[Interpreting Your Data Story Series]
The Performance Snapshot Part 1

In this first episode of the “Interpreting Your Data Story” series, host Scott Reid discusses an exciting topic: YOUR MARKETING DATA!!

He reviews Six Key Metrics and talks in-depth about the interrelationship of each metric and how you can use these metrics to optimize your traffic and website. 

If you’ve ever wondered about how to get started interpreting your data so that you can make better business decisions (and a LOT more), this is a great episode to listen to!

EPISODE SNAPSHOT

  • [1:28] Google Analytics for data analysis and interpretation.
  • [6:23] Analyzing website data using Google Analytics.
  •  [10:31] Website analytics metrics and their significance.
  • [14:39] Analyzing website data to identify trends and improve performance.
  • [20:11] Ecommerce metrics and data analysis.

SPONSOR

This episode is sponsored by our very own Ecommerce Optimization HUB – your essential tool for enhancing traffic quality, reducing traffic costs, and refining the online customer journey. With The HUB, complex marketing data becomes easy to understand, helping you to clearly identify what’s working and what’s not throughout your traffic and website. 

The best part is that subscribers of The HUB also get access to on-demand support, feedback & coaching from Chief Optimizer (and show host) Scott Reid. You can take a test drive with our full access, 30-day free trial – no credit card is required. Get all the details by clicking here

EPISODE TRANSCRIPT

00:00
Welcome to the Ecommerce Optimizers Show. I’m your host, Scott Reid. For our new listeners, I always like to start every show with my quick definition of ecommerce optimization since it means different things to different people. As a specialist in this field, I view optimization as a continuous evolving process with three core objectives, one, enhancing traffic quality to reducing traffic costs, and three refining the online customer journey. These aren’t just goals, they’re the pillars for scaling your business effectively. So why does this matter? Because when you blend these objectives together, you convert more visitors into customers grow revenue, cut costs, and boost your bottom line. It’s all about getting more for less, more conversions more revenue at a lower cost. Now this episode is sponsored by our very own e commerce optimization hub, your essential tool for enhancing traffic quality, reducing traffic costs, and refining the online customer journey with the hub. Complex marketing data becomes easy to understand helping you to clearly identify what’s working and what’s not throughout your traffic and website. And the best part is that subscribers of the hub also get access to weekly optimization feedback and coaching from yours truly, you can take a test drive with our full access 30 day free trial, no credit card is required. And you can get all the details at ecommerce optimizers.com. In today’s episode, we are going to talk about a fun subject. Actually just joking, it’s not that fun. But it’s something that can allow you to make significantly better decisions that drive your business forward. So that subject today is analytics. Specifically, we’re going to be focusing in on Google Analytics for or GA for data. Now,

01:50
at this stage of the game, beginning of December 2023, you’re probably well aware that Universal Analytics was replaced by GA four. And that happened on July 1, when Universal Analytics officially although it didn’t quite go away for many people right at that point. But it was replaced officially by GTA four.

02:13
And GTA four is an incredibly, incredibly powerful platform as Universal Analytics was, it can really shine a light on what’s working and what’s not throughout your entire marketing strategy. But here’s the thing, GA four can be very intimidating, there’s a lot to learn. And since it’s a brand new platform, everybody is in the same boat essentially in terms of the learning curve. And GA for for for most people, I would say it is confusing, there is that steep learning curve. That’s one of the main reasons why I created the ecommerce optimization hub or the hub, which this episode is sponsored by, it just makes interpreting GA for data significantly easier. It reduces the learning curve drastically. So that you can spend your time making better decisions and understanding how your traffic and your website are working together to convert a visitor to a customer without going through the pain and suffering of and months and maybe years of trying to learn the GA four platform, I want to be crystal clear about one thing. And that is that every single thing that I’m going to talk about today can be accessed in GA for all the data that’s in the hub. Everything that I’m going to talk about today is coming from GA for it’s simply being visualized in a much more easy to understand manner. In other words, you do not have to subscribe to the hub in order to get a ton of value out of this episode. What I’m going to review today is I’m going to talk about some of the key metrics that you should be keeping your eye on and just the way to look at it, and to interpret the data start to interpret that data in order to make better marketing and business decisions. So the first page that I’m going to be or the only page that I’m going to be talking about today is what is referred to as the performance snapshot. The first thing that you should always consider whenever you are analyzing data is your date range. Okay? So kind of like my default, if you will, is the last 28 days, I always start there for most analysis, not everything but for most so the performance snapshot is a for instance, when you load it up, it comes in with a default last 28 days, you can manipulate it and with any data you can certainly manipulate that that date range to answer different questions. But again, having that last 28 days is particularly useful for a couple of different reasons. Number one, when you are analyzing and looking at key metrics, at least in the hub, we have a comparison metric. What it does is it shows you the percent change from the prior period. Okay, so as a for instance, I’m looking at the Google merchandise shop data from November 9 to December 6. I’m recording

