There’s no doubt about it: bounce rate is one of the most important metric for an ecommerce site to track.
At the surface level or most basic understanding of bounce rates, a high bounce rate could be costing you a lot of money. A climbing bounce rate means potential customers are stepping backwards out of your funnel with their cash still in their pocket.
Before you dive in and start analyzing and dissecting your online store to reduce bounce it’s important to take a step back and realize a few things.
First, every website (especially ecommerce sites) have customers who bounce. Even the most successful global brands experience bounce.
Here’s the bounce rates of top ecommerce brands during the first month of 2017
99% of customers don't complete a purchase on their first visit. #bouncerate #abandonment #ecommerce #opimization Click To Tweet
Second, it’s impossible to reduce your bounce rate to nothing. You always have a stream of new customers who aren’t quite ready to make a purchase. In fact, 99% of customers don’t complete a purchase on their first visit.
And that’s not necessarily a bad thing.
But before I get too deep into why bounce rate is such an important metric and how you can leverage that data, let’s look at the definition.
Google Analytics Support Docs offer a pretty basic definition of bounce rates:
Bounce Rate is the percentage of single-page sessions.
The problem with this definition is that it’s incomplete and leads to common confusion that a bounce is inherently bad. The confusion is understandable.
In analytics, a bounce is calculated specifically as a session that triggers only a single request, such as when a visitor lands on your product page and then exits without taking any other action/interaction during that session.
It reminds me of Kaushik’s famous take on customer bounce: came, puked, left.
An interaction means any hit sent to Google Analytics: of course, it could be a pageview (and the user went to another site) but it could also be a transaction, a social share, an event (when non-interaction is false), or a virtual pageview user-defined hit.
This means that if your user lands on the website and you send an event, then there is no bounce, even though it could have been a single-page visit.
Analyzing traditional bounce rates is never as simple as “high bounce rate bad, low bounce rate good”. It’s important to remember how your customers act and behave once they land on your site.
Equally important is the context of their visit – why are they shopping with you in the first place?
Making decisions based on bounce rate alone can be misleading.
Let’s assume you’re selling a big-ticket item on your store like an outdoor fire pit so you launch a campaign to promote it with a custom landing page tied to a remarketing campaign.
Since a landing page has limited navigation – in this case it’s the option to purchase one of several types of fire pits (add to cart), the interactions are minimal.
Some of your users are interested in the offer but need a day or so to discuss it with a spouse or think over the purchase.
Other users were grabbed by the campaign advertisement but once they got into the page they realized they weren’t sure about the normal prices – so they wanted to do some price comparison before they make their decision.
There’s even a segment of users who were initially interested but after reading more about the product they decide it’s not for them, so they leave.
Each of those audience segments would technically count as a bounce, but they all have very different intent, and each has a varying percentage likelihood of returning to complete the transaction.
Can you lump these users together in your analyses? Of course not, because ecommerce customers bounce for a variety of reasons:
With just a small tweak though you can get a lot more value and insight from your bounce rate in Google Analytics.
You need to adjust your bounce rate if you want more actionable insights. To do that you have to amend your tracking code to change the way bounce rate is calculated.
By amending your analytics code you can trigger events based on specific activity based on the behavior (or targeted behavior) of your audience. This way certain segments of your audience are excluded from bounce calculations.
For ecommerce sites you typically have a fair bit of information when you’ve crafted better product descriptions. It can take a user some time to review the offer. The longer they read, the more likely they are to make an informed purchase decision – even if it comes later.
Reviewing your average page durations can help you benchmark and “guesstimate” the amount of time spent on a product page before someone is considered an engaged visitor.
Redefine your tracking so anyone below that threshold is considered a bounce.
For example, if your average buyer spends 30 seconds reviewing content before making a purchase then you could set anything below 20 or 25 seconds as a bounce.
Simply add this line of code to your website and voila – it works (you can also implement such an event through Google Tag Manager):
setTimeout(ga('send', 'event', 'NoBounce', 'Over 20 seconds'), 20000);
The event will be executed after 20,000 milliseconds (20 seconds), so visits longer than that will no longer be recorded as a bounce in Google Analytics.
Scroll depth tracking could also be an alternative modified bounce rate.
This is a great indication what content is interesting to a user, and it solves the problem of the one-single page bounce rate (if a user scrolls, an event is sent – so there is no bounce). This is ideal if your product pages contain a lot of information below the fold like Amazon product pages.
With your bounce rate segmented to focus on those visitors who legitimately bounce without a valuable level of engagement you can analyze that data per product and landing page to see where optimization needs to take place.
Prioritizing your efforts is important here; don’t start with the pages sporting the highest bounce rates. Conversely, you shouldn’t ignore pages with lower bounce rates.
