We are fresh out of another successful online holiday season. It is quite boring that the main headline is that digital commerce has had yet another double-digit growth year.
Digital commerce metrics
There is nothing newsworthy there. The world has gone digital and digital commerce is the beneficiary of this shift. Business leaders and media should change their thinking and take a look at digital commerce business from the point of view of its full potential.
Taking this approach, the big headline should have been – Why does the average e-Commerce site have a 70%+ cart abandonment rate? – and – Why is digital commerce not do anything to reduce this rate that is growing year over year?
This would have been possible only if the executives at digital commerce brands or news media had known about the abandonment rate metrics. Most of the time they don’t. This brings us to our main topic: is there the need for free cart abandonment rate web analytics?
Why cart abandonment rate analytics?
The main reason that very few brands track and analyze their cart abandonment is the lack of understanding of the metric and hard work needed to properly provision web analytics tools.
For example many companies do not fully understand how to properly measure this metric and think that the cart abandonment rate (CAR) is the percentage of visitors that start the checkout process and then abandon the cart:
Where in fact, the cart abandonment funnel starts from the moment when visitor adds product to the cart, which is the moment when a visitor becomes a real shopper:
Additionally, as a digital commerce company, the logical question is if one should only track the rate or also the dollar value of abandoned carts or the number of abandoned items.
When it comes to provisioning the web analytics solution to track the cart abandonment rate, the process starts with adding of custom tags to the e-Commerce source code. Just if you are curious the custom tagging code might look like the scripts below:
The whole process requires advanced web analytics knowledge and IT participation, which is a big barrier to getting the metric.
Placement of the custom tags in the e-Commerce site is just a first step in the setup process. To get meaningful results, one also needs to configure a web analytics tool to actually calculate the metric and show the reports. Again, this requires work and expert web analytics knowledge, which further complicates the process.
The following are examples of work done by some of our clients that are above average when it comes to the cart abandonment rate metric setup.
Let’s start with Google Analytics example which is showcasing the state-of-the-art funnel charts below:
Other example of the existing art is the Adobe’s Site Catalyst solution:
What we are trying to illustrate is that provisioning of the web analytics tools requires a lot of knowledge and a significant amount of work.
About how we do it
We do respect quality and technical capabilities of the existing web analytics solutions but we also passionately believe that much more needs to be done to move the cart abandonment ball much further down the field.
This is why we took up the challenge to introduce cart abandonment web analytics that removes the implementation complexity while providing deep and actionable insights without a need for any custom reports.
To minimize complexity of the provisioning of the cart abandonment analytics solution, we are introducing integration connectors. At the moment we are providing two connectors below with many more to come in the near future:
Demandware certified cartridge: we are one of the first Link partners and our most recent version of the integration cartridge is designed to provide all web analytics data sets right out of box.
Tealium tag management: we are leveraging Tealium’s universal data object (UDO) to tap in into all data exposed by UDO and to automatically map this into HiConversion web analytics.
As a fall back plan for platforms for which we do not have connectors yet, we are providing configuration capabilities through the application interface.
We often joke saying that the cart abandonment rate metric has more than 50 shades of gray because our CAR analytics module has more than 50 different charts.
These charts are organized around our 4D view of the digital commerce:
The first dimension of our analytics is dedicated to Visitors. It provides insights into results associated with different visitor types, helping you understand abandonment associated with different channels, devices, geo locations, etc.
The Journey is about multi-page experience and provides a better understanding of the abandonment rate relative to entry points into the site, exit points and other metrics related to overall behavior in the funnel. These reports will help you drive visitors to the best entry point and to examine and fix the high abandonment at the exit points.
Experience dimension is about on-page results. It will help you better understand the details of micro conversions of each page in the funnel, or correlations between page load time or time on page to CAR metric.
The final dimension is the visitor behavior, set of metrics that show how different visitors react to every aspect of your digital commerce. Here you will learn about frequency of visits, correlation of the CAR metric to average order value, or sections visited, or types of products that were put in the cart.
Finally, what you can do with this solution
We wanted to avoid the pitfall of the existing web analytics solutions that are great in showing huge number of data points while staying short from presenting pictures that provide insights understandable to the average user.
Our approach is that each chart must tell a meaningful story. For example, even the simplest chart below that shows the relationship between total number of Shoppers (visitors that put at least one item into the cart) and the cart the abandonment rate is providing meaningful insight into a post holiday season:
The dotted lines are showing two disjointed trends indicating that the number of visitors, or motivation to select a product is significantly down while CAR is slightly up. This is expected during the period immediately following the high holiday season but if this trend continues, this report will force you to ‘peel the onion’ and dig deeper into other aspects of the abandonment process to determine if your demand generation process is not up to the par or if your site requires optimization.
Stay tuned for the coming announcement.