05:00
That’s on December 7, so it’s providing me with the results from the prior 28 days not including today, the value for total users, which is one of the key metrics that I always like to keep an eye on is 79,590. So let’s just call it 80,000 80,000 users for the Google merchandise shop, which is the demo account.

05:22
And there is a value underneath that, that says, up 11% from the previous 28 days, okay. So I can see very, very quickly by looking at that one metric of 80,000 total users.

05:39
And then right below it, there is another comparison metric that’s showing in green that says, Alright, our user count is up 11%. So what I’m essentially doing is I’m looking back at the last 50, I have the ability through the primary metric, and the comparison metric to look at the last 56 days, which would be 28 plus 28, if you follow me on that, and it the reason I’m kind of spending some time on this, too, is because it’s about a lot of the analysis that you’re going to want to do or using GA for data, however you’re accessing it is all about trends and patterns. So as much as possible, you should always be looking at the trends and patterns over time. And that’s why kind of getting back to the to the start of this last little segment, when I started talking about the performance snapshot. That’s why I like that 28 day timeframe is because if you are looking at your data on a regular basis, you don’t have to do it every single day. But if you look at it a couple times a week, you get into a sink in terms of how your business is trending. And if you’re looking at these trends and comparing them comparing metrics in the last 28 days as a for instance, and comparing it against the prior 28 days, you’re looking at a 56 day window. And that gives you a good, solid understanding of how your business is trending over time. Now, clearly, you can run quarter over quarter analyses, annual and all these other things you can look at the last week. But having that default standard of last 28 I just like it myself, I spent more time than I thought on date range, but I think it was well worth it as I talk through it because it really is about looking at your data in an easy to consume manner. In also in a way that is useful.

07:25
And the reason for that is that if you’re just looking at a given metric, or some data point, in a vacuum, just by itself, it doesn’t tell you anything. It’s the trend, it’s the pattern, it’s the way that the metrics kind of work together, that tells a story. And then when you understand that story, you can get insights from that story. And then through those insights, you’re able to make better decisions that drive your business in a positive direction.

07:54
A big thing with interpreting your data is keeping it simple. Okay, so the old kiss acronym, keep it simple, stupid, that could not be more relevant for analyzing your data and getting started with it. Especially in the spirit of keeping things simple. I like to keep my eye on six key metrics, right? There are obviously many, many more that are very important. But these six give you a good snapshot in terms of how your business is trending in some kind of interconnected ways. So those metrics are and on getting back to the performance snapshot page of the hub, those key metrics, right across the top of the performance snapshot page. Okay, so those metrics are total users sessions, ecommerce conversion rate transactions, average purchase revenue, and revenue. And these are not just random metrics. Okay, these are essentially defining key aspects of the customer journey from start to finish. If you think about visualizer, on the left hand side of the equation, we have total users. So this is the total number of users that are interacting with your site. And total users as defined by GA for or not by GA for the Google Analytics for metric, as defined by Google, in Google Analytics Help total users is the total number of people who visited your site or app in the specified date range. Now, it’s not going to be an exact number, okay? Because we have different devices, and people are signed in under different profiles and incognito mode and all this other stuff. But that’s a pretty good idea. Totally users gives you an idea of unique humans, okay. Generally speaking, that’s the start of the process is the number of users who hit your site. The next metric going from left to right, is sessions. So users generate sessions. And there’s a kind of a long, complicated ish example or definition. Just think about it this way. It’s the number of times unique times that your users interacted with the site. So

