Digital transformation has been a buzzword for decades, but the COVID pandemic increased the need for companies to adopt a digital-first mindset. Now, brands must understand not only their customers' wants and needs but also their customers' experiences at every point of interaction.
Digital solutions are able to make that happen.
So how can businesses ensure they're delivering the best customer service in this digital-first world?
The following three pillars form a great underpinning for positive customer experiences.
1. Building a Consistent Presence for Your Customers Across All Channels
Customers today use a variety of digital channels—messaging, social media, email, chat, and more—in their everyday life. The first step toward improving their experience is to identify the channels your customers use most frequently.
You can ask customers via surveys, you can ask your customer service team, or you can conduct some quick sampling of major social networks for mentions of your brand name.
Think beyond the traditional channels, too. For example, businesses can analyze notes taken at the point of sale by employees for common topics and themes. Those notes can provide key information that the provider may not obtain through something like surveys or a chat tool.
Once you've figured out which channels your customers prefer, integrate those channels into the care strategy you already use. Doing so not only helps maintain a consistent message and brand voice across all customer care interactions but also connects your customers with the experts at your company who can most efficiently handle their questions.
Here's an example: Early in the pandemic, European Wax Center realized a lot of its customers used Instagram, but it wasn't supporting customer care on that channel at the time. So the company integrated Instagram DMs into its digital care solution and directed its contact center team to respond the same way they did to emails or SMS. The company was able to manage a major spike in support volume without increasing its customer service staff at a critical time for the brand.
A personal touch is always important in customer interactions. Don't just meet customers where they are; make them feel that they're talking to a real person who cares about them and understands their needs. Use your software to track conversation sentiment across all channels—even voice!
Omnichannel analytics are indispensable for today's care centers and marketing operations.
2. Finding Out What Your Customers Are Feeling—And Why
Most companies already know that tracking customer sentiment is a good thing. People (and our purchasing decisions!) are often driven by emotion, so understanding that emotion is vital both to converting prospects and retaining customers.
But you can go even further. Many brands look only for keywords that express sentiment—I'm mad at this company, I'm happy, etc.—without looking into the why behind the sentiment.
Knowing that a customer is upset is important, but understanding the root cause of that sentiment allows you to resolve customer friction at its source before it results in an inbound contact.
Start by tackling customer conversations from a root cause-analysis approach. Look beyond the words themselves to figure out the why: "I'm mad at this company because their chat function has been down for weeks," or "I'm happy since the company brought back my favorite type of product."
Conversations between you and your customers aren't the only places to track sentiment. Customers often use social channels to speak both with you and about you, and it's important to monitor both types of conversations.
For example, some companies have entire subreddits on Reddit. That's not a platform where a brand would normally play, but employees and frequent customers of the brand have conversations there every day.
You might not want to jump in directly (depending on the tone and topic), but you can still analyze what your customers are saying, and take action accordingly. Perhaps you'll uncover blind spots you didn't know you had that could lead to product or service improvements. That's information you can't afford to leave on the table.
Luckily, these days, you don't have to gather such information manually. Advanced omnichannel analytics and deep listening software can help you track emotion on every channel your brand and customers use. It can even help you turn that data into actionable insights by figuring out the reason behind the emotion.
In the long run, you'll save your brand time and money while also improving the customer experience.
3. Implementing AI and Machine-Learning to Enhance Positive Customer Experiences
Incorporating AI and machine-learning can drive even stronger relationships with your customers. We've all seen the horror stories of bot interactions gone wrong, but the reality is, there's a lot of efficiency to be found when powerful tools get deployed in service of positive customer experiences.
In fact, customers are often open to the use of AI if it's helpful to them, but they also want a healthy mix of human and AI interaction.
Here are the Top 5 reasons customers reported positive experiences with AI:
- Quick resolution
- Swift and responsive interaction
- An option to speak with a human representative
- Strong resemblance to human interaction
- Confidence that the issue would be resolved
The bottom line is that customers want the option to interact with a human agent if they need to, but they're also perfectly happy dealing with a chatbot if it can solve their issue quickly.
Chatbots are good at solving most simple problems. When they can't solve an issue, they're also good at routing customers to the best person who can.
That improves not just customer experience: Chatbots can dramatically reduce the workload on human agents, too, freeing them to deal with more complex customer issues (and often improving their job satisfaction). Bots help brands increase self-service and operational agility by automating messages across multiple channels and creating virtual assistants with app-like functionality.
Machine-learning, too, can create more positive customer experiences. If customers are talking about something not in your classification model, machine-learning can recognize that and provide better insights into your products and business processes.
For example, if customers complain frequently enough about a specific but previously unknown defect in a product, machine-learning will eventually add that defect to the list of important topics to your brand that should be flagged.
Machine-learning also helps you evolve your understanding of customer sentiment, detect trends in customer concerns, and improve AI routing and responses.
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The solutions outlined in this article are, of course, only as powerful as the humans who use them. But with the right digital-first mindset and the proper technology stack, companies can improve the customer experience without increasing service staff—and that's exactly what consumers are coming to expect.
More Resources on Positive Customer Experiences
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