How Many AdWords Accounts Should I Use?

This is a really great question and, as simple as it seems, an important one to consider before getting started with new campaigns. AdWords implementation is, unfortunately, never straightforward so do yourself a favor and answer a few questions before you create that first account.

What Is Your Budget?

Typically, larger budgets require greater segmentation. If you intend to eventually give each of your business initiatives a significant portion of your digital budget, then it might be best to build account-level segmentation at this early stage.

A few examples that we have worked with might include segmentation for various product or service segments or domestic and international targeting.

How Do You Want Cost To Be Associated To Your Google Analytics Properties?

Whenever you establish the linking groups in Google Analytics, the setting that pulls cost and click data into GA, it will pull ALL of the cost data into that associated property. Because the AdWords data is a separate data set, there is no way to segment that cost prior to import unless you build multiple AdWords accounts then individually link them to the most appropriate properties for reporting purposes.

For example, if you have a B2C Google Analytics property and you import your cost and click data from a single Google AdWords property that represents ALL of your marketing initiatives, then your cost attribution will appear skewed in certain reports (unless, of course, you filter or segment your data in some way within the report).

How Much Access Should Particular Users Have?

Kind of a no-brainer, but if you want to ensure that certain users can only make changes in campaigns that they are responsible for, then you should consider multiple accounts with multiple users of varying access levels.

Another concern is that you may not want the team from Product A to know how much of the overall marketing budget Product B’s team is receiving this year. Using multiple accounts can alleviate “budget wars” in this case.

Can You Handle Organizing This Level Of Complexity?

One key issue you that you want to avoid while managing multiple accounts is having keywords that overlap across the account. This cause two problems: (1) lack of consistency in ad messaging and (2) increased costs overall.

Consider the following circumstance:

Both Account #1 and Account #2 are bidding on the keyword [ebooks] and are attempting to drive searchers into different experiences in order to complete different business goals. When the keyword is eligible to be triggered (i.e. someone searches for ‘ebooks’) AdWords will evaluate both accounts to determine which ad will win the auction, but because only one ad from any given domain can appear in search results, the ad with the highest “ad rank” (typically the highest bid) will win the auction.

Essentially, you would be creating your own internal competition and unnecessarily driving up cost. You also lose a bit of control over messaging.

Think of this same scenario for broadly-focused keywords. Which initiative gets priority for branded search or shared search intent? This should play a large role in how you structure your AdWords account(s).

RECOMMENDATIONS:

Prioritize the questions above to determine which what account structure is the right fit for your needs.

Option 1: Use One Account

If you are not concerned about sharing budgets with users and can trust them to not make edits in campaigns that are not their own, and if segmenting cost prior to importing into GA for more accurate attribution is also not a concern, then simplicity is usually best. Use one AdWords account and link it to all of your Google Analytics properties. Grant any users access as necessary.

Option 2: Use Many Accounts

On the other hand, multiple accounts is best if you are concerned with privacy and attribution. Managing the overlap, as described above, between the accounts will be more difficult but not impossible if you establish some rules prior to launch.

In this scenario you might have an account structure managed under a Google AdWords manager account (umbrella accounts used to manage multiple other accounts).

Your structure might look something like this:

Company MCC
> Company B2B
> Company B2C
> Company Brand (optional)

**Each account is nested under the MCC, aka manager’s, account. The optional “Brand” account would house keywords that overlap initiatives, such as branded search or keywords with a non-specific, broad focus that would be used to simultaneously promote multiple initiatives using features like ad extensions or through creative landing page testing.

Link individual accounts to the most appropriate Google Analytics properties, link the manager account to your Google Analytics rollup properties, and grant user permissions to the applicable accounts. BOOM! Now you have a thoroughly broken down series of AdWords accounts. Each one pushing cost data to a specific Google Analytics view, and each one now has the ability to accept only certain users if deemed necessary.

There you have it. Consider your reporting and management goals when establishing your AdWords account(s). If your comfort zone is more along the line of straightforward and simple then go with Option 1. If you desire more control and 100% accurate attribution modeling, then go for Option 2.


Google Analytics Power Reporting for SEO and PPC

Your neighbor tells you he is thinking about buying an electric car. Avoiding fossil fuels is important to him, but he is getting older—his 80th birthday is next week—and his kids don’t want him riding a bicycle any longer. Forget Uber, he doesn’t have a mobile phone. Plus, his barber moved across town and he needs a monthly trim of the few remaining hairs on his head.

He returns the next day with a Tesla S, the zero-emission sports car that goes 0 to 60 (mph) in 2.8 seconds, faster than a Porsche 911 Turbo and nearly every other street-legal car on the planet. The old timer wanted an electric and his new Tesla S meets the criterion.

Enter Google Analytics.

At some point, we told coworkers that we wanted a web analytics tool and create a Google Analytics account because it did all of the things we needed. And for years we (figuratively) drove that bad-ass sports car to the barber at 22 mph. We are the old man!

Let me be clear, I am the old man, too. I have a turbo-grade tool in Google Analytics, but each year I do an industry scan for the perfect search marketing reporting provider. I compare features, sit through sales demos, subscribe to 30-day trials. As trials expire and shoulders shrug, I continue driving Google Analytics in first gear.

That stops this year.

Search marketers at LunaMetrics are using Google Analytics the way it’s designed to be used. Here are some of the ways that we are doing weekly monitoring and monthly reporting without totally overwhelming our people or our clients.

Daily Monitoring

Google, Adobe, Hubspot… most analytics providers have apps that allow digital marketers to monitor performance from anywhere: your bed, your birthday party, your wedding. That doesn’t necessarily mean that you should.

Goal: Reacting to an extreme shift in any search channel.

Challenge: Keeping a finger on the pulse while still having enough time to eat, sleep, and bathe.

Solution: Alerts in Google Analytics

Alerts act like push notifications. “Hey, healthy person enjoying their Sunday morning, your conversion rate tanked yesterday so you should probably finish your breakfast and check on it.”

Keep in mind that these alerts are not always real time. They will not let you know the moment Kanye takes a selfie with your product and your server buckles under the weight, but you are more likely to know before Monday morning when your boss is waiting by your parking spot. Here are 55 Google Analytics alerts for your account.

Weekly Monitoring

Spotting trends save lives. Okay, that might be a touch extreme for your industry. Maybe spotting trends saves dollars and bonuses. Throwing yourself in front of something trending downward or maximizing the effects of something trending upward makes bosses and clients very happy.

Goal: Spotting trends in the act stage instead of the react stage.

Challenge: Knowing where to look and, well, remembering to look there.

Solution: Custom reports and dashboards in Google Analytics.

The guide to basic Google Analytics automation reviews dashboards with custom reports, which are wonderful ways to monitor performance without losing your life to it – see the Daily Monitoring section above.

Google Analytics dashboards are perfect for 60-second reporting and analysis: a summary of search conversions, revenue, return on ad spend, etc.

Monthly Monitoring

This is the big one. We do the bulk of our reporting at the monthly level, and the demands are higher.

Goal: Finding a tool that is easy to access, affordable to use, and broader than several channels.

Challenge: Having all of it in one place.

Solution: Google Drive integrations with Google Analytics.

Google Drive reports are not the prettiest girl at the dance – other platforms have cleaner interfaces with interactive charts – but she is the best dancer, and isn’t that most important? Read-only logins for bosses/clients, automatic daily refreshes, and the opportunity to fetch data from AdWords, Bing Ads, Search Console, social advertising, and more. You can even create handy tools like ad budget trackers to maintain monthly pacing. Looks like I need to apply the brakes!

A coworker tackled the how-to side of this topic far better than I can. Check out Sam’s post on connecting Google Analytics to Drive and supercharging reports with filters and segments.

Taking a Test Drive

Google Analytics can be your Tesla. Or your (more modest) Nissan. It has all of the things you need and many of the things you want. The SEM power reporting muscle is there; you just need to know how to unleash it.

Want to learn more about Google Analytics power reporting for SEM? Attend Andrew’s session this year at SMX West, SMX London, and SMX Advanced.


What Is Google Tag Manager? (And How Does It Work With Google Analytics?)

For quite some time, Google Analytics (GA) has been around to help you collect, process, configure, and report website and mobile app data that results in actionable insights. Then in 2012, Google announced the release of its new groundbreaking product, known as Google Tag Manager (Tag Manager or GTM).

In short, we love it. And we write about it often! Despite GTM’s usefulness, there’s still a lot of confusion about what it is, what it does, and how it’s different from Google Analytics. So, we’ve decided to dedicate this bit to dissolve the confusion.

Where People Get Tag Manager Wrong

A common misconception is that Tag Manager is the same thing as (or the latest version of) Google Analytics. This is not the case! In actuality, Google Tag Manager is a completely separate tool.

Breaking It Down

In short, Google Tag Manager is a user-friendly solution to managing the tags, or the snippets of JavaScript that send information to third-parties, on your website or mobile app. Adding other products to your site, including but not limited to AdWords Conversion Tracking and Remarketing, DoubleClick Floodlight, and of course, Google Analytics, is a breeze.

In more detail, GTM makes your life easier by simplifying the process of adding these JavaScript snippets to your website. Instead of updating code on your website, you use the interface to decide what needs to fire and on what page or what action. GTM then adds the appropriate tracking to your site to make sure it all works.

Google Tag Manager consists of these three main parts:

  1. Tag: A snippet of code (usually JavaScript) added to a page.
  2. Triggers: Defines when and where tags are executed.
  3. Variables: Used to receive or store information to be used by tags and triggers.

Before And After Tag Manager

Before Google Tag Manager, the JavaScript on your website or mobile app had to be hard-coded. In other words, you were forced to team up with developers to make even the slightest changes to your tracking. Need to add an event? Get in line behind the urgent site issues and routine maintenance. Or, if you’re the one in charge of updating your site, tracking certain links or forms may require wrestling with JavaScript/jQuery to get the exact thing you need.

Now, Tag Manager gives you a friendly user interface that walks you through creating tags step-by-step, which eliminates the need to have extensive experience with JavaScript. To get started, you add the custom-generated tracking code, also called the container tag, to your website or mobile app.

Afterwards, Google Tag Manager allows anyone with the appropriate user permissions to add, change, and debug tags for your website. You can use it to control and fine-tune what fires on your website while it delivers the JavaScript to your site for you.

Most importantly… You can take tagging into your own hands, and steer your tracking however you desire, quickly and easily, without those sometimes pesky backseat drivers (your developers).

So GTM And GA Aren’t An Old Married Couple?

Not necessarily. Google Tag Manager and Google Analytics are two completely separate tools, and can live independently of one another: You can use Google Analytics on your site by itself, just as much as you can use Google Tag Manager on your site by itself.

However, as our Technical Marketing Manager, Jon, always says, “Google loves Google.” Therefore, it should’t be surprising that they work very well together.

GTM And GA Working Together

Quite honestly, the possibilities of how the two tools work together are endless!

However, there are a few ways to use Google Tag Manager with Google Analytics that are commonplace. For instance, you can use GTM to send different pieces of data to Google Analytics, such as pageviews and events. Let me reiterate that normally, you would have had to add JavaScript on your site, but not when using Tag Manager.

Here’s an example:

For Google’s sake, we’ll show you how to send data to Google Analytics using Tag Manager. Let’s say that you need to track resource downloads on your website (pdfs, docx, xls). For tracking purposes, it’s important to know two things:

  1. How many people downloaded the file?
  2. What page was the user on when it was downloaded?

In this case, GTM allows you to easily set up a Click Trigger and a Google Analytics Tag to see what and where resources are being downloaded without needing to add any additional code to your site.

Furthermore, you can use Google Tag Manager triggers to dictate when this data should be sent to Google Analytics. To expand on our previous example, maybe you want to only send a virtual pageview to Google Analytics when a user clicks on a resource download link. If so, you can use Tag Manager’s triggers to specify these conditions.

7 Reasons Why Google Tag Manager Is Special

1. It’s F-R-E-E, Free.

Not to worry, it’s both free and awesome! Google Tag Manager has a multitude of robust features, including (but not limited to) usability, accounts and user roles, tag firing rules, and supported tags (Google, third-party, and custom HTML tags).

2. Do It Yourself

Insert the container tag once, make changes whenever you want without much hassle, and voilà! With the available debugging tools and preview mode, you can be sure of what you’re doing before you publish it.

3. Forget About Limitations

You can use Google Tag Manager with more than just Google products. Take a peek at the other predefined tags, such as Marin, comScore, AdRoll, and more! Can’t find the tag you need? Customize one! You can also add Tag Manager to not only your website, but also to your iOS and Android apps. You’re truly unlimited.

4. Cool Features With Google Analytics

Google Tag Manager makes it easier to implement some of the more complicated Google Analytics features, such as User ID tracking. User ID tracking gives you the ability to measure real users instead of devices. This provides more accurate data for you, which ultimately helps your users! It’s a win-win. Tag Manager also helps with common challenges in Google Analytics, such as Custom Dimensions, Cross-Domain Tracking for multiple sites that are tracked together in Google Analytics, and Enhanced Ecommerce that requires collaboration with developers.

5. Easily Track More Things

With so many great resources available on the web (and our own site!) it’s easier than ever to track things like YouTube videos on your site, print tracking, or AJAX form submissions.

6. Worry-Free Security

No need to worry. Google Tag Manager has all of the security features you need. One awesome feature is two-factor authentication that requires both your normal password and then a numeric code that you receive via a text message, voice call, or mobile app. You are also able to control the access by granting different levels of permission at both the account and container levels.

7. Debug Central

With debug options, built-in error checking, and version controls, you can rest easy knowing that everything you do with Google Tag Manager can be tested and debugged before it goes live.

When Can You Migrate To Google Tag Manager?

Any time is a good time to migrate, especially if you haven’t already upgraded to the latest version of Google Analytics (Universal Analytics), then it would be a great opportunity to also migrate to Google Tag Manager. Check out the important migration tips and tricks linked below that you should put into practice. Migrate whenever you feel you’re ready to take advantage of its many awesome features!

How Can We Help?

Are you ready to try it out? We are a Google Tag Manager Certified Partner that is here to help you implement Google Tag Manager and Google Analytics through GTM. You can reach out to us, check out some of our other blogs on Google Tag Manager, check out our GTM Book and GTM recipes, or find out when our Google Tag Manager trainings are coming to you!


What’s Premium About Google Analytics Custom Funnels

As web analysts and marketers know, analyzing and understanding user behavior is so much more than reporting on overall users and pageviews.

There are tools in the Google Analytics interface to help understand behavior like the Navigation Summary and Entrance Paths, but both are limited in terms of the scope of steps and stages. Even the Behavior Flow report, showing a complex map of user navigation, really just scratches the surface of behavior analyses. Using the funnel visualization or sequences with advanced segments are also options, but a new feature may prove to be one of the most powerful (and easiest) tools yet!

Custom Funnel Reports is the newest available reporting feature released by Google Analytics 360. It is a custom reporting template that allows you to experiment and create funnels out of nearly any user behavior and action on your site. You don’t necessarily need an explicit stepped process with pages belonging to a strict path. In fact, using custom funnel reports becomes more valuable when you think of ways to explore the data.

The view that you are in must be within a Google Analytics 360 property. If you are not currently a GA360 customer, you will not have access to this type of report but can follow along with the screenshots! If you’ve used Enhanced Ecommerce features like Shopping Behavior and Checkout Steps, you will be familiar with the look and feel of the end report.

Creating a Custom Funnel Report

Like other custom reports, the first step is navigating to the Customization tab in the topmost menu and choosing New Custom Report. Once in the creation screen with all of the custom report settings, you should notice that there is a new button in the Type section, Funnel.

Then, you can choose what sort of analysis you are looking for. If you are more focused on sessions, choose “All stages must occur within the same session.” If you want a user-level, choose “Different stages can occur in different sessions.” This option means that if a user completes a step one day and completes the funnel the next, the user will still be counted in the funnel analysis and not look like a drop-off.

The section Funnel Rules is where the steps, or stages, are defined based on Google Analytics dimensions. You may already have some ideas for pages that you are interested in creating a funnel report for but don’t limit yourself to just pages!

The best part about these reports is that you can use any dimension in Google Analytics, including custom dimensions and ecommerce dimensions. You can even use different dimensions for different stages or different dimension conditions in the same stage as well.

This can be used to create a funnel solely from events. Maybe we have a one-page form with events that fire on the individual form fields and we want to track drop-off within that form. We wouldn’t be able to use the goal funnel visualization because it is a single URL.

Below is an example of a Custom Funnel Report based off of fields in a lead generation form. The settings for the individual steps would be based of of event category, action and label:

This may spark ideas about creating event-based funnels around actions that you may already have implemented like scroll tracking, video interaction or even timing events! The limits for Custom Funnel Reports are currently a maximum of 5 rules per stage and 5 stages total.

Custom Funnel Reports can also be used to analyze user actions along with content. For example, at LunaMetrics we might want to analyze the closed funnel of users who view blog content, then view our services page, and finally take action to contact us. Not only can we analyze the volume of users who flow through the stages, we can create segments based off of the stages and drop-offs. In this case, I might want to target the users who left the funnel before completing the last action of submitting a contact form to create an advanced segment or remarket to this very specific audience.

Custom Funnel Reports vs. Funnel Visualizations

Custom Funnel Reports don’t have the same behavior as the funnel visualizations and work differently. Unlike the funnel visualization report, there are no backfills, it can be used on historical data and you can add an advanced segment to the reports (there is a limit of only one at a time).

However, you do have similar options such as choosing whether the funnel is open (where a user can enter the process at any step) or closed (where a user must hit the first step to be included in the funnel). Custom funnel reports are also visually different and are interactive.

Custom Funnel Reports vs. Sequences in Advanced Segments

Custom Funnel Reports are similar to advanced segments in that you are free to use any and multiple Google Analytics dimensions. Both also provide the option of specifying whether the next step should be immediately following the previous step or not.

The biggest difference between these two tools is that Custom Funnel Reports allow you to interact with and re-engage your users based off of where they entered or dropped out of the funnel with remarketing. Also, keep in mind that using any type of advanced segments in the standard version of Google Analytics will trigger sampling if there are more than 500,000 sessions in the range of the report and flow visualizations will trigger sampling at 100,000.

The GA360 Custom Funnel Reports provide a new way to analyze behavior with Google Analytics. Moving toward user-centric analysis, the flexibility lets us analysts and marketers think more about the journey and story of people using the site in a more focused and insightful way.


Integrating Google Analytics and Salesforce – A 30,000 ft View

Salesforce is one of the most popular CRMs available today. Many teams use Salesforce heavily for reporting and analysis. The ability to model the data in Salesforce to fit any organization’s needs is particularly powerful. Many of our clients and Google Analytics training attendees use Salesforce and want to merge data it contains with their Google Analytics data. Thankfully, Salesforce offers a robust set of features to let us integrate the two. The requests I hear most often are:

  • Can I see Salesforce data in Google Analytics, e.g. Industry, Customer Type?
  • Can I see Google Analytics data in Salesforce, e.g. Source/Medium, Campaign Information, or Goal Completion data?

The good news is, you can! Here are four approaches we might take to do this:
1.) Adding hidden fields to carry in data to Salesforce
2.) Creating a custom Salesforce Trigger and sending the data to Google Analytics
3.) Periodically querying the Google Analytics API and sending that data into Salesforce
4.) Periodically querying the Salesforce API and sending that data into Google Analytics
5.) NEW – Salesforce integrates with Google Analytics 360 and sends back Lead/Opportunity Changes

Today, I’m going to cover four different models for sharing data between these services, as well as why you might like to do each.

Method #1: Adding Hidden Fields

This is the oldest-school way of bringing Google Analytics data into Salesforce: you add Custom Fields to one of your Objects, create a Web Form for that Object, and then populate those hidden fields using data about the user. When the form is submitted, the data is stored in Salesforce.

One of the most common ideas – use the data stored in the __utmz cookie to see the current user’s Source/Medium and Campaign information. If you’re using Universal Analytics, there are some hoops you’ll have to jump through: E-Nor has one method that may work for you, and I’ll discuss our method in a future post.

The hidden form field method is the simplest way to get Google Analytics attribution data into Salesforce, and also provides the simplest type of insights – essentially, last non-direct click attribution. For companies with longer sales cycles, this might not be the most useful data in the world, but for more demand-generation based folks, this can be super helpful. Again, with some customization, this pattern can be extended to provide more useful information for you to leverage. We’ll cover that in a later post.

Method #2: Creating A Custom Salesforce Trigger

Triggers are a feature in Salesforce that mimic triggers you might have used with database software. Essentially, triggers are conditional rules that you can set up to fire when certain actions take place. This includes, in Salesforce, sending data to outside services. In this way, you can configure Salesforce to do really awesome things like:

  • Manage User IDs for your clients
  • Update user data in GA when important actions occur, e.g. a big sale closes
  • Fill in extra dimensions about users from your CRM into GA, like Industry or CLV

There are some limitations in terms of what Triggers can do – you can only use 10 @future calls (required for sending data to services outside Salesforce) per transaction, and you have a limit of 200 @future calls per Salesforce license, so you may need to be choosy about what you send into Google Analytics with these methods. There are great resources available on how to optimize your code to work within these limits.

This approach is great because you can get near-real-time updates to your Google Analytics data, which can help avoid any data quality headaches.

Method #3: Periodically querying the Google Analytics API and sending that data into Salesforce

Google Analytics has a robust and well-documented API for accessing data from your account. You can take advantage of this and create scripts or services that periodically poll Google Analytics for specific pieces of data, and then submit that data to Salesforce via the REST or Bulk APIs.

Salesforce has a handful of really interesting APIs for all different application needs, which you can check out here. In order to take advantage of these APIs, you’ll need to create a Custom App in Salesforce and build a service on your own server somewhere to orchestrate things.

This approach is how we can bring data from Google Analytics into Salesforce that maybe isn’t available when a form is submitted. For example, we may want to know the first source/medium of a particular visitor’s visit history. With a client- or user-specific key in Google Analytics, we could retrieve that data on a periodic basis and upload it to SalesForce for use in our CRM.

Method #4: Periodically querying the Salesforce API and sending that data into Google Analytics

Similar to Method #3, we can also pull data out of Salesforce using its APIs in order to upload that data to Google Analytics, either using the Measurement Protocol or programmatic Data Import. This method still requires a Salesforce app for authentication and a service on a server to orchestrate things.

This approach is how we can bring data into Google Analytics from Salesforce without using Triggers.

Method #5: Integrate Google Analytics and Salesforce

Announced in 2018, Salesforce and Google Analytics 360 have teamed up to make this process even easier! In a nutshell, connect your Google Analytics 360 account to your Salesforce account and make a small number of changes on your website to enable this feature, included with the with your Google Analytics 360 license. Once that’s finished, Salesforce will send data back to Google Analytics, importing changes to Leads and Opportunities and connecting to the original user that submitted a lead/contact form.

Take a look at our Google Analytics 360 and Salesforce Integration post which describes this process in full detail.


Interested in getting started? We can help. Get in touch with us about integrating your Salesforce and Google Analytics data today.

Is your organization sharing data between Salesforce and Google Analytics? Are you doing things differently? Share your models in the comments below.


Google Sheets and Google Analytics Part 2: Segments and Filters

If you’ve ever struggled with how to pull quick reports comparing multiple properties  or how to customize and automate dashboards with your data, the Google Sheets Add-On is worth looking into. It’s free, it’s simple and it allows you manipulate your data outside of the Google Analytics interface. The introduction is here to get started in case you haven’t used it before. If you have completed that quick-start guide, read on for the second guide to using segments and filters.

The Filters field in the report set-up is similar to other fields. If you only need one dimension to filter on, it is constructed the same way as the other fields. For example, to look at only blog pages I would add the following to the field:

ga:pagePath=~/blog/

‘ga:pagePath’ is the dimension, ‘=~’ is the operator for ‘matches’ and ‘/blog/’ is the subdirectory that I want to filter on.

To add more than one filter, we need to first think about how we want to filter the data. Should it be an ‘and’ or an ‘or’? In terms of the reporting API, just remember the following:

Or = Comma

And = Semicolon

If we want to create a filter showing blog pages or contact pages, I would use a comma and it may look like this- ga:pagePath=~/blog/,ga:pagePath==/contact. However, if we want to filter data to look at only blog pages and only users from an .edu network it would look like this- ga:pagePath=~/blog/;ga:networkDomain=~.edu.

The syntax can be tricky, so there’s a handy guide for Filters with the API to help you.

Subsetting your data into specific segments of sessions or users is one of the most valuable tools as an analyst. To use advanced segments with the Google Sheets Add-On, you have a couple of options.

Option #1

The first option is appropriate if you have already created your advanced segments in Google Analytics. For example, let’s say I have a simple advanced segment that looks at users from an .edu network domain (showing that they may be on a campus. The set-up in the Google Analytics interface would look like below:

If it is already created, one way to get the segment’s ID is to use the Query Explorer. In the segment dropdown menu, the ID will show automatically and you can copy-and-paste it right from the page to Google Sheets.