10:00
For instance, I’m looking at the performance snapshot for GA for again, we have 80,000 users, and then we have 100,000 sessions. So 80,000 users visited the site 100,000 times, okay, that’s the easiest way to think about it. And that just shows you the level of activity from a variety of different aspects that we’ll drill down into in terms of analysis and future episodes. But for this episode, just just know that that’s the relationship between users and sessions. The next metric is ecommerce conversion rate. Because once you have your users and then those users create sessions now what we’re doing is we’re on a very, very high level, we are examining how the site is performing in terms of converting a visitor to a customer. And that is represented in terms of the E commerce conversion rate metric, okay. So that is defined as the number of transactions divided by the number of sessions. And this is not available in GA for this metric is not available in GA for like it was with Universal Analytics, you actually have to calculate this. So this is calculated for you automatically in the hub with the corresponding comparison metric. The next metric in the line going from left to right is transactions. So again, we have total users sessions, ecommerce conversion rate, and transactions. So all of those sessions, we applied the 1.1%, we had 100,000 sessions, we applied the 1.1% ecommerce conversion rate, and we have 1100 transactions. And that’s very simple transactions a transaction, each transaction has an average to in terms of what the revenue was from that transaction. Okay, as I believe I mentioned earlier, the Universal Analytics metric, and what we all kind of refer to it as is average order value. A Ovie is a very common acronym. Now, they’ve renamed it to average purchase revenue, it’s the same thing. Okay. So the average purchase revenue, again, is the average transaction order value. Very simple. And then you take your transactions, and your multiply it times your average purchase revenue to get your, our sixth and final metric, which is revenue. And when you’re looking in the hub, or you’re looking in GA for if you’re structuring it in that way, and in some shape, or form. When you line these metrics up from left to right, you are able to read a story. Okay. And that story, it’s very simple to read, especially when you have some comparison metrics, because you can see the trends and the patterns in terms of how each of these are performing. So let’s break the story down into chapters. We have total users and the sessions that were generated by those users. So looking at that, and looking at the trend in terms of the comparison metric, and see is that in an increasing or decreasing manner, we don’t want to see things going down, we want to see them improving, or at the very least staying stable, okay, and all of these comparison metrics in the hub, are conditionally formatted in either green or red. So you can quickly come in and just look and see where things are going well or not in terms of these metrics. So let’s look at the users metric. What does that metric tell us? And why is it so important? It tells us all about our traffic strategy, how our traffic strategy is working to attract and bring people to the site. So if that’s going down, and you see a decline in total users, you see some type of a negative pattern, the first thing that you’re going to want to do is to look and see what potentially might be going wrong in terms of your traffic strategy, something might be broken, or targeting is off or whatever. But that’s the one of the first things I would do. That’s why that metric is so important. Because you can’t sell anything without website visitors, which is quantified in terms of the total users metric. The next metric is sessions. So you’re gonna want to look at this, again, on a high level, because that’s what all these metrics are high level metrics, you’re gonna want to look at that and look at the percent change over the prior period for users, and then match that to sessions. Okay, so as a for instance, and I’m going to look in here right now we have the total users metric increased 11% from the previous 28 days, okay. And we have sessions increased 8% from the previous 28 days. So that’s, that’s pretty even. Okay. 8% 11%. What would jump out at me, is some type of a significant diversion from a positive trend on both. So in other words, if we saw, using this example, an increase of 11% for users, but we saw a decrease in sessions of 20% That would be a red flag to me, that would indicate

