Have you ever had this online shopping experience: You click on a product you’re ready to buy, but when you get to the product page, only some of the information loads? You wait a second or two, maybe five if you’re feeling generous, before deciding you don’t have time for this now, so you close the page and move on.
 
In that micro moment, the site you were on just lost a sale. Like all of today’s consumers, you expected a seamless ecommerce experience without any hiccups — smooth, fast and intuitive. Lesson learned, if you want to compete at the highest level to win and keep customers, this is where the bar is set. And seemingly small issues, like missing page information, add up to weigh your progress — and profits – down.  

The good news is that 75% of companies say improving the customer experience is a top objective, according to a reporty by Spigit. The even better news that 86% of buyers are actually willing to pay more for a superior customer experience. 

So how can you meet these lofty expectations? To take it to the next level, you’ll need to identify and eliminate as many friction points as possible, beyond the obvious gaps and errors. Companies that rise to the top will be the ones that do this exceptionally well.

The experience is unique to each visitor

The key to being on the cutting edge of the customer experience is to look at the real experiences of actual users by investigating on the client side, not just the server side. Each of your visitors experiences a website differently, depending on their location, device, operating system, browser, connection and so on.  

So what happens when a specific, but relatively small segment of customers, get tripped up by an issue? For example, maybe it’s only occurring when Chrome users near Chicago click on a specific page. When users get frustrated, they lose confidence or worse, never return. If this micro issue continues unchecked, abandonment by this relatively small group can add up to significant lost revenue over time. 
 
Certainly these micro, or long-tail issues demand attention, but the tricky part is in identifying them. Do you know what percentage of consumers will tell you about an issue rather than just leaving when confronted with a frustrating experience? For example, 39% of visitors will abandon if images don’t load or take too long. Most users will never report these moments, making it incredibly tough to diagnose problems or provide support. If shoppers give up rather than open a support ticket, how do you even know that these micro issues exist? 

Treat CX issues like cybersecurity threats

Cybersecurity software and analytics tools continuously scan websites to detect and alert network admins about threats in real-time. If they didn’t, anyone with a stake in the website would constantly worry that something nefarious could be happening at any moment. Do Web developers stay up at night worrying that the Web or mobile site is breaking for someone and they don’t even know about it? With the right tools, they could sleep soundly. 

Similarly, a negative customer experience is a threat in its own right, sabotaging current and future sales. Like cybersecurity, which has been pushed to evolve in order to catch and resolve even the most nuanced threats, it’s time for UX tools to catch up. We have more insight into what the customer experience looks like than ever before, but even the most sophisticated ecommerce brands are getting an incomplete story from their customer experience tech stack. 

While there are tools that monitor page performance, they don’t take client-side issues into account. Real user monitoring will let you know that something went wrong in the experience, but it won’t tell you why. Customer support tickets and internal testing can help uncover some issues, but they can’t paint the complete picture of the vast and varying user experiences across your site. 

Machine learning to identify deviations

Technology is emerging to proactively surface even micro issues in real-time, so you can stack order and triage effectively. This includes alerts that are based on visitor behavior rather than site technicals, moving from reactive configuration of customer flows to proactive intelligent monitoring. 

For example, if you know that a particular percentage of people who spend one minute on a product page will add that product to their cart, you can set a user journey baseline. When there is a material deviation from that baseline, you’ll know that something is wrong and can identify the cause. 

By leaning on A.I. for the heavy lifting, you can find deviations from normal patterns in your customer journey and focus on the most significant opportunities. When your tool learns the consistent patterns of behavior on a page, it can then isolate for signals that things are amiss - even uncovering the micro issues. 

Many companies are taking steps in this direction and using machine learning to identify patterns, looking for combinations of frustration signals to determine which sessions indicated the most irritated visitors. 

As consumer sophistication evolves, so too does ecommerce tech. It’s hard work to create and maintain winning experiences that surpass customer expectations. With so much choice and competition, if you’re not going big when it comes to anticipating their needs and solving even the micro issues, your customers can (and will) find someone who can.