Instead, prioritize based on how those bounce rates impact your revenue.
For example; Let’s say you’ve got two product pages on your site. For the sake of simplicity the products are priced similarly at $49.
1. Product Page A averages 8,000 monthly visits with a bounce rate of 39%, and converts at 6%
2. Product Page B averages 1,000 monthly visits with a bounce rate of 76% and converts at 4.8%
If you put effort into optimizing page B first and reduce your bounce rate by 10% you’re only engaging an additional 76 visitors and converting an additional 4 customers.
However, the same 10% reduction in bounce on product page A helps retain an additional 312 visitors, and 19 additional customers at the current conversion rate.
When deciding which pages to target for improving bounce rates consider a number of factors:
A great tool to help you prioritize your optimization (especially for ecommerce sites) is the content grouping feature in Google Analytics.
There’s no such thing as a “good” level bounce rate. Because content across your site varies as much as the intent of the visitor it’s possible for a page to have a high bounce rate – much higher than product pages – without it necessarily being an issue.
Your targeted and expected bounce rate should reflect the purpose of the page.
According to ConversionXL, content-rich pages reference pages are all “bounce worthy” and typically have much higher bounce rates. This includes:
The next steps to prioritizing your optimization efforts is to know “average” bounce rates, to see where you fall among your competitors and other industries in ecommerce, and how different audience segments bounce.
So, what is the average bounce rate? It depends.
Most websites have bounce rates somewhere between 26% and 70%. As a rule of thumb, a bounce rate in the range of 26% to 40% is great. 41% to 55% is ok. 56% to 70% is higher than average but may not be cause for alarm depending on the website. Bounce rates over 70% could be a problem.
Most #websites have bounce rates somewhere between 26% and 70%. As a rule of thumb, a #bouncerate in the range of 26% to 40% is great. 41% to 55% is ok. Bounce rates over 70% could be a problem. #ecommerce #optimization Click To Tweet
ConversionXL’s guide to bounce rate benchmarks recommends a few different benchmarks when determining your “ideal” average, starting with website type.
Next up, each industry has different average bounce rates.
Kissmetrics offers a similar infographic on bounce rates by industry and site type.
Here’s where you can start segmenting your data to dig deeper, and this is critical to any analysis you conduct – especially conversions and bounce rates.
Start with segmenting your traffic by device. Even slight navigation issues that may not be apparent on desktop can cause significant friction in the mobile user experience.
You should also segment your bounce rate by channel to review how your marketing campaigns, and the types of traffic they generate, are impacting your bounce rate. Here are the channels monitored within Analytics by Google.
Neil Patel shares a variety of other segments you should analyze, depending on your business model and marketing, include:
Here’s real case clearly illustrating how a wrongly reported bounce rate could impact your business in a negative way.
We had a client showcasing surprisingly low bounce rates (less than 10% site wide). Their marketing team was celebrating and considered it a great achievement. Unfortunately, the data was reported falsely.
Since the rate was abnormally low our team dug into their Analytics and discovered the average bounce rate on product pages was 0%.
It turns out when a user visited their product pages they landed in a tab resulting in the tracking code marking that as an automatic event. Each visitor triggered two hits that were registered: one pageview and one event.
Not a single visit was recorded as a bounce because every visit registered a false interaction.
In reality, the client’s bounce rate was closer to 60%. Because of this error they had no inclination that they were losing revenue and saw no reason or opportunity to improve.
We’ve seen similar cases with other clients where mistakes in site and analytics configuration log bounce rates incorrectly, such as duplicate analytics codes (duplicate hits), incorrectly implemented tracking (events trigger on entry even with no interaction) and even third party add-ons like live chat that registers as a visitor interaction.
It might present as a sudden drop in bounce rates for no discernable reason, like in the example below where bounce rates plummeted to 6%:
The base bounce rates in your Google Analytics should be taken with a grain of salt because there’s far too much data being lumped together and analyzed to create that single percentage. By itself, bounce rate is an incredibly deceptive KPI when you consider how much it can change depending on how you segment the data.The base #bouncerates in your Google Analytics should be taken with a grain of salt because there's far too much data being lumped together and analyzed to create that single percentage. #ecommerce #googleanalytics #reports Click To Tweet
This is why segmentation is so critical – analyze the data in a way that is most relevant to the page type, your audience, how they interact with you, the campaigns you run, their devices, and more. The more granular you get with data analysis, the easier it is to determine the cause of visitor bounce so you can prioritize optimization and follow through with changes that will have the most significant impact on lifting revenue.
But not only analyzing bounce rate might help you to better understand the processes in your ecommerce. Check out our article: 8 Must-Have Google Analytics Reports for Ecommerce Optimization.