Yet, despite increased investment in online advertising and eCommerce infrastructure, customer attention is more difficult to capture. According to eCommerce optimization experts, the room for improvement is tremendous:
- Only 40% of visitors go beyond the first page
- Over two thirds of shoppers abandon their cart and don’t complete the checkout
- 98.4% of visitors never buy anything at all
While these analytics help us define the problem, only a comprehensive testing strategy will help us solve it. Keep in mind, however, that not all testing is created equal. Many merchants adopt simple eCommerce A/B testing ideas, some examine web analytics, while others do no testing whatsoever.
The problem with traditional solutions is that many of them are rooted in statistics that work well in a static world — not in the dynamic world of eCommerce. eCommerce sites are in a constant state of flux due to evolving technologies and the ever-changing behavior of shoppers.
Let’s explore the pros and cons of eCommerce A/B testing and examine a reimagined approach — adaptive experience optimization testing.
eCommerce A/B Testing: Good Start but not for the Long Haul
A/B testing (sometimes referred to as split testing) is a simple method of website optimization whereby the performance of two versions of a page (version A and version B) are compared to one another using live site traffic.
Site visitors are directed to either one version of the page or the other with often a single feature being tested from version A to version B. By tracking the way visitors interact with the page they are shown, merchants can determine which version of the page results in higher conversions. Sometimes a third or fourth version of the page is included in the test (an A/B/C/D test). This means that traffic to the site must be split into thirds or quarters, with a lower percentage of visitors landing on each page.
A/B testing is the least complex method of evaluating a page design, and is useful in a variety of situations. However, it is limited in terms of testing multivariate elements on a page and has no real-time adaptive intelligence to limit potential lost revenue from failing experiments.
That said, if you’re looking to get comfortable with this whole testing game – check out this super-simple guide from our friends at CXL: A/B Testing Mastery: From Beginner to Pro in a Blog Post
Pros and Cons of eCommerce A/B Testing
- Simple concept and design
- Good starting point for skeptical teams
- Doesn’t require high traffic volume
- Shows impact of simple design changes
- Low number of tracked variables
- No multivariate insights
- No intelligent adaptation to counteract underperforming tests
- Does not account for dynamic and changing shopper behaviors
Who Should Use eCommerce A/B Testing?
A/B testing is a great way to get your feet wet with eCommerce testing but its performance is limited. Think of A/B testing as your training wheels. When you’re ready to hit the road properly, take the wheels off and consider adaptive experience optimization testing instead.
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What You Should Be Doing: Adaptive Experience Optimization Testing
Adaptive experience optimization testing is a completely different approach to testing that accounts for the dynamic, multivariate world of eCommerce.
In our experience-driven economy, the linear visitor behavior of previous eras is replaced by a highly fragmented path-to-purchase. Today we think about different audiences, at different buying stages, all requiring different experiences ― from initial acquisition through retention.
Adaptive experience optimization takes all this into account. It applies artificial intelligence to the testing process to continuously detect and adapt to visitor preferences in real-time. Adaptive experience optimization is based on the premise that actual visitors and customers of a company’s website should be the ones that define the best practices.
The technology has self-learning algorithms that adapt to visitor preferences using real-time signals to stage the right buying experiences, for the right audiences, at the right time. Additionally, disparate, non-compatible web and experience data sets come together under a single big data analytics architecture, enabling real-time algorithm data analysis.
Since Al optimization tools are integrated into a single platform and share the same application logic, merchants can fully leverage positive cross-variable interactions to maximize global results.
Unlike A/B testing, adaptive experience optimization has self-correcting feedback loops to minimize the risk of optimization by overplaying good experiences while filtering out the bad ones in real-time. This allows merchants to optimize many variables in parallel.
Pros and Cons of Adaptive Experience Optimization Testing
- Built for the dynamic, ever-changing eCommerce industry
- Accounts for multivariates
- Adapts in real-time to user behavior to improve the experience and avoid lost revenue
- Large data sets are required
- Expensive to do it alone
- Resource intensive when doing it alone
Who Should Use Adaptive Experience Optimization Testing?
Adaptive experience optimization is perfect for any merchant that’s serious about testing. It is the only method of testing that accounts for the dynamic world of eCommerce and that adapts to user preferences to ensure conversions are maximized — even during the testing time frame. Think of adaptive experience optimization as testing 2.0. It’s perfect for any merchant looking to move beyond eCommerce A/B testing and gain a real understanding of buyer behavior.
The Mobile Optimization Initiative Makes Adaptive Experience Optimization Testing Accessible to Everyone
We’ve established that testing is of prime importance in eCommerce but not all testing is equal. Adaptive experience optimization is the only testing solution that can stand up to the demands of the modern eCommerce industry. However, such testing requires specific knowledge and can be hugely resource-intensive when conducted in isolation.
Through collaboration and standardized testing, merchants can conduct adaptive experience optimization efficiently and gain from the learning of others. Adaptive experience optimization is the technology backbone of the Mobile Optimization Initiative — a community of merchants, systems integrators, and eCommerce experts working together to improve the mobile customer experience.
The Initiative is free to join (for qualifying merchants) and provides access to:
- Sponsored use of the adaptive experience optimization testing software for 60 days
- Sponsored support from experienced conversion optimization specialists
- Access to over 130 standardized optimization experiments
- Global insights into mobile eCommerce optimization trends
The Mobile Optimization Initiative makes adaptive experience optimization testing accessible to everyone. Join the community today and start benefiting from this dynamic eCommerce testing methodology.