Redefining Support #3: Technology to Power the Future of Support
If you’ve been following our Redefining Support series, you might have read our first post on why traditional support models are broken (so were some guitars, sadly). Earlier this week on the Freshdesk blog, we also saw why it’s important to stress on people instead of process and how it can vastly improve customers’ experiences. But because of the restrictions that traditional support models evolved with, businesses haven’t really been able to do that.
We believe that new technology is what will enable a new support model that lets you put the customer first; a model that will give you an edge over the competition. So here are the four leading trends in technology, that are already transforming the world of customer support, that you should look out for:
Big data refers to sets of information so large and complex, that they cannot be handled by conventional data processing; I’m talking big. All the information is just waiting to be leveraged by businesses to maximise on the potential that data has to offer. It’s so promising because everything is collectible: every point of contact a customer has ever had with a business, be it an email, a phone call, any solution article they searched for and read, or even a tweet. With all this information readily available, agents need to ask far fewer questions. Resolution times become that much faster. With this much context around the customers, even unpredictable things like social media disasters can be avoided, because you’d be able to gauge the influence a tweet or the person tweeting it can have.
But big data doesn’t necessarily have to come into the picture only after you’ve had some form of contact with a customer. Information – like a customer’s workplace, their usage statistics for your product, the purchase pattern, their history of interactions with you, and their activity on your app or website – can help you build profiles for your customers and cater to their exact preferences. You can offer proactive support, taking care of problems before they even crop up, you can make sure you’re not being intrusive or irrelevant, and ensure that you’re actually bringing your customers value with every interaction you have with them.
Machine Learning is thrown around quite a bit these days, but that only speaks to its merit. It essentially gives systems the ability to learn on their own. Using Natural Language Processing, ML systems can learn to analyze the language that customers use when they’re contacting support and automatically determine what emotional state they were in when they write to you. They can also identify how time-bound any query is. Agents can prioritize urgent or emotionally impactful requests and time-sensitive issues without having to manually sort through the tickets assigned to them. They can see visible boosts to their productivity and get more done in the same amount of time.
ML can also greatly improve efficiency by automatically identifying articles that could help address a customer’s query. Such possible solutions can also be sