Charles Farina, Analytics Pros - Actionable Uses of Google Analytics

November 6, 2017

Actionable Uses of Google Analytics

Slide 1:

I’m very excited to be here.

Slide 2:

As mentioned, I have about 10 years of experience with Google Analytics.

Slide 3:

And what I am passionate about sharing with everyone today are what I think are actual use cases of using the platform.

Slide 4:

I’ve been working for about 10 years in this space, all of which have been with premier retailers of Google Analytics 360 Suite, which is the enterprise paid version. I have the fortune of working with every vertical and large clients like GoPro, VISA, Yelp, and many others in the space.

Slide 5:

What i’m going to show you hopefully over the next 20 to 25 minutes, are some quick tips and tricks that I have picked up over the past 10 years that you should be able to immediately apply in your current environment. I’m going to cover a variety of use cases around attribution. Everyone talks about attribution, but I don’t see many companies actually adapting any techniques outside of last click. Then we’re going to spend a variety of time around various engagement and content as well. If you have any questions, make sure to enter those into the chat box and we’ll address those along the way.

Slide 6:

First, let’s start with some ideas around content and engagement.

Slide 7:

The way I’m going to structure the next 20 minutes, is I’m going to ask a variety of question s that I normally get asked when I’m on site with various clients and there are a few different techniques of how I address those.

One of the exciting ones I think to start off with in using Google Analytics is around how you can identify your most valuable users.

Demo Screen 1:

If we switch over to Google Analytics, I’m using the Google Merchandise Store. It’s a live ecommerce site that you can access yourself and buy some Google swag like Google tee-shirts. And anyone can access this account by Googling the Google Demo Account. Google released it for everyone to use so you can follow along during this session if you would like to.

In identifying your most valuable users, what’s exciting about that is Google, in the last year, released a brand new report called the User Explorer Report. What’s unique about the User Explorer Report is it’s one of the places where we can identify individual users and follow along their user journey to see when and where they’re doing actions and start to figure out the why behind it.

So as an example, since this is an ecommerce store, if we’re trying to identify the user who either spend the most amount of money, or transacted the most, we can simply sort by our metrics at the top. If you’re not on an ecommerce site and you wanted to find people who submitted a form or downloaded something, you can simply apply an audience of users that did that action. Then all we have to do is select an individual user.

Here’s a user who have three transactions and had eight sessions. And if we drill into them, it’s going to show us everything about their behavior. This client ID is the anonymous Google client ID, a unique ID that’s created and stored on a cookie. If your website has some sort of authentication, we can capture authenticated user IDs and have a similar number. Now we can see everything about this user. We can see their acquisition date was August 14th, we originally acquired them from a referral, so another website visit, and the LTV of that visitor, year-to-date.

In here, all I have to do is open up the visits and I can start to see everything this user is doing. So on October 9th at 2:51pm, they purchased 985 dollars worth of product and we can see that the visit started at 2:36, they logged into the Google Merch Store. The visit ended about 15 minutes later and you can see at about 2:51 they purchased two Nest Outdoor cameras at 558 dollars each. The beauty of this is I actually have the ability to see everything that happened in between. For identifying individual user traits, I find this a very valuable technique, especially when I’m trying to build audiences, like our most engaged users, or certain product users, or blog users. We can start to understand how their individual behavior is different and use that to improve user experiences we have around our site.

Slide 7:

Another question I get asked all the time is: what is a good bounce rate? I think I get asked this question more than any other question.

Demo Screen 2:

Google Analytics has benchmark reports, but I don’t recommend anyone use those because they’re benchmarking your definition of a bounce rate versus others and most implementations of analytics aren’t actually that good, so who knows what you’re comparing the data to. Instead, since every business and every website and every experience is very different than anyone else’s, I would recommend and answer that questions by turning it around and using internal benchmarks.

We can use internal benchmarks in Google Analytics in a variety of powerful ways. The first example is we could go into the traffic source report, and if we were looking at where we get all of our traffic by source medium, we have this bounce report right here. It’s telling our overall average is 55 percent. What most people don’t know about Google Analytics is there’s kind of a hidden feature above the table, and there’s this little button, which is the comparison feature. This allows us to go in and select a metric like bounce rate and it will quickly compare the average bounce rate for our site, and then show us each row in the table compared to that average.

So we can go in and slice this by any other dimensions or metrics we might want to explore this for. So for example, I can start to look for mobile, desktop, tablet, and see that Google organic on desktop is 12 percent better, but Google organic on mobile is only five percent better than the overall bounce rate. Once place I find this technique most actionable is around landing page optimization.

Slide 8:

If you were asked by your boss tomorrow to identify five pages on your site that may need improvement or that you may want to start testing on to try and improve the amount of users that are actually engaging or taking action from that page. As an example, that could be very challenging if you don’t know how to use Google Analytics very effectively.

Demo Screen 3:

Most people might go in and go to the site content, then they’ll go to the landing pages report, and then sort by bounce rate. But when we do this, now it’s showing our landing pages or entry pages have a 100 percent bounce rate, but each of these only has a single session. They’re not actionable. If we use that technique that we just learned, that’s an excellent method for determining which pages perform better or worse. So I’ll select bounce rate again, and now it’s going to show me each landing page and hopefully I’ll see some outliers. So Waze pack of nine decal set is 50 percent worse than any other page.

What I like most about this, is this average or internal benchmark, when we go in and say we want to look for anything in the accessory section, I’ll search for accessories, and that counce rate is now going to change. The internal benchmark for all our accessory pages is 50 percent. Now it’s going to show me each page within that category and which pages are performing better or worse. So the pages I might first take a look at is the power bank, the galaxy screen, and the keyboard since those are driving significantly worse. And then I’ll probably also want to do some analysis on the fun page since that one, for some reason, is performing 30 percent better.

Using this comparison feature is a great way to use not only bounce rate, but any other type of metric to use your own website as an internal benchmark to take that and make some meaningful actions with it.

Side 9:

For the next example of how to use Google Analytics actionably, a question that I like to ask of my clients is: how can we combine qualitative and quantitative?

Demo Screen 4:

One of the things about Google Analytics is it’s a fantastic quantitative platform. It’s measuring numbers and statistics, but there’s very few data points in it that are qualitative in nature and address the why behind things happening. So what I wanted to show is the power of integrations you can do with Google Analytics. Almost every marketing platform has some integration with Google Analytics, and especially when we look at voice of customer, or for example session replay, those ones tend to be very valuable.

As an example, if I go into our Analytics Pros account, I could go into the top events report and I set up an event in Google Tag Manager to track all of our JavaScript errors that are occurring on our site. You might have events, for example, for form submission fails or for when someone unsuccessfully registers, but it’s really important to set up events for when things go right, or more importantly, also when things go wrong.

Using SessionCam, which has a free trial so anyone can go and try it out. What I can do is add in a dimension as a SessionCam ID, and I have a Chrome extension added. What this is going to do is add this button where I have the ability to track this action and I can launch this into the SessionCam platform and what it’s going to do is taking me to the recording of that session. So I don’t have to try to figure out from the numbers what’s going on, I just hit play and now it’s like I’m looking over this person’s shoulder.

Right now, they’re reading a blog post that we wrote on Simo Ahava about five reasons that we really like him. What’s interesting about this session is as the recording goes on, we’ll see that this particular user starts to search over and over again for different materials. It would be really interesting if I had search set up to see why and what they’re looking for because it’s pretty clear they’re stuck. They keep going to the category pages, but not drilling in on any of our articles. I wouldn’t get this type of insight any other way. This SessionCam is a great integration and something I recommend that you try out for yourself.

Slide 10:

Another question is: how can I identify how many users converted after seeing a specific piece of content? This is a common question I get all the time.

Demo Screen 5:

If we were to go into the content reports, what we’ll find is—this is an ecommerce site we’re looking at—when we go in and look at the performance of the homepage or the blog or any of the content on this, there’s no ecommerce data available. There’s this metric called page value, but there’s no easy way to associate revenue that’s coming from users that interact or engage with a particular piece of content.

One of the most powerful features you, in my opinion, have to know to use Google Analytics effectively, is advanced segments, which are also known as audiences. If we know how to use audiences, we can answer any kind of question and tie anything to an outcome and associate that together. As an example, i can create a new segment, and if i want to identify how many people landed or saw the homepage of the Google Merchandise Store, and then somehow ended up purchasing, I can do that really easily using this audience feature.

In here, all I’m going to do is click on Conditions, I’m going to select Page or use Landing Page if I wanted the entrance page, and I can say any page that exactly matches: /. And when we save this audience, what it’s going to allow us to do is either pick sessions or users and analyze everything about this. What’s exciting about this is I think Google, about two years ago, added this option called Sequences, so now I can do something like say, show me any user who saw a page that exactly matches: /, so that’s the homepage. And then, at some point later, I can say they transacted.

Then I can make this user-based, so it can be across multiple sessions, so any transaction per user is greater than zero. So, “Saw Homepage Then Purchased.” We can see on the right hand side it’s showing us exactly how many users match this condition. You have 1,300 users that saw the homepage and then somehow purchased. They could have seen the homepage on Monday and then purchased, or they could have done it in the same visit, so it’s showing us all of those users.

Now, you can take this particular piece  of audience, and I can understand everything about what they did. If I wanted to see what product they purchased the most, all I have to do is visit the Product Performance Report—it keeps this audience stickied—and now you can see the Nest Secure Alarm Starter Pack was the most purchased item from this particular cohort. These audiences are one of the most actionable uses in Google Analytics, and we’ll come back to these later, but you can see, once you apply them, it filters the entire platform to tell the story and give you the data behind everything about that particular audience.

Slide 11:

The last piece I wanted to cover for content and engagement, kind of goes back to some of the qualitative ideas. Can Google Analytics help with content ideas? How can I identify content that may need to be created or help me to modify? We saw the technique here about landing pages, but what else can we do about content?

Demo Screen 6:

One of my favorite parts about Google Analytics where we can get more qualitative data is around site search. Google Analytics has the ability, if your site has a search engine on it or search widget, to track what people are searching for. As an example, earlier I saw that if I search for “bike,” Google is supposed to be good at search, but this particular query ends up in a 404. These are the types of things we want to know and we want to keep an eye on.

Google Analytics can help with these content ideas in a few ways. If I go to the Site Search report, which is in the behavior section, there’s a list of search terms. If you set this up—it’s really easy to do, simply grab the query parameter in the URL and parse the query parameter out. In here, it’s going to tell us all of the key search words that were searched for in any particular date range.

Let me actually switch to the premium version of this. So I have a premium account and it has different search terms. In this particular report, we can see all of the keywords that were searched on this website. So YouTube was searched 297 times. We also have data around search exits, which is the amount of users that searched for that keyword and then exited the site. And then we also have Refinements, when they searched for something else.

So something I recommend all of my clients do is, for example, search for search exits. These are the words that have the highest number of exits. Then you can add a filter and say we want to look at anything that Total Unique Searches was greater than five. We don’t want single keyword search terms. This is where I would start some of my analysis or investigations. So “twitch” is a popular keyword. This is something where you want to find out why people are searching for “twitch” on the website.

If possible, I’d like to make a category or content page or some sort of content about it because it’s telling me that a high percentage of users are looking for this and there is nothing on my site that addresses it and then they leave it. So using Search Exits or Search Refinements is a great place to go in Google Analytics to get content ideas for different things your users are telling you that they’re looking for, and then the data is telling us they’re not getting what they’re looking for either. So a great place to start.

Slide 12:

Now we’re going to switch the discussion to attribution. This is one of my favorite topics to talk about. My friend always talks about attribution in Google Analytics and he has a phrase that I like to repeat and that’s: attribution is bullshit. That is actually a lot to think about. I shared in my intro that I find that most companies in the space are still struggling with moving away from last click. I feel like one of the reasons that there are all sorts of attribution tools and they’re still struggling, is that they’re still struggling to explain the basics of why attribution even matters.

Google Analytics can play a powerful part of this story in a number of important ways and it can help you take that conversation to the next level. The first thing is: can you even answer a question or do you even know if you even need to be thinking about attribution? To do that, we should be able to answer questions like this: How long are my users looking at my website or my experience before they convert? And do they tend to have multiple touch-points before they do that?

If it ends up telling a story that most of your users end up converting on a single visit, then it doesn’t matter what attribution model you use. But if the data ends up telling you that most of your users are converting in a week or after two or more visits, then it is more important that we think about attribution. Google Analytics can help answer all these questions, and in a number of ways.

Demo Screen 7:

What I would recommend you start off with is understanding a little bit in the conversion section about a series of reports called Multi-Channel Funnels. What’s unique about Multi-Channel Funnels is in here, Google built a linear attribution model, which assigns equal credit to each marketing touch-point that leads to a particular outcome.

We can go in and select any sort of conversion, micro or macro, so a form submission, downloads, if you’re in premium, you can use e-commerce. I’ll select e-commerce. We can set a look back window, we can see path length. I’ll say a path length of “All.” Now we can select any date range and start to understand what is leading to those ecommerce actions.

I would recommend starting your attribution conversation by finalizing the Time Lag and Path Length reports. The Time Lag tells us how many days occurred before a user converted. In the Google Merchandise Store, and 58 percent of all their conversion occur on day zero, the same day. But that’s also telling us that roughly 42 percent are occurring in one or up to 30 days later. About a fourth of all our revenue transactions occur somewhere between 12 to 30 days.

If we look at the path length, which is going to tell us the number of touches, only 32 percent of our users come and convert in a single visit. Over 68 percent of all of our users are converting in two or more visits. In 30 seconds I learned that attribution at the Google Merchandise Store is a very relevant and important topic because almost all of their users are converting over a series of days and multiple visits, not in a single visit and not in a single day.

To start off in the journey of moving away from last-click, you can do a lot of exploration and kind of small optimization with insights that you pull from this report. As an example, if we go to the Top Conversion Path Report, it’s going to tell us every transaction that happened and every touchpoint that lead us to those transactions. There’s 446 thousand dollars of revenue, and if I wanted to figure out how social is performing,

I can look for social and I can figure out if social is upper funnel or more of an end funnel. Scanning this report, we can see that social tends to appear most of the time somewhere in the middle. And we can get as granular as we want or need with this information. If we’re driving campaigns from Facebook, they’ll show up here in the campaigns or if it’s people coming natively from their social shares, it will show us that. So we’re getting a lot of traffic from, so some sort of social group here. But using this, I can easily figure out where my upper and lower funnel are.

Another unique value add with the Google Analytics platform, all of the ads are natively integrated. If I come in and I want to look for display, display has some unique capabilities within Google Analytics. In the free version of the product, we can get click-throughs from display. If you’re a Google Analytics 360 user, you’re going to get user display. This tells you where and when a user sees a display ad, they don’t click on it, but they later come back to the site. If I’m running brand campaigns or I’m running remarketing campaigns for display, this is one of the only place that you can go to to understand what is bringing in a converter, versus what is just noise in that journey.

If I add a campaign, I can get as granular as I want with the display insights to figure out what display campaigns are doing enough. These four conversions occurred from users who were using multiple display campaigns, both the electronic and the office, which means these users already knew our brand before they ever saw those display ads. These are band-based campaigns, but you might not necessarily want to give them credit.

So in starting that attribution journey, Top Conversion Funnel is a great place to start. Then there’s also all sorts of features Google Analytics has. They have attribution modeling and they just added a new product called Google Attribution, which is coming later this year or early next. To help marketers to make it even easier to solve the attribution challenges that exist.

I’m pretty passionate that there’s a lot you can do with your own business in answering basic attribution questions about what your user journey looks like and understanding where and when your various marketing are fitting in, whether that’s email, social, paid, or organic search results that users are coming from.

Slide 13:

The last piece I wanted to end with is how the activation of this data can be used.

Slide 14:

Google Analytics has two really important features on the activation spectrum where we don’t have the ability to read data, but we have the ability to take action with it. The first is those Google Audiences, the second is a brand new product called Google Optimize.

Demo Screen 8:

Google Audiences is a really important piece. We created an audience earlier of users who saw the homepage and then converted. We can create other audiences such as our most engaged users. Here’s an audience of anyone who viewed more than three pages or saw more that 180 seconds worth of content on our site.

Google integrated these natively with Adwords, so if we wanted to do bid adjustments or serve those users a different ad or remove them from seeing ads, we don’t have to tag our site anymore. We can share these audiences, build lookalikes all by simply creating them in Google Analytics. It’s removing that dependency on IT or tagging or tag management to create those audiences and putting it in your hands. It’s as easy as coming here, clicking three buttons, and then I can actually do something with the audiences I’m creating.

The other piece is around the landing page optimization and all of that. Google has a brand new product called Google Optimize, and it’s completely free to use. They’re also launching an Adwords integration in a few weeks. With this, you’ll have the ability to create and use a WysiWyg to create experiences, change content, and without having to know any CHS or HTML, we can start to play with the campaigns and the keywords and ad URLs to have our landing pages match and relate to what we’re doing there.

More and more, what’s exciting to me about the Google Analytics platform, is the ability not just to come in and analyze the data and have aggregate numbers, but the ability to filter through the entire platform for audiences you care about. They have allowed us to take those audiences and share them with other platforms. Then with third-party tools like SessionCam, we can integrate and find out more about our users to help us solve the problems we’re looking for.

I’m excited there are a variety of ways to actionably use Google Analytics, and not just use it to collect really cool data about your users.

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