Posts Tagged ‘beginner’

May 27


Every now and then, we like to get “back to basics”. We still find established, experienced clients making simple mistakes that could easily be avoided and corrected using basic features already available in Google Analytics. One of them is properly using annotations – basically taking notes on different events (internal or external) that impact your site. These “sticky notes” might seem insignificant, but can often be a life-saver, providing insight as to why your data sometimes looks the way it does, especially anomalies or outliers.

Let’s talk about some strategies and best practices as to when and how to create valuable Google Analytics annotations.

What Are Annotations in Google Analytics

In early 2010, Google Analytics introduced annotations. Annotations offer a simple way to track notes in the Google Analytics reporting interface by date, so you can mark important events based on that may have impacted your data in otherwise seemingly inexplicable ways. In this way, it can explain reasons for jumps in the data to your entire team (if shared with everyone) that otherwise may be unclear.

To create annotations, simple go to any report and click the down arrow on the tab at the bottom.


Click “Create New Annotation”. Enter the date of the event and a small note about what happened. Choose if you’d like the note to be private or public.


Viola! Annotations are indicated by the tiny little talking bubbles at the bottom. To see the details, click the “down arrow tab” again for a list of annotations. The notes stay is available on any report in case your dissecting the data, see something weird, and need some insight into what happened that day!


The Benefits of Using Annotations

There is a spike in your data, a sharp increase, a drop, flat-line, etc., and you have no idea why. Wouldn’t it be nice to have an clear explanation or clue as to why any of this happened?

Imagine the following scenario.


The traffic for your company’s most valuable landing page died for 2 weeks. Someone’s paycheck is about to get cut!

You’re the marketing manager and you have a meeting with your CFO in 5 minutes. Sure, you could spend hours combing through emails, trying to figure out last week if your development team made an update to your site that tanked ecommerce. Luckily, you annotated exactly on that day that your developers switched to Google Tag Manager. You check with them, and they forgot to publish your new version of Universal Analytics code. You check the bank account, and sure enough, the money is still coming in, it’s just the data is missing. (Phew!)

Another example might be that an influencer shared your page to 1,000,000 followers, and for 2-3 days, your traffic has increased by thousands of visits. For something like that, there is no email paper trail that can lead you to the cause, and now, you’ve lost a potentially valuable partner that has a genuine interest in you that could help you blast your next campaign. It would have been best to “sticky note” or annotation right when it happened.

How to Use Annotations: 5 Tips on What to Annotate

1. Be explicit.
There’s nothing more frustrating than an incomplete clue to a burning mystery. “Blog Post shared”. What the hec does that mean? Who shared it? Which post? The worst part is I don’t understand my own note! If you’re notes are mysterious, you’re wasting your time creating it in the first place if no one’s going to understand it. While you only have a handful of characters (160), be as detailed as possible – it’s plenty of room to get specific points across.

2. Keep in mind who will be reading it in the future.
In the cases of shared annotations, you aren’t the only person who will be reading these notes. Your analysts, marketing team, etc., will be reading them and potentially using them for analysis and insights. For example, chances are if you use personal abbreviations, they’ll be interpreted in a way you didn’t intend. So when you wrote “ICBINB” to mean “internet consultant Brian implemented new banner” your colleagues will be wondering why you noted “I Can’t Believe It’s Not Butter”. Make sure your notes are understandable to any one reading it without context.

3. Record marketing campaigns, online and offline.
As mentioned, many things can affect your traffic, and you want to know what those things are. Obviously online campaigns probably will. If you release an email blast to 1000 subscribers, if even 10% click through, that’s 100 extra visits, so you’ll want to know what caused that when you look at your data a month later. But what about a TV ad? A radio ad? Flyers you passed out at the bus stop? That could increase traffic too, and you obviously want to know what offline campaigns worked the best for you. Log as much as you can.

4. Record any update or issue to the site/app.
When updating your website, you QA furiously to make sure nothing breaks – not SEO, not Analytics. Unfortunately, best laid plans don’t always come through. If you’re not looking at your data regularly, a change to your site that affects your tracking code may be discovered late. At this time, usually you’re in panic mode, so minimize your stress by being diligent noting site updates. Usually, these notes can give you direction into exactly what happened and exactly how to fix it.

5. Record any external event that may affect you traffic.
In March, you meet Tim Cook on the street and give him your card. Next thing you know, Apple tweets your site to millions of followers. You think it’s awesome. At the end of the year, you’re analyzing how some of your campaigns are doing and it looks like for some reason March traffic skyrocketed. You want to do that again! You drill down deeper, turns out one day spiked your data, but you can’t remember what happened that day! If you had annotated that you met Tim Cook and that he tweeted, you could filter that day out for a more accurate trend.


Hope that helps and gives you a new appreciate for such a basic but useful feature in GA. Have special uses for annotations? Leave a tip or trick in the comments!

Oct 23

desktop background google analytics regex cheatsheetI have a background in design. With powerful tools and applications like Photoshop, remembering all the commands can be a challenge. It’s almost 100% necessary to have keyboard shortcuts and cheat sheets if you plan to do heavy surgery with them. Despite your best efforts, some shortcuts and codes just never get memorized (I’ve been trying to remember the hex for red for 7 yrs now, just never has been a priority).

I saw this awesome Photoshop keyboard shortcut desktop background and thought, “How convenient!”

Google Analytics is a powerful tool too, but the commands (Regex’s and Keyboard Shortcuts) can be hard to remember. So for the analytics ninjas (or wannabe ninjas who haven’t memorized every shortcut yet) doing heavy data crunching and report making, we thought it might be cool to have one of those for Google Analytics! We know that there are already some out there, but we wanted ours to be really “pretty” AND could be used as a desktop background (for maximum convenience). This is only for the hardcore analytics ninjas that are willing to get rid of that Hello Kitty desktop pic, picture of your spouse and kids, or “Man of Steel” desktop background.

Click here to find your screen resolution!

DOWNLOADS: Google Analytics Regex Cheat Sheet

Black and White Printable (8.5in x 11in)
1024×1024 (iPad)

DOWNLOADS: Google Analytics Keyboard Shortcuts

Black and White Printable (8.5in x 11in)
1024×1024 (iPad)

Sep 23


You are a marketing manager and your online sales have never been better. Your greedy CEO calls you into the office. “We hit our quota this quarter, but next quarter, we want to blow the numbers out of the water! I need to buy a new yacht!”

How are you going to increase online sales when the numbers are already decent? You’re going to really need to dig deep and find ways to cut the data so you can uncover hidden “gems” of insights allowing you to further optimize.

Too many times we see business owners looking at aggregates. What do we care about most in eCommerce? Dollar Dollar bills. The metrics usually measured are things like “conversion rates” and “number of transactions”. This is important obviously, but you’re potentially missing ways of slicing the data that can show you more money.

For Practical Ecommerce, I wrote an article called “5 Ecommerce Metrics You Should Be Tracking“. I thought it would be cool to make a video series based on this.

Here is the first in our 5 part series:

Here’s Google’s developer topic on segmenting by category: Tracking Code: Ecommerce.

Jun 16

advanced-segment-logic-thumbWe just passed Father’s Day! Your client’s site sells silk ties and they’re expecting big bucks this season, so they increased their PPC spend. They want do some advanced segments to see how their U.S. and Canada paid traffic did.

We just read a great piece by Jesse Nichols on advanced segment logic and thought it might be a good idea, as part of our “Back To Basics” series, to expand on that a little.

Advanced segments are essential in filtering your data so you can dive deep and get clean insights. However, you might have to blow the dust off your old symbolic logic text books, cause this stuff can be confusing. Getting the logic wrong could mess up your data analysis and reports.

Hopefully, the diagrams we made here will help you remember your “and’s” AND “or’s”. Or, I guess it would be your “and’s” OR “or’s”…(Anyway, whatever…)

Advanced Segment Logic (Non-Exclusive)

When creating Google Analytics advanced segments, you can “include” or “exclude” dimensions.

We’ll go through the following:

  • Include “this” AND Include “that” (This and That)
  • Include “this” OR “Include “that” (This or That)
  • Exclude “this” AND Exclude “that” (Not This and Not That)
  • Exclude “this” OR Exclude “that” (Not This or Not That)

For non-exclusive dimensions (dimensions that can overlap, like place and kind), the following is a visual representation of how it will work. (We’ll go through exclusive dimensions – dimensions that don’t overlap, like two different places).


