Obviously, the main goal of an online business is to turn a profit. And while there is a lot of information out there about how to track and measure and analyze your revenue, few people understand that it’s also possible to use your existing data to increase revenue.
We’ll cover a few Google Analytics revenue reports here and explain how you can leverage this information into more revenue for your content-based online business.
We’ll look at the following reports in Google Analytics:
- Conversions > Ecommerce > Overview
- Conversions > Attribution > Model Comparison Tool
- Conversions > Multi-Channel Funnels > Top Conversion Paths
- Conversions > Ecommerce > Goal Flow
In order to track sales and other ecommerce data, you have to enable and implement ecommerce data tracking. If you haven’t done that yet, it doesn’t work retroactively, so you’ll need to activate it and wait until you have enough data to use this guide to analyze your revenue.
Understanding the Ecommerce Overview Report
When arriving at the Ecommerce Overview page, you will see a lot of numbers. Let’s break it down and point out the most important ones so it makes a little more sense.
The top graph is automatically set to show you Revenue and Ecommerce Conversion Rate. The Revenue is the dark blue line and it indicates how much money your site made overall per day. The light blue line indicates the Ecommerce Conversion Rate or the percentage of sessions that included a conversion, per day.
The next line down you will find your total revenue and average ecommerce conversion rate as well as the total number of transactions and average order value.
The bottom rows of numbers are going to be some of the most important numbers in this view. These numbers have the ability to tell you where exactly your revenue is coming from. Some of these numbers can even tell you which promotions are working better than others.
For instance, in the example above we see that you Campaigns have an average order value of $232.60, while Coupons have an average of $112.49 and Affiliation has an average of $190.63. Now, assuming that similar efforts were put into each of these categories, it can be assumed that your campaigns have a better ROI than the other two categories. However, we see that Affiliation has a lot higher volume.
Another major feature of the Ecommerce Overview is the “Top Sellers” portion. This table allows you to see, at a glance, which products are making the majority of your money. You can also segment “Top Sellers” by product category and product brand.
Analyzing Revenue with Model Comparisons
We can start to see how people are interacting with our site when they buy by going to Conversions > Attribution > Model Comparison Tool.
We’re going to look at two attribution models to give you an idea of how you can use leverage your data about paying customers to increase your revenue.
The first attribution model we’ll cover is the Last Interaction model. This model attributes 100% of the conversion value to the last channel used before the conversion. The other attribution model we will be using is the First Interaction model, which attributes 100% of the conversion value to the first channel used before the conversion.
Example: Sally was looking for carpet cleaner. To start her search she typed “carpet cleaner” into Google. She saw an ad for Express Clean and clicked on it, but eventually, she left the site without purchasing the product. The next day Sally typed in Express Clean, went to the website and bought a bottle of the product.
In the Last Interaction model the conversion value would go to Organic Search, but in the First Interaction model, the conversion value would go to Paid Search.
Now that you understand Last Interaction vs First Interaction, we can dive into the data. When you first open this tab you will see only data for the Last Interaction model, be sure you click “Select Model” and add the First Interaction model as well.
When looking at the first line you will see that Direct traffic brought in 2,349 Last Interaction conversion and 1,737 First Interaction conversions. There is a difference of 26.05% between the two numbers. This can be because people are going back to your site directly after seeing an ad of yours or finding you through search (similar to the example above).
Another interesting number to look at on this table is the small gray numbers in parenthesis. These numbers are the percent of total conversions that the specific channel brought. So looking back at the first line we can see that 56.71% of all conversions are attributed to sessions that came via direct traffic as their last interaction before converting.
If this were your site, this should be a flashing neon sign to you to make sure all of your funnel levels above revenue (acquisition, activation, and retention) are optimized to increase engagement in order to raise brand awareness. Direct traffic is some of the most solid traffic for strong brands and, obviously, people are more apt to buy from brands they know and trust.
If, on the other hand, you see that a large portion of your conversions come from search traffic and that the first and last interaction were organic searches, then this likely means that people are OK with not being as familiar with your brand before buying. If this is the case and you can get a good chunk of initial sales without strong brand awareness, then your best opportunities are in increasing repeat customers.
This means making sure you’re activating and engaging those people who come via search and buy by getting their email addresses (activation) and adding them to campaigns to get them coming back again (retention). Don’t rely only on search just because your data say it’s the best channel right now. If this is the case, your growth opportunity lies with other channels as well.
Increasing Revenue with Top-Conversion Path Data
We can add another layer and extend the idea of first and last interactions by analyzing Top Conversion Paths. Go to Conversions > Multi-Channel Funnels > Top Conversion Paths.
This data tells us exactly what paths people were taking to conversion most often. This first row shows us that the Top Conversion Path for our site is two direct visits. This means that before converting on this site, people are generally typing in our domain name twice. The second line shows something different- the users were referred to the site then came back directly a second time to convert.
The main pattern in this particular data set is that the top ten conversion paths always required two or more visits. It didn’t matter how the users originally got there, they almost always left and came back before converting. Again, this tells me I need to make sure my funnel is optimized above the level of revenue in order to maximize sales.
The default view for this report is grouped by channel, but you could change the primary dimension at the top of this report and see different source and medium paths or, if you want to get even more fine grain, you could select “Other” and search for the “Landing Page URL Path”. This would allow you to see the most common sets of pages viewed before purchases.
Using Goal Flow Data to Increase Revenue
Using the Goal Flow report (Conversions > Ecommerce > Goal Flow), we can see how well people are moving through the step-by-step sequences required to achieve a goal we’ve defined. In order to measure this, you’ll have to first set up a goal funnel for the goal flow report.
In the example flow chart below, I’ve changed the dimension from Source to Default Channel Grouping.
From this, we can see exactly how well people move through the steps to make a purchase when coming from different acquisition channels. Green boxes show us how many visitors entered that step. If you hover over the red lines, like I did in the above example, you can see how many users dropped off at that step.
You can get these exact numbers by looking at the table below the chart.
The gray numbers will tell you the percentage of people who made it to that step. For instance, in row one for 603 people entered the goal funnel through Organic search (Step 1) but only 190 of those people (31%) made it to Step 2.
Abandoning carts is not uncommon and it’s not the end of the world. However, major dropoffs like this would probably cause me to investigate a little more and make sure my cart is optimized for ease of use and clarity of information.
Putting It All Together
We’ve outlined some relatively quick and easy ways you can analyze your revenue data and come up with data-driven ideas to increase sales. I hope you can appreciate how the various levels of your funnel can work together and that it’s important to optimize each one and not try to skip a step in the process.
If you’d like to have all these data in one spot so you can quickly assess your revenue performance and make better decisions about your online business, get the Google Analytics Revenue dashboard I’ve created.
To set up your dashboard:
- Click the button above; you will be taken to your Google Analytics account (sign in if you are prompted to do so).
- Select the view of your Google Analytics account that you would like your dashboard to be in. You can see more about setting up Three Essential Google Analytics Views if you haven’t done so already.
- The dashboard is named “04. Revenue” — you can change it if you like or keep it.
- Click “Create” — and you’re done.
Now you have a go-to dashboard to go along with this guide so you can make data-driven decisions that increase your revenue.