15:00
Hate that there’s some reason why we don’t have people coming back to the site as frequently as we would like. Using that example, I would definitely drill into this and in an attempt to identify what could be causing that reduction in returning visits, okay. So things that I would look at would be the customer journey, I might look over at the ecommerce conversion rate and compare that within the same date range, if there was a corresponding reduction in ecommerce conversion rate that might be indicative of something broken on the site, which was negatively impacting the user experience, which was then negatively impacting the return visits, it could also be a change in the traffic strategy, specific to what type of copy or content that we are using to bring people to the site, if it works to bring people to the site, but it’s perhaps in congruent with them coming back to the site or staying on the site in the first place. That might be another area that that could cause something like that. So there’s a bunch of different things, those are just two kind of broad ideas. But the point is, is that being able to identify and look at that data would provide you with clues that story that the data is telling you would provide clues, by way of that comparison metric, just that one little metric could tell you this case would tell you that you should look further in an attempt to identify what is causing that. Because especially if you have a consistent spread between users and sessions over time, which is another thing you’d want to look at just to kind of validate that spread. From a historical standpoint, if all of a sudden something changed, and went down. And that was an anomaly, that would, again, be a red flag, and it would be an area that you would definitely want to drill into. The next metric is ecommerce conversion rate. And again, that is transactions divided by sessions. And that’s expressed as a percentage. Okay, so the conversion rate percent, in this example, is 1.1%. So the average ecommerce brands website converts at around two to 3%, if you were to look globally, and really what that metric represents is, again, the ability of the website to convert a website visit to a transaction or to a customer, depending on how you want to look at that. But either way, you don’t want that to be going down, because that would indicate some type of challenge, primarily in terms of the website, and its ability to perform, and secondarily around the traffic that’s coming to the site. Because the reality is, is that if you send garbage traffic to the best website in the world, it’s just not going to convert, okay. And the opposite is also the case, if you send great traffic to a really poorly performing website, you’re just not going to convert nearly as much. So they’re both interdependent upon one another, and your ecommerce conversion rate, the way that I look at it in terms of analyzing if I saw a negative trend that was outside a reasonable variation, if you will, I would first start out with the website itself, I would drill down into the different stages of the customer journey and see if there was an apparent drop off. If there was I would go in and troubleshoot that and then fix it. Okay, or at least test around that, in an effort to improve that area of the website. The second thing that I would do would be to drill into the traffic strategy and see if there’s anything that’s changed, okay. Has there been a big change in copy creative in traffic sources that are being used that might be negatively impacting the quality of the traffic that’s being delivered to the website? Because if that quality does change, that’s how you could see a variation in terms of returning visits as evidenced by that session metric and the trend in terms of is it increasing or decreasing, as well as how is that comparing to the total users metric? In summary, with the E commerce conversion rate metric, it is a very, very important one, obviously, because of the breadth and depth of what that one singular metric is dependent upon. I mean, so much of an E commerce brands marketing strategy boils up and bubbles up into that metric. Transactions is the next metric after ecommerce conversion rate. And that is one that doesn’t necessarily require a lot of explanation. It is a result of user sessions e commerce conversion rates, so that’s why it’s next in line obviously

20:00
You’ll want that to be on the upswing, you don’t want to see it going down. But it is very much an important one. Because that is by way of the nature of that metric. It’s what’s creating your revenue, it’s those transactions. So you want as many of those as possible for obvious reasons. Now, average purchase revenue is the next metric. And this one is really important, for obvious reasons, we want the average purchase to be as high as possible, I don’t think that there’s any ecommerce brand that would ever want their average purchase revenue to go down. And so that being said, it’s one that you really want to keep your eye on. That’s why it’s at the top of our performance snapshot in the hub, it’s very important one just like all the others, but average purchase revenue, it’s one of those things that you want to keep your eye on it, first of all, and if you do see a decline, it can be an indicator in terms of something that is going wrong, either on your website or with your traffic. So in terms of average order value, as it relates to a potential website issue, there’s all sorts of things that could cause somebody to, in essence, cut their visit short, thereby reducing the average purchase value on a per order basis, which is the definition of average purchase value. But if things are frustrating, or more frustrating, or they become more frustrating than normal, that could definitely lead to a reduction in average purchase revenue. There’s all sorts of different things. But it’s definitely something that you would use advanced reporting, in an attempt to identify where something may be broken, or isn’t working quite as well as it once was that you would then want to go and optimize. And I don’t want to leave out research either. Because research is a it’s a key component of the optimization process and