There is also a trick to getting the ID without using the Exporer or the API. In Google Analytics, apply your segment so that it is the only segment. In the URL, you should see something like below at the end:

/%3F_u.date00%3D20151001%26_u.date01%3D20151031%26_.useg%3DuserhSiQKwf1RVqrtiVO54rx7Q/

The last part after ‘user’ is the segment ID.

Option #2

Segments can also be added while you are setting up your report in Google Sheets. The syntax is slightly different that the regular reporting fields. Using the same example, if I wanted to only look at sessions from an .edu network, I would go to the Segment field and build it like below:

users::condition::ga:networkDomain=~.edu

The important thing to remember is to specify the scope of the segment (users or sessions). And again, there’s documentation on Segments with the API to help you out!


The ease of adding segments and filters in the Google Sheets makes the add-on one of the quickest ways to use the Core Reporting API. For all the dimensions and metrics available with the API, check the reference here.


Getting the Most Out of Your LunaMetrics Training

You’ve decided it’s time to learn more about Google Analytics, or Ads, or both. You’ve signed up for Bounteous training. Now what?

Read on for tips on what to do before, during, and after the training to optimize your learning experience.

Before the training

1. Get access to an account

For Google Analytics, get edit access at the account level if possible and create a test view. For Ads, get standard access or know who has it.

For a Google Analytics test view, simply copy the main production view and put your name on it. Or you can have someone else create a test view for you and give you edit permissions at least for that view.

Create the test view as far in advance of the training as possible, so you have some data to work with. If you don’t see data but think you should, verify that GA tracking code is on your site. And if none of that made sense to you, we’ll talk more about Views and the GA Tracking code in our Google Analytics 301 class!

2. Come with questions

Write a list of questions ahead of time and bring it with you. Look at your Google Analytics data or Ads data and make notes about what you can’t find or what seems confusing.

Other sources of questions: Email or ask your team or your boss what they want to know about your websites (or apps) or campaigns. Ask if they have questions about using Google Analytics or Ads. What can you learn that will help them?

Read our course descriptions to see what topics we’ll cover in your training. Watch the Analytics Academy videos on the GAIQ Prep page. These may also prompt questions for your list.

3. Think about business objectives

Give some thought to overall business objectives before you arrive, because we’ll be asking you about them during the training. Think about objectives for your company’s digital presence, too.

We’ll describe how to relate business objectives to digital objectives, how to set up Google Analytics and Ads to measure those objectives, and how to find the data and use it.

4. Bring the right people

What is your role in your company and what will your responsibilities be? Read over those course descriptions one more time and make sure you have the right people in the right courses. Take our quiz to see which course you should be taking.

The more technical classes like Google Analytics 301 and Google Tag Manager Workshop will give specific recommendations for changes to make to your website. If there’s a person or a team that handles this for your company, ask them if they should attend as well.

5. Keep your confirmation email

And double-check the training dates. Your email is your ticket and receipt, and shows the courses you selected when you registered.

The “Notes” section of your confirmation email includes helpful info about how to get to the training, where to park, and other important details.

To find out about cancellation policies, meals, what you should wear, and so forth, read our Training FAQ.

During the training

The week has come, get ready to learn! We know how hard it is to leave the office for an extended period of time, so we’ve included breaks and an extended lunch to allow time to check in back home. Here are a few reminders:

6. Bring a laptop and take notes

Make sure you bring a laptop and power cable. Get the password if your laptop is a loaner.

It’s easiest to navigate Google Analytics and Ads and take notes on a laptop, compared to a tablet or other device.

You’ll get a copy of all the slides to review later, so while you’re taking notes, write the slide number at the same time.

7. Ask questions

Come early, stay late, get some personal attention at breaks or lunch. Pull out that list you wrote ahead of time and get answers.

Don’t be afraid to speak up during training, either. Someone else may have the same questions.

If we don’t cover something you’d like to learn, let the trainer know.

8. Be present

Focus on the training, even set your email away message to keep distractions to a minimum. We’ll take breaks to give you time to check in with the office, stretch your legs, and get out of your chair.

Network with other attendees. Ask them how they handle campaign tagging or which attribution model they use. You probably have a good deal in common, and getting out of your seat will keep you motivated and focused in the long run.

After the training

Phew! You made it! The courses are jam-packed with material, so it’s important to keep the momentum going and follow through with everything you’ve learned.

9. Take action

Audit your account for best practices. Use our 12-point checklist for Ads, or our GA 301 site health checklist, and then act on what you find.

Debrief your team about what you learned while the info is still fresh in your mind. Discuss new ideas you have about what to set up, measure, or improve.

10. Keep learning

Use your “Get Out of Jail Free” card to email us after the training for any question that crops up later. Follow your trainer(s) on Twitter.

We provide you with many resources during the training, including a flash drive with the training slides, handouts, and more. We talk at the end of each day about how to continue your education with specific links to industry blogs, Google resources, and certifications. Read this blog! Our blogs often come directly from training topics.

Recap

That’s it! Follow our tips to make sure you’re prepared and focused during the training and invigorated and successful after the training.

1. Get Account Access
2. List Questions
3. List Business Objectives
4. Bring the Right People
5. Keep Confirmation Email
6. Bring Laptop
7. Get Answers
8. Focus on Training
9. Take Action
10. Keep Learning


Google Analytics 10M Hit Limit: What Are My Options?

If you’re reading this blog post, chances are you’ve received a message from Google Analytics that felt a bit like a detonating bomb:

Your data volume (xM hits) exceeds the limit of 10M hits per month as outlined in our Terms of Service. If you continue to exceed the limit, you may lose access to future data.

Take a deep breath. You have some options, and we’ll talk about them here.

As the Manager of Analytics here, I want to share with you our approach to this problem and how we’re handling it for our own clients.

What does the message mean?

Is our data kaput?

The free version of Google Analytics allows for up to 10 million “hits” per month, per property. (It’s in the Terms of Service you read very closely when you signed up for GA.)

What is a hit? A hit is generally a pageview or an event. A single session can have many, many hits, depending on how many pages your users look at and how many custom events you choose to fire on those pages. Every hit counts, so make sure you’re not accidentally looking at Sessions.

And what is a property? Your GA data is sent to a particular “UA” number or property, via the tracking code that you placed on the website itself. Whether you’re using JavaScript on your site or Google Tag Manager, you’re sending data to a property, where the data is collected and processed.

