearts and minds if you don’t have enough capital to continue to exist).

Expect to take a couple of sessions to choose and organize your goals, and remember that although you can’t delete goals once you’ve created them, you can completely repurpose them so they bear no resemblance to their previous state (one advantage to that: you can edit the names of your goals with impunity if you decide they aren’t clear). There will be future posts here about using the information GA gives you about goals in various contexts.

Dart board by TeroVesalainen via Pixabay.

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We’ve discussed why you might want to delay sending product impression data to Google Analytics via event triggering, so that your product impressions are actually reflective of products appearing onscreen. However, that means you are adding event hits to your GA total hits, so ideally you will only send impressions as events when you truly need to. If you’re sending a product detail impression or a promotion impression for a banner at the top of the page, it makes more sense to send the EEc data as payload on the pageview tag (yes, tag – I’m assuming you’re using Google Tag Manager).

The preferred way to give the details to GTM is in the datalayer, but that requires all the EEc information be present in the page in the appropriate syntax upon page load, and sometimes that’s just not practical. However, you can provide the data in a variable instead – see Google Support’s basic Ecommerce Tracking article for as much as Google has to tell you on the matter; the full developer documentation doesn’t say any more.

Basically, you enable Enhanced Ecommerce features but do not check “Use Data Layer.” Instead you can create a GTM custom JavaScript variable that the tag will read from as though it is the datalayer (so a small caveat: this is incompatible with using the datalayer in the same tag, but other tags firing on the page can use the datalayer even if the pageview tag is reading a variable). That variable has to return the object you would otherwise push into the datalayer.

The key to this working, of course, is that even though the tag will fire at page load, you can scrape the page’s contents to construct your datalayer object just the same as if you were pushing to the datalayer to trigger an event (as we did when adding campaign tracking data recently).

Plan B image by sciencefreak on Pixabay.

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Just a little bit of special syntax for describing patterns can greatly increase the flexibility of your filters in Google Analytics. This post is to give you that bit.

What are we working with?

In Google Analytics you can filter using what I’ll call the basic filtration box, that input box with the magnifying glass button above the table of data, and the advanced filtration area which opens if you click the “advanced” link next to the basic filtration box.

I’ll assume in this post that we’re looking at my craft blog’s analytics, specifically the Behavior > Site Content > All Pages report, with the default primary dimension of Page.

The basic filtration box will give you generic pattern-matching: typing “crochet” will give you all URLs that have “crochet” anywhere from the beginning to the end. In the advanced area you can further specify that the URL begin with, exactly match, or end with your search string. In both locations you can use regular expressions.

Regular expressions are a way to describe a pattern to be matched. In full generality the language is extensive and can express very complex patterns. We don’t need the full language (and GA doesn’t support all parts of it anyway), but a little RegExp goes a long way toward easily filtering to the data you’re interested in.

Your first batch of syntax

Regular expressions work by having a collection of reserved characters, symbols that hold special meaning in the RegExp context.

The most useful in GA is | (pipe), found above the return key along with backslash. It means “or.” For example, I did a series about embroidery on crochet where the introductory post’s slug is embroider-crochet and the later posts’ slugs begin embroidery-crochet. I can capture both together with
embroider-crochet|embroidery-crochet

Portions of a regular expression can be enclosed in parentheses. This does nothing by itself, but can be combined with other operations. Enclosing an “or” expression in parentheses lets you make it part of a longer expression. This lets me shorten my previous filter, such as to
(embroidery|embroider)-crochet

Since regular expressions are their own singular option in the advanced filters, you have to use RegExp symbols to get “begins with,” “ends with,” and “exactly matches” filters (unless otherwise specified RegExps match like “contains”). Preceding your expression with ^ means “begins with” and following your expression with $ means “ends with.” Using both gives you “exactly matches.”

For example, if I filtered by /embroidery, I would get both posts in the embroidery category (they begin with /embroidery) and the posts in the “embroidery on crochet” series (which contain /embroidery but begin /crochet). To limit myself to posts in the embroidery category I can filter with ^/embroidery. If for some reason I wanted to filter to just the main blog page, which shows up as /, I could filter with ^/$.

Summary

exp1|exp2 : matches strings matching exp1 or exp2
^exp1 : matches strings beginning with a match to exp1
exp1$ : matches strings ending with a match to exp1
(exp1) : allows exp1 to be part of a longer pattern

Special characters versus ordinary characters

What if you need to use a reserved character literally? Very few reserved characters would ever appear in a URL, but they could in page titles and elsewhere.