21:49
exit surveys on site surveys around the user experience, those types of things, post purchase surveys, could be very instructive in terms of identifying an area of the website, or of that online customer journey that could be potentially preventing people from building their order up, as compared to an earlier time when things worked more smoothly. So the second thing, as it relates to average purchase revenue is traffic. Again, it’s incredibly important for your business for your brand to generate the highest quality traffic possible because quality traffic, by definition is, is traffic that is really engaged with your brand, they really want your products and your services. And they’re just going to buy more of it. So if there was some type of change or issue with the overall traffic strategy and the execution of that strategy, that could definitely lead to a reduction in average purchase revenue. But either way, it’s a really important metric, and one that can point you based on the story that it’s telling can point you in different directions where you would then either go drill down deeper into user research, and or more advanced analytics in an attempt to identify where issues may exist. So the final metric is revenue. And that’s a really easy one, because you’re basically just totaling everything up, you’re totaling up sessions, multiplying that times ecommerce conversion rate, which gives you a product of transactions, and then you take those transactions and multiply it times average purchase revenue, which gives you a revenue. I know you know that. But there is a corresponding comparison metric with revenue, at least in the hub. And if you’re just using GA four, you should definitely be looking at it through the lens of that trend. You always, almost always if you’re a growing ecommerce brand, you want that that comparison metric to be on the upswing, you want to have month over month growth, which if you’re looking at a 28 day look back, that having that metric, having that comparison metric in green, with an arrow pointing up is the best thing that you can see. If you start seeing that go down, you’re gonna go backwards, you’re gonna go back to the story and you’re gonna see what happened, you’re going to look at each chapter, you’re gonna look at the total users chapter, the session, the sessions chapter, the E commerce conversion rate chapter, the transactions chapter and the average purchase revenue chapter, to see what’s negatively affecting that revenue, and then drilling down from there based on the story that each one of those chapters tell you are the part of the broader story. So I hope that this was helpful. The big key here is, is that your data tells a story, there are six key metrics that tell a broad, high level story, okay? And then you can drill down from there, but if you keep your eye on those, and there could be some other ones that you really like that help you to manage your business proactively and keep in tune to it so that you’re in sync with what’s going on you kind of feel the ebb and the flow. That can be very, very, very comforting because then you have confidence that you know how your business is operating.

25:00
And, and you kind of feel that heartbeat going a lot more than, then you might without that type of that that type of analytical reporting. So I hope this was helpful, I really enjoyed talking about it, I went a lot longer than I thought it was gonna go. But I only touched the surface of the E commerce optimization hub, I just talked about that top row. So in the snapshot, which we’ll talk about in future episodes, because I’m thinking about it, I’m just gonna go through the hub and just talk about these metrics. And the way that it’s reported and structured because again, whether you use GA for or you use the hub or some other reporting platform, just the experience, and the thought process is the most important thing in terms of analyzing your data. And what I’m going to do is just kind of go through my thought process and an effort to, you know, impart some of my knowledge on you. And hopefully that helps you to grow your business, other parts of the performance snapshot, the next episode in our analytics series, we’ll talk about the traffic snapshot, the product snapshot, the sessions and revenue per device category, horizontal bar chart that we have, which is really great in terms of optimizing revenue per gender, which can be helpful with traffic, and audience targeting, and then user distribution across sessions, total users, active users and new users. So we’re going to drill down into that user metric some more in our next episode, and the and it may not be our next episode, again, our next episode on analytics. And I should be able to do that all in one episode. And then we’ll have those five areas at least and then we’ll have that performance snapshot page of the report and kind of like that, again, depending on what you’re using for your analysis, you’ll have that high level overview of the areas that you should keep your eye on, on a very regular basis. So thanks very much for taking the time to listen to this episode. I really appreciate it and I look forward to talking more in a future episode. Stay tuned. Bye bye