To learn more about using data to optimize customer experience, check out our webinar “Using Analytics to solve customers’ new struggles.”
Customers engage with a brand on a digital channel like a website, mobile application, or email to accomplish something. This could be a purchase, enrollment, or call-back request. And it’s our job as marketers to deliver the best digital experience, enabling customers to accomplish their desired task quickly.
But what happens when your customer struggles to complete a task? And what happens if this becomes a recurring theme across your customer database and you don’t even know it’s happening? Are you waiting for unhappy or angry customers to submit a support request form or respond to a customer satisfaction survey? Well, guess what: most of the time, customers won’t tell you they had a poor experience. They vote with their feet (or fingers, these days) and go to another brand.
The key to optimizing any digital experience is to not just learn from what works successfully, but from what goes wrong. The first step is to understand the type of customer you’re dealing with, and then look to see what kinds of behaviors these customers show across your channels. When you begin this deeper dive, you can see a fuller picture of the customer experience — from their viewpoint.
This isn’t just about seeing what happens at the beginning and the end, but everything in-between. In fact, the actions in-between are what’s really interesting. Did the customer follow the website path that you planned? They often don’t, so then the questions become: Why did the customer stop filling out the form? Why did they abandon their cart? Why did they click on the red image so much?
Once you’ve spotted a problem, what’s next? As marketers, we need to proactively get in front of potential struggles before they become a real problem. This is something you need to constantly monitor because customer behavior is constantly evolving, and that behavior can be even more heightened during a situation like the current pandemic.
Look at your own digital channel’s search function and compare what products or services were searched for against what was actually purchased. Why are people searching but not buying? It could be because they’re window shopping, or they didn’t find what they were looking for because of incorrect or insufficient search results. Once you have this information, you can adopt new strategies and select the right messages for email outreach or e-commerce promotional campaigns based on the reasons behind their abandonment.
Take food delivery. If a customer needs to feed three hungry kids right now but your wait time is 60 minutes, that customer will find another provider who can deliver in 30 minutes or less. Customers don’t align to our needs; we need to meet their demands.
And when it looks like a prospect is going to abandon, you can view their engagement with your brand holistically across their purchase journey and target them with the right promotion, like a $5 coupon for the next time they visit as an apology for making them wait. You probably don’t want to do this for everyone: you want to pick the audience that will either come back or use the coupon to convert. By segmenting your audiences based on historical data, you can group customers into specific audience categories like price-sensitivity or VIP and target them accordingly.
Breaking down your organizational silos is also key to staying ahead of your customers. For example, if there are an abnormal amount of ‘forgot password’ clicks on your eCommerce site, you need your marketing, eCommerce, and call center teams to share data in real-time to first assess if there’s a system issue and, if there is, to resolve it before it becomes a very big problem.
From lost sales transactions to loss of customers, it’s imperative to understand why people call support or what’s kicking them off the digital channels. Using voice-of-customer functions, your various teams can gain quicker insights.
“The key to optimizing any digital experience is to not just learn from what works successfully, but from what goes wrong.”
But that’s still just reactive. What if you could get a peek around the corner and anticipate a large call volume? What if your brand could be alerted in advance so you can prepare and engage with customers in the best way possible? With anomaly detection, before spikes come into your call centers, teams can be alerted that something out of the ordinary is happening. This is possible thanks to AI technology assessing historical data. Additionally, determining the cause of the anomaly— whether it’s a one-time fluke or an evolving behavior pattern — will enable your organization to proactively engage in resolutions before that anomaly becomes a problem.
Customers want an instant, responsive, consistent, and personalized experience — all the time, across all channels. When you respond to customer struggles and system anomalies proactively, quickly, and effectively, then you have a better chance of increasing customer loyalty. It’s all about anticipating the evolving needs of your customers instead of responding to substandard experiences after the fact.
For more on using data and analytics to solve struggle, check out the rest of our Brilliant Basics series.