Best Practices to Ensure Your CX Tech is Meeting the Real Needs of Your Customers
There are many ways that technology is boosting the customer experience. Think of hospital call center chatbots that are answering patient questions 24/7, or ecommerce sites that remember your purchasing decisions and send offers as though they were your own personal shoppers. Advanced analytics, AI and tons of data are empowering these scenarios and making life better for everyone – until they’re not.
Think of the times when you were on a phone loop from hell and no matter how many times you screamed that you wanted to speak to an agent, you were completely ignored (perhaps the chatbot was never trained to understand rant-filled expletives). Or, the mobile app from your telecom provider that crashes every time you try to send a message; and don’t forget the friendly little chatbot that asks you if you have any questions when visiting a website, until it becomes the smallest little stalker, following your every move on the site.
It’s Time to Rip Off the Band-Aid
Sometimes technology is the answer to a better customer experience and sometimes it’s the cause of its demise. But in any event, it’s important to make sure that the technology solution isn’t covering up the real problem. For example, if you’re developing a chatbot to help an overloaded call center deal with a deluge of questions and issues, maybe the real issue is the quality of your product. It’s important to first identify the issue, fix it and then the technology deployment is just icing on the cake. As much as technology can facilitate better customer experiences, too often people are either trying to use it for everything as some kind of cure all or they are using it to cover up root product, service or even business model problems.
The Data and Design Approach
Other things to consider are the humans interacting with the technology. When technology is being used to improve the customer experience, it must take a human-centric approach. It must begin with an understanding of the customers, their needs, wants, frustrations and experiences – and then take all of that and personalize it.
The key to gathering this data and acting upon it, however lies in the synergy between data and design. If design is where human empathy, awareness and experiences are gathered, then data is what is used to either validate those decisions, or to send up a red flag that there may be an issue to begin with.
According to an article in the Harvard Business Review, digital transformation initiatives must follow a 70/20/10 rule: “Seventy percent of the effort of changing an organization—its processes, ways of working, key performance indicators, and incentives—involves people. Twenty percent entails getting the data right. The remaining 10% is about the technology foundation.”
Unfortunately many companies start with the technology. They’re also product-centric, instead of human-centric so while they may be informed by data, it’s only in relation to the products, or customer experience tools that are being leveraged. Yet while the majority of initiatives must follow a human-centric focus I would say that the 70/20/10 rule should perhaps look more like a 50/40/10 rule. Data is required to get the human part right. Customer experiences will inform the data and predictive analytics will help to identify if it’s a widespread issue. It also what fuels AI algorithms often used in customer experience solutions to create a more personalized experience. The symbiotic relationship between data-driven analysis and customer experience is what leads to effective digital initiatives that hit the mark.
So how can companies use data and design to make sure they’re not just pushing technology for technology’s sake but using it to actually boost the customer experience? Below are key considerations.
Don’t take a one-size-fits-all approach.
If you’re designing a mobile app to help Medicare patients set up their own doctor visits, data analytics may be telling you that the majority of patients are senior citizens. By understanding how frequently this demographic uses mobile apps you can decide if on would really move the customer experience needle or simply go unused. Likewise, if you’re a physician’s office creating a chatbot for medical questions, maybe the fact that it’s available 24/7 won’t be received as a good thing. Maybe when someone is call in the line at 2:00 in the morning, it’s urgent enough that they need a real live human.
Look for ways to personalize the experience.
It’s not enough to deliver the right experience to a specific cohort of users. You also need to personalize the experience on an individual level. Personalized customer experiences do not only mean getting customer names right in interactions. It also means having complete data available when someone calls customer service, or tailoring relevant offers to a customer on your website. Understanding if personalization matters means speaking to your end-users and taking a design-thinking approach, but the end-solution will most likely involve data-driven AI which will enable you to deliver the experience.
Go out into the real world.
Most data scientists can help you predict trends, behavioral patterns or the statistical probabilities of user behaviors, but they also know it’s not enough. They recognize that there are nuances (or even errors) in the data that they can’t understand while sitting at their desks. They expect design experience professionals to uncover the soft data – the sights, sounds, user’s facial expressions and discussions that are not yet digitized. This requires face-to-face meetings with end-users to uncover their likes, dislikes and frustrations.
Strive for continuous improvement.
Once a solution is launched, continue to take the pulse of end-users. Through one simple follow-up question after an interaction, you can determine if the solution is being well-received. In addition to simple customer satisfaction questions, use data to determine if improvements are required. If callers immediately hang up when they realize they’re interacting with a chatbot, maybe it’s time reassess the situation. The key to better customer experience requires a solid blend of data and the right analytics to support it, along with a deep understanding of customers and end-users and what makes them tick. Instead of chasing the shiniest new technologies to digitalize a better customer experience, customers need to start with the existing customer experience and then see if the technology is really the solution.
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