So you can have up to 10M hits, per month, per property, before Google drops the bomb.

It appears that the worst offenders are being notified at this time, but you should be aware that any Google Analytics property exceeding 10M hits is technically in breach of the TOS, so you should check where you stand now.

How do we know how many hits we have?

In Google Analytics, look under the Admin, under Property, and click Property Settings. Scroll down and find the Property Hit Volume. You will be able to see your hits from yesterday, the last 7 days, and the last 30 days.

You’ll also see a message here if you have exceeded your limits:

Warning! You are exceeding our limit of the allowed volume of 10M hits/month to this property, as outlined in our Terms of Service. If you continue to exceed our hit limit, you may lose access to this data.

What’s the penalty?

At this time, we really don’t know. This Google page says that “there is no assurance that the excess hits will be processed.” That’s not good, but it might imply that your data would still be accessible. But then there’s this nugget: “If the property’s hit volume exceeds this limit… you may be prevented from accessing reports.

Whatever the penalty, it’s obvious that the days of ignoring GA’s data collection limits innocently (or otherwise) are behind us.

What are the options?

Your team’s plan of attack depends on how you choose to answer these three questions:

  1. What is my available marketing budget?
  2. How greatly am I exceeding the 10M/month/property hit limit?
  3. How important is comprehensive data collection to me (i.e., would a “sample” of sessions suffice)?

There are two major options you’ll have to choose from: Upgrading to Google Analytics 360 or altering your data collection. I’ve outlined the different approaches below.

Google Analytics 360

If you have budget available, the safest and most immediate way to maintain access to your data, while not sacrificing data collection, is to purchase Google Analytics 360. This could seem like an extreme option from a budget standpoint, but there are several reasons why you should consider GA360 beyond just the data question.

Let me start back at the beginning. Google Analytics 360 is the pay-per-year enterprise version of Google Analytics, that comes with three huge benefits over the free version of Google Analytics.

How much more data do I get?

Google Analytics 360 comes with much greater data limits, allowing for up to 1 billion (with a “B”) hits per month per property. (There are also higher pricing tiers for websites that exceed 1B hits.) To address that much data, GA360 comes with a variety of features to help keep the interface running quickly and without sampling (like Scheduled Unsampled Reports and Custom Tables) as well as helping you access your data in ways not available in the free version (BigQuery integration).

What kinds of features are included?

In addition, there are a variety of features and integrations that are available only to GA360subscribers, including:

  • Data-driven attribution modeling – GA360 will determine which marketing channels are most effective at driving conversions, based algorithmically on the performance of your particular mix of marketing channels. The free version uses basic models and only looks at conversion traffic, but GA360 uses 100% of your traffic and advanced algorithms!
  • DoubleClick integrations – Are you using DoubleClick Campaign Manager (DCM), DoubleClick Bid Manager (DBM), DoubleClick For Publishers (DFP) or DoubleClick Search (DS)? GA360 will integrate with these tools, allowing you to see impression data, cost data, and a series of rich reports for each platform.
  • Roll-up reporting – If you have data in different properties, you can consolidate that data into one property with just a few clicks in the interface, and with no additional implementation required.
  • 200 custom dimensions and metrics – You probably know you can customize your GA implementation by passing along additional metadata for users, sessions, pageviews, events, and even products. With GA360 you get 10x the capacity for new custom dimensions and metrics.
  • SLA Support – GA360 comes with 24/7 SLA support for both GA and GTM. That means greater than 99% up-time guarantees, or your money back.
  • and more…

We’ve written about this extensively – check out our great post comparing the 360 features with the free version.

How do I put it all together?

Here comes the kicker. You might think, “Why should I pay for a tool that I’ve previously been using for free for the past 5 years?” Aside for data issues, which is what prompted this whole discussion, you also get to work with a world-class Google Analytics Certified Service Partner!

Working with a Sales Partner that’s also a Service Partner means that we’re able to discuss and provide options around implementation and configuration support, training, reporting and analysis – wherever you have the greatest need. We can also deliver a private, onsite training at your company location, tailored to meet your team’s needs.

Need more info? Learn more about our Google Analytics 360 services or reach out to us if you just want to talk about options. If you’re not quite ready for GA360 yet, read on for more ways to address the issue.

Non-Google Analytics 360 Options

GA360 may not be for everyone. That’s why we wanted to offer a 5-step “Data Limit Compliance Checklist” that you should use to bring your GA implementation under the 10M hit/month/property limit. There are still ways you can keep GA and get value out of it with a smart implementation, and this might be the best opportunity you’ll ever get to reflect on what you really should be tracking on your site.

1. Audit your existing GA implementation

Sit down with your marketing team and decide how you use your Google Analytics data. What websites do you currently track in GA, and into which properties? Do you get value out of the data you have? Is your data complete, accurate and trustworthy? Do you know what you’re tracking?

It all starts and ends with strategy. Your Analytics may have been implemented years ago, by an entirely different employee or agency. Make sure you understand what’s being collected and why.

Look for common mistakes, like duplicated tracking or a poor Google Tag Manager implementation.

As you begin to investigate, you may find spam data in your reports: this is an unfortunate problem with Google Analytics at a fundamental data collection level because in actuality anyone can send data into anyone else’s Google Analytics property. Usually, this isn’t a major problem, but you should see if spam data is making up a sizable chunk of your 10M+ hits.

If it becomes apparent that some of the data you have is strategically unimportant, this is the time to clean up shop.

2. Identify what webpages or sections could be collected in different properties

If multiple websites are tracking into one property, should they be? Would you be better served to separate out entire websites from each other, or to disconnect your development or staging sites, for example?

Google Tag Manager makes it easy to track different UA numbers on different subdomains, or on different microsites, using different triggers or lookup tables.

Just be aware that if you were previously tracking multiple websites in one property, removing any of those sites will have serious repercussions on any historical data analysis. Furthermore, if you begin to track a single website across multiple properties, it will become more difficult to understand the overall picture of user behavior on your website or to accurately gauge marketing attribution.

3. Identify what hits should be dropped

We often use “events” in Google Analytics to track user activity on a page, but sometimes our custom implementation can get a little out of hand. Are there any events that you see that are useless from a reporting perspective? Are you tracking events too frequently, like firing a video event for each second played? Or maybe you are using engagement events, like scroll tracking events, that you don’t actually analyze?