Let’s break this down in terms of the potential Google Analytics dimensions we’ll be looking at.
Let’s say:

  • “This” = “U.S. traffic”
  • “That” = “Paid traffic”

Include “this” AND Include “that” (This and That). You’re looking for traffic that is U.S. and paid. You might translate “Include U.S. Traffic and Include paid traffic” into normal English, “I want U.S. traffic and paid traffic”. The latter implies you want both, which is where the confusion happens. In actuality, you are looking for where they overlap. Thus, in our diagram, you are looking for the dark grey color.

Include “this” OR “Include “that” (This or That). Translating this into English would sound like “I want U.S. or paid traffic”, which sounds exclusive – “I want either U.S. or paid traffic”, which sounds misleading. You will be pulling up “either or” as well as the overlap. If the condition hits either case (which includes if it hit’s both), it will be included. In our diagram, this corresponds to the dark and light grey.

Exclude “this” AND Exclude “that” (Not This and Not That). “Not U.S. and Not paid traffic”. A little tricky. In traditional symbolic logic, “And” means both conditions need to be satisfied. You would think then that this is an overlap. Actually, you’re not getting rid of the overlap, you’re getting rid of both cases. That means anything that is from the U.S. will be eliminated as well as all paid traffic will be eliminated . Thus everything that is grey will be gone. You will only be looking at the orange universe.

Exclude “this” OR Exclude “that” (Not This or Not That). “Not U.S. or Not paid traffic”. To me, this is the most confusing one. Again, traditionally, you’re thinking “OR”, which is both data sets. That’s not correct.

To understand this one, let’s look at “include ‘this’ or include ‘that’ “ for a second. The logic behind this implies: The data set either has to have “this” or has to have “that”.

Along the same lines, for “exclude”, if we take that italicized part of the previous sentence and insert “NOT”, you get this:
The data set has to NOT have ‘this’ or NOT have ‘that’.
Meaning, if the data set doesn’t have one of them or is missing one of them, it checks out.

Let’s go through each color area we have and compare it to that last logical sentence.

  • Does the orange NOT have “this” or not have “that”? The orange doesn’t have either, so that checks out.
  • Does the light grey ‘this’ area NOT have one dimension? It doesn’t have ‘that’, so that checks out.
  • Does the light grey ‘that’ area NOT have one dimension? It doesn’t have ‘this’, so that checks out.
  • The dark grey area isn’t missing either one, it contains both! So it doesn’t check out!

Conclusion? This advanced segment eliminates the dark grey overlap! So here, you are looking at the orange universe and the light grey. In other words, you are filtering out U.S. Paid traffic.

Advanced Segment Logic (Exclusive)

What happens when you have dimensions that are mutually exclusive? For example, U.S. traffic and Canada traffic? (Another example of sets that don’t overlap is if U.S. has no paid traffic). Things become a little different.


Include “this” AND Include “that” (This and That). It’s impossible that one visit will fall under both locations (unless you have the power to teleport or go warp speed, in which case, you’d have to also be surfing the net during that time). Thus, you’ll get nothing from this segment, as they never overlap!

Include “this” OR Include “that” (This or That). This would be either U.S. or Canada traffic. Thus, you’ll get both (light) grey colors from this segment.

Exclude “this” AND Exclude “that” (Not This and Not That). Similar to non-exclusive dimensions or sets, you’re just getting rid of both. Thus, in our diagram, you’re left with the orange universe. Anything that is not either one.

Exclude “this” OR Exclude “that” (Not This or Not That). “Not U.S. or Not Canada traffic”. If we look at the non-exclusive diagram, you are getting rid of the dark grey overlap. Since there is no dark grey overlap in this diagram, you’re not really getting rid of anything. Thus, this is a moot segment when dimensions are mutually exclusive.


To analytics ninjas, the obvious segment you would want to create to analyze “U.S. paid traffic” is “Include U.S. and Include Paid Traffic”. When filtering for mutually exclusive dimensions like U.S. and Canada, “Include” and “OR” would be the way to go. Of course, there are a bunch of different combinations that will create different logic, but hopefully, these diagrams will help remind everyone of the basics to build on.

In any case, forget the ties, and get your dad something cool, like a camera or an iPad or something…