There is a straightforward means to get your regular expression to interpret a character as the ordinary version and not the special RegExp version: precede it with a backslash. This is called escaping the character. For example, \( and \) get you literal parentheses.

Characters that need to be escaped are: \ ^ $ . | ? * + ( ) [ {

I have a Related Posts plugin on the craft blog that adds query parameters to its links. If I put /?related into the filtration box, it wouldn’t give me what I was expecting. The ? needs to be escaped: /\?related.

Cautionary notes

In the basic filtration box, you always need to escape reserved characters since it assumes you’ve typed a regular expression by default (though GA is smart enough to interpret a lone or leading ?, say, as a literal character – meaning in our last example filtering on ?related without the / would work just fine).

In the advanced filtration area, the match type drop-down must be set to “Matching RegExp” for the filter to be interpreted as a regular expression. In that case you must escape special characters, but in any other case the backslash will be interpreted literally and break your filter.

A second batch of syntax

What’s above may meet all of your needs. However, you may find situations in which you can’t quite get where you need to be with pipe, parens, caret and dollar sign, or where filters based on those are cumbersome.

The wildcard

A period in a regular expression will match any single character. For example, /page/./ will match /page/2/ but not /page/10/. /page/../ will match /page/10/ but not /page/2/, unless it happened to actually be /page/2//. Since I know my data doesn’t include any URLs with double slashes, I can see ultra-deep dives into content by filtering on /page/../ to get only pages 10 and up.

Repeats

Instead of typing some large number of periods to match a longer string that varies, we can use characters that indicate repetition. This also allows us to match when the varying string does not always have the same length.

Repetition is indicated by one of three “suffix” characters: question mark, asterisk, or plus sign. They mean, respectively, 0 or 1 repeat, 0 or more repeats, 1 or more repeats. For an example:
A.? matches A, AB, A5; does not match ABC, AB12
A.* matches A, AB, A5, ABC, AB12
A.+ matches AB, A5, ABC, AB12; does not match A
(the lists of strings matched or not matched is representative, not comprehensive)

Going back to the page number example, I’d like to look at engagement with pages 2 and later of all category archives. I know the URL structure will be /category/[category-name]/page/[number]/, and that the part from “page” on doesn’t exist on the first page.

Basically I need /category/ and /page/ with something in between, so here is my RegExp:
/category/.+/page/
.* could be used interchangeably with .+ here, because there won’t be a match to category//page.

All three modifiers – ?, +, and * – can be used on any character, not just the period. This lets us simplify our “embroidery on crochet” filter even further. The only different between embroidery-crochet and embroider-crochet is the y, so embroidery?-crochet will match both. It will not match embroiders-crochet, though either embroider.?-crochet or embroider(y|s)?-crochet would match all three.

Summary

. : matches any single character
? : indicates the part of the pattern preceding it can occur 0 or 1 times
* : indicates the part of the pattern preceding it can occur 0 or more times
+ : indicates the part of the pattern preceding it can occur 1 or more times

One little side note

All of my regular expressions so far have matched the case of the URLs I was trying to filter down to. By default, though, Google Analytics makes matches in a case-insensitive manner, meaning “thread” would match “Thread” and “THREAD” as well as the all-lowercase version. This generally is a helpful simplification but if capitalization is meaningful for your site, be aware you can’t filter for it simply by capitalizing in your RegExp.

The full reference list

Characters that need to be escaped (preceded with a backslash) to be interpreted literally:
\ ^ $ . | ? * + ( ) [ {

Coffee photo by miheco on Flickr.

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Just a quick tip this morning.

Suppose you have incoming traffic that you’d like to track as though the URLs were tagged with UTM parameters. And suppose you use Google Tag Manager to send data to Google Analytics. You might be tempted to tack a query string onto the URL in the “page” field, especially if you’re already doing something to the “page” field (e.g. cleaning out potential PII).

However, you might also find that doesn’t work worth a darn, despite seeing numerous tutorials online that indicate it works great – at least for parameters like search term. In that case, remember that setting the “page” field is but one example of directly setting any field you should so desire – including campaignName (utm_campaign), campaignSource (utm_source), campaignMedium (utm_medium), and any other campaign-related fields that are relevant.

Edited to add: If you are a heavy GA API user like me, it is worth pointing out that the field names you enter into GTM are not the API names (e.g. API pageTitle is just title in GTM). The analytics.js field reference has all of the applicable names.

In short: don’t add UTM parameters to the URL in GTM; add campaign data directly to the pageview GTM sends to GA.

This was a puzzle because searching for help brought up so many irrelevant results. Hat tip to Lunametrics for cracking it for me, once I finally found their post!

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