- Analytics in a Nutshell: An Introductory Look at Setting Up Google Analytics for CRO
- How Analytics Help e-Commerce Stores Boost Sales
- Google Analytics for e-Commerce
- Google Analytics Segmentation
- Google Analytics Funnels and How To Structure Them for e-Commerce
What is a funnel and how are Google Analytics funnels configured?
In e-commerce, a funnel describes how a potential customer finds you and what interactions lead to an ultimate conversion. The sales funnel typically starts at the very first interaction a user has with your brand – often seeing an ad on Google, on Facebook, or wherever they are likely to hang out. From that moment to when they finally purchase – which could happen minutes, weeks, months, or years later – is all, technically, your sales funnel.
But, as you can imagine, it’s nearly impossible to track that far back. How can you tell that seeing your ad six months ago is what spurred the visitor to buy? You can’t. It might have been a combination of that ad and seeing your product in their neighbor’s house that did the trick.
So let’s focus on the part of the funnel we can know: What happens on your website.
On your website, your funnel may start with a customer visiting a product page, then adding a product to their cart, then opening the cart page, entering their billing and shipping information, and finally completing the purchase.
Why is it a sales “funnel” (and not, say, a sales slide)?. Because, a funnel is wide at the top and narrow at the bottom – not everyone who comes to your site will go all the way through to conversion. Visitors drop out every step of the way. The job of the conversion optimizer is to make them less likely to drop out, so you can capture more sales.
In a perfect world, a CRO could transform that funnel into a pipeline – every visitor who enters your site would pop out of the other end, purchase in hand, for 100% conversion. It’s not possible, but even small improvements in conversion can have a hugely positive impact on your business.
How can analytics help?
Google Analytics offers funnel reporting and visualization, so you can see exactly what’s happening in your funnel, and if it’s breaking down anywhere (and losing more visitors than it should). But first you have to set it up.
Under the Conversion report section, you’ll find Goals, eCommerce, Multi-Channel Funnels and Attribution. For funnel reporting and visualization, the first step is to add a goal.
To accomplish this, go to the Admin tab of your Analytics account, go to views and open ‘Goals.’
This is the ‘add new goal’ screen. Once you click the red ‘+ NEW GOAL’ button, you will open the following dialog:
You must first define the goal you want to track. The most common goals come pre-listed, including revenue, acquisition, inquiry and engagement. Depending on the nature of your business, choose the appropriate goal. There is also a custom goal option.
The Goal description is automatically filled if you choose a predefined goal. For custom goals, users must fill in the name of the goal and define its type.
Goal type refers to the way the goal is tracked, such as viewing a specific page, duration of visit, pages per session or event tracking. This is entirely dependent upon what goal you want to track.
For engagement goals, the most appropriate tracking methods are duration of visit, pages per session or specific events. For other goals, the destination page will probably be the most appropriate.
The final screen is ‘Goal details.’ Here we can set the monetary value of the goal, which is entirely optional. It serves to measure the relative importance of the specific goal if there are more than one goals being tracked.
The final option is the one we are most interested in. If enabled, we get to fill in the fields with the funnel path, identified by urls of specific pages in the conversion path. Once properly filled in, Google analytics will automatically create a funnel and track the visitors as they move along it.
How does it work?
Here is what the funnel visualization looks like once it is properly configured:
In this example, the funnel begins with a cart, which was filled with at least one product by 6.285 users. However, only 1.926 of them made it to the next step, and the rest dropped out. Google Analytics even helpfully shows the ways the users dropped out of the funnel. We can see that the conversion ratio of the first step of the channel is relatively poor at 31%.
The next step in the funnel is billing and shipping, where users are expected to give their payment information and shipping destination. Here, the dropout rate is 28%, as a quarter of the users was unwilling or unable to enter in their payment data.
In the next step, which is payment itself, another 30% of the potential customers drop out.
How can we use this information?
Google Analytics will give you the data, but it’s up to you to analyze it to see what’s going wrong and what can be improved. Using the example above, we can conclude:
- Most of the customer attrition happens in the first step. That means something is preventing them from moving onto the next step. The sticking point might be a technical glitch (maybe they can’t move on), or most likely, something confusing or concerning on the cart page. How to remedy it? The first step is to narrow down the possible reasons for users abandoning their carts. The simplest way to find out is to create a survey that pops up if they leave the cart page without moving onto the next purchasing step, or to email the survey after they’ve left the cart page (this would require you to ask for their email addresses early in the purchase process).
- Be careful with how you ask for contact information though, because if the sign-up/sign-in process is too complicated, users will lose patience and leave. Trying creating logins using common social network logins or guest accounts to complete the purchase.
- Questions could range from “What stopped you from proceeding with the purchase?” to “What additional information would motivate you to buy the product?” It’s okay to be blunt and ask what you really want to know. Those answers will tell you how to improve the content and provide potential customers with more incentive (and less friction) to complete the transaction.
A high dropout rate at billing and shipping often indicates a trust issue: customers quit because they don’t consider the site trustworthy enough to leave their payment data. Adding another payment channel, such as PayPal, or adding trust badges like McAfee (to name one of many) can help with this. Not sure if trust is the problem? Check your guess with a user survey. It could be that users didn’t like the shipping options available (or were just adding their product to the cart to get a better idea of shipping costs).
Dropping out at the transaction confirmation screen is probably a sign that the user had second thoughts about their decision to buy. Enhancing the value proposition, offering additional benefits, or showing the diminishing stock numbers of the product (showing scarcity) could drive some of these users to reconsider and buy. Recouping just 30% of the users that drop out at this stage would, by itself, increase revenue by the same percentage.
As we can see, the funnel visualization allows us to easily identify underperforming areas of the conversion process.
However, the funnel visualization has one significant drawback. Segments reports are not available for funnel visualization. But, since Google Analytics is highly customizable, you can bypass this by creating filtered views that allow you to track goals by segments filtered in your view. The data will take some time to be collected, but after that initial hurdle, it will provide segmented data in real time.
Neat – huh?
The other way is to use the Goal Flow report in Google Analytics.
This report can use segments and offers similar insights to the funnel visualization
Final words on Google Analytics Funnels
From funnel report data you can derive significant insights into what is preventing your potential customers from completing their intended purchase and then act to remedy this. Testing the solutions will allow you to minimize the risk that the change will have adverse effects on the site.