The point of Google Analytics is NOT to track every single user interaction on every single page. Instead, you should only track events if they will serve some reporting purpose, or if you can imagine their analysis being helpful from a marketing or UX-design perspective. Let that be your litmus test.

Additionally, you may be tracking “user timings” or “virtual pageviews”, which also count toward your 10M hit limit. You will want to remove any excessive timings/events/pageviews in order to work toward reducing your overall hit volume.

4. Block unwanted traffic from data collection

You should consider blocking traffic from your internal IP address(es), or from your development/staging environment, to limit hits entering the property. Perhaps you’re currently using filters inside the GA Admin to filter out that traffic. Unfortunately, due to the nature of the 10M hit limit being imposed on the “property” level, filters inside Google Analytics cannot circumvent the limit, since the data will already have been collected.

From the Google documentation on data limits:

Note: Adding view filters does not reduce the number of hits you send to Google. Filters act on data that has already been collected and cannot be used to reduce your traffic levels.

Instead, the way to block the data from entering the property is to prevent it from being collected in the first place. To do that, we recommend using Google Tag Manager to exclude certain types of traffic from data collection.

5. Impose your own data sampling

Maybe that wasn’t enough. Maybe you’re still exceeding the data limits. There’s one last hope, but it’s the nuclear option.

Google Analytics allows you to configure the “sampleRate” for your implementation. This is a setting we would generally never want to adjust, because sampling makes data analysis imprecise. In this case, however, we’re out of options. We need to manually limit the number of hits that Google Analytics will collect.

For example, if you currently have 1 million users a month with around 10 million hits, you can set a 90% sample to capture approximately 900,000 users with around 9 million hits, give or take. Using Google Tag Manager, simply adjust the sample rate under “Fields to Set” in your pageview tag. You can set the sample rate to any number between 0 and 100 to include that percentage of users in your data, like so:

It’s a very inexact science, due to the changing nature of your web traffic, but with some fiddling you can reduce the total hits that are being recorded in Google Analytics.

Success?

Ideally, we’d love it if everyone upgraded to Google Analytics 360. For us, it’s a goldmine of analysis, a preponderance of data, and a land of opportunity. We love the new features and increased data limits.

Realistically, not everyone has the resources for GA360, so we hope the five steps above will help guide your response to the data volume warning.

If you’re still looking for help, call us! We are dealing with this with our clients right now, just like many of you are, and we want you to know that you don’t have to go it alone. We’ve been doing this for over 10 years, and we’d be happy to help you audit your website’s GA implementation and create a Measurement Strategy for future data collection. We’d also be happy to help you compare your options with Google Analytics 360 and make the best decision for your company. Let us know how we can help.


Announcing New Resources for Google Tag Manager

At LunaMetrics, we’ve embraced Google Tag Manager as an excellent tool to help companies and agencies correctly implement Google Analytics and other third-party tracking. We use Google Tag Manager (GTM) daily with our clients, helping to manage their implementations from afar, responding to urgent updates, or helping to train key staff on how best to utilize the tool.

From these interactions with GTM, we’ve written a ton of blog posts about GTM (over 60 to date!) and love sharing tips, tricks, and our lessons learned.

We’re excited to announce our two latest initiatives to help others learn about Google Tag Manager and Google Analytics! We’ve published a book about Google Analytics implementations through GTM as well as launched a new GTM Recipe Section.

Practical Google Analytics and Google Tag Manager for Developers

Our book has been in the works for a while, you’ve probably heard us mention it once or twice! Jonathan Weber, our Data Evangelist, and resident GA/GTM expert, wrote the book with contributions from the entire team here at LunaMetrics. It’s packed full of best practices, step-by-step instructions, and careful explanations of some of the most complicated GA/GTM topics.

Jonathan comes from an information architecture background and started with LunaMetrics over 6 years ago, back when there were just 4 employees.

He heads up our Data Science services, working with clients on the fun but difficult analysis projects that follow excellent implementations.

As a trainer at LunaMetrics, he’s helped to craft our Google Analytics trainings and Google Tag Manager workshop with the most important information possible, traveling the country to lead seminars.

So what can you expect from the book?

  • Google Analytics fundamentals and basic measurement strategy
  • How to Implement and Test Google Tag Manager
  • Tracking Interactions (Downloads, Forms, Emails, etc.)
  • eCommerce and Enhanced Ecommerce
  • Additional Information using Custom Definitions and Data Import
  • Cross-Device Measurement and Mobile Apps
  • Information about GA’s Measurement Protocol
  • Bonus: BigQuery and Big Data Analysis

Practical Google Analytics and Google Tag Manager for Developers is available in both print from popular retailers including Amazon.com, as well as an eBook online from Apress.

Even if you don’t buy the book, take some time to check out our brand new book section for more information on the chapters, relevant links, and code from the book. We’ve made all of the information available online to make it easier to find links and code from the book as well as relevant blog posts and updates that have come out since the book was published.

Google Tag Manager Recipe Section

In addition the book, we’ve launched a new Google Tag Manager Recipe section our site as part of our LunaLabs. We’ve created “recipes” or GTM Containers to address some of the most common requests that we’ve gotten for Google Analytics implementations through GTM.

Each recipe contains all of the necessary Tags, Triggers, and Variables to add functionality to your site, like File Download tracking, Outbound Link tracking, as well as more advanced solutions like YouTube and Scroll tracking.

You can download these container files and import them into your container and hit the ground running with just a few minor tweaks.

Sound like a dream come true? You betcha!

We’ve written about some of these recipes before, while others we’ve been using internally but haven’t shared with the public yet. As part of LunaLabs, we’ll continually be adding to this section, adding more of our own experiments with Google Tag Manager and recommended solutions for common issues.

To get started, here’s a list of our current recipes:

For brand new implementations, check out the Google Analytics Starter Pack, which includes the following individual recipes:

We also offer some more advanced Recipes, like:

You can download everything we’ve got in the LunaMetrics GA Complete Pack, which includes all of the above!


How to Connect Tableau and Google Analytics

Ah, the lure of shiny objects. Tableau’s beautiful, interactive data visualizations long tempted me, but it wasn’t until they introduced the direct connection to Google Analytics that I finally took the bait. And was immediately disappointed.

It’s not that the visualizations are disappointing – my Tableau dashboards are great for interacting with GA data, and my clients are delighted with them! The letdown was in the Tableau and Google Analytics connector.

In this post, I’ll show you how the connector is supposed to work – and then show you how it can go wrong.

It’s Simple, Until It Isn’t

On the surface, connecting Tableau and Google Analytics looks straightforward and simple. You give Tableau permission to access your GA data, and then describe the data you want.

The connection process may be found in several places online, including Tableau’s own documentation, of course. I’ll recap here, for reference later when I talk about the pitfalls.

First, click “Connect to Data” and choose “Google Analytics” under More Servers… Sign in to the Google Account you use to access GA, and click “Allow” when Tableau asks for permission.

Then tell Tableau what data you want to see. Select the options presented as Steps 1, 2, and 3. See what they did there? It’s easy as 1-2-3!

Step 1: Choose an Account, Property, and Profile (View)

Step 2: Select Filters (Date Range and Segment)

Step 3: Select up to 7 Dimensions and 10 Measures

Tableau sets Date as a dimension by default, and you’ll probably want to keep it. Search the list to add another dimension. (Or more, if you’re feeling lucky. See “Common Pitfalls” below.)

Then select your GA metrics, called measures in Tableau. Choose one of the suggested “Measure Groups” or search for specific GA metrics.

After you have selected at least one item in every dropdown list, for all 3 steps, you can tell Tableau to pull the data. In a new workbook, Tableau will helpfully highlight the Sheet 1 tab as shown here. In an existing workbook, click any sheet or click the next icon to add a new sheet.

When you go to the sheet, you’ll see the name of your data source at the top of the left navigation pane, followed by the list of dimensions and measures you requested. Plus a couple extras in italics, like Number of Records. Metadata: bonus!

Now you’re all set to start visualizing that data, right? Maybe. Maybe not.

Common Pitfalls

About the only thing that can go wrong in Step 1 is that your GA account has poorly named properties or views, but that’s not Tableau’s fault. Go fix the names so you can tell what they are!

It’s a different story for Steps 2 and 3.

In Step 2, you have the option to “filter” your data. Tableau recognizes that it’s not a good idea to ask for ALL THE DATA – and Step 2 provides two ways to define a smaller data set.

Wait, why can’t you ask for all the data? In a word: Limits.

Pitfall #1:

The GA connector is bound by the limits of the Google Analytics API, which means you can’t ask for more than 10,000 rows of data at a time.

Pitfall #2:

If you ask for any segment of data that GA has to calculate by searching through a really large set (500,000 sessions or more), then GA will estimate total results based on a sample of that data.

The worst part is that Tableau doesn’t warn you when it returns incomplete or inaccurate, sampled data.

Pro Tip: Use the API Query Explorer! Enter the same date range, segment, dimensions, and metrics.

The Query Explorer will tell you (1) how many rows of results were available (even though it returns 10K rows max), and (2) whether or not the data was based on a sample.

You can also download the results from the Query Explorer and view them in Excel. To see what Tableau pulled from GA, click the table icon (“View Data”) at the top of the left navigation pane, next to “Dimensions”. Select all, click “Copy” and paste into Excel to compare.

You may have noticed this doesn’t solve the problem, but only alerts you that a problem exists. Read on!

Pitfall #3:

You can’t use “filters” in the Google Analytics sense, at least not to reduce the volume of data in your request.

Sure, Tableau lets you choose segments – er, ONE segment – to reduce the size of the data set. But for GA there’s a big difference between segmenting and filtering.

In Google Analytics, you can use the search box on any table to filter what data is displayed. The act of filtering simply removes some rows from the existing table.

On the other hand, when you apply a segment, it’s like asking GA to search all the data in your property and create a brand new table. This can result in sampled data, Pitfall #2.

In Tableau, if you want to remove some rows you have to pull the data first, and then filter it. Not having this option can result in getting cut off at 10K rows, or incomplete data, Pitfall #1.

Does it feel like we’re going in circles here? One more pitfall, this time from Step 3, Selecting Dimensions and Measures.

Pitfall #4:

If you ask for too many dimensions, you may get sampled data.

Google Analytics pre-aggregates certain combinations of dimensions and metrics, to produce the default set of tables also called “standard reports”. If you ask for a combination of dimensions that was not already calculated, GA has to create a brand new table. Same as with segments!

Examples: Add Device Category to a dimension like Source/Medium. Add Page to Event Category, Action, and Label. It’s not obvious, and there’s no warning.

If you’re a Google Analytics Premium customer, see the note at the bottom for ways around this issue!

Again, use the Query Explorer to discover the problem. Maybe you’ll find there is no problem. Swell!

But if there is a problem, what are you going to do about it?

Web Data Connector to the Rescue

The newest version of Tableau introduced a feature called Web Data Connector, which you can connect to Google Sheets!

This means you can use the Google Spreadsheet Add-On for Google Analytics, build the tables you want using filters if needed, and then connect those tables to Tableau.

Using the Add-On in Google Sheets gives you another advantage. You can combine API data from multiple queries before sending it to Tableau.

This supports the most common remedy for sampled data: reducing the date range. But it also allows you to combine data from different views, properties, or even accounts.

Why Bother?

You may be wondering, “Why not just use GA for reports and analysis?” Isn’t this a lot of bother to re-create something that already works pretty well?

It’s true there are already many features in Google Analytics reports, such as secondary dimensions and charting options among others, that are great for exploring your data and producing reliable, accurate reports.

And it’s true you could produce something in Tableau that is less functional than what’s in GA.

But it’s also possible to go way beyond.

With Tableau, you can:

  • add interactive features customized to your audience, e.g. list selectors
  • rename and re-group dimensions and measures, and create hierarchies
  • easily join data to provide context and improve readability

As long as you’re aware of the pitfalls and are prepared to address them, you’re ready to start visualizing.

Google Analytics Premium and Tableau

Just a quick note – the main takeaway here is that when Tableau requests data from Google Analytics, you’re subjected to the same sampling limits that would typically apply in the interface and the Core Reporting API. If you’re a Google Analytics Premium customer, this means there are steps you can take to overcome many of these pitfalls – mainly using Custom Tables to tell GA which reports should be unsampled.

We’ll save GA Premium and Tableau for a later post, but in the meantime you can read more about unsampled data, Custom Tables, and Google Analytics Premium.


Have you faced any pitfalls connecting Tableau and Google Analytics? How did you work around them? Have you tried the new Web Data Connector yet? Please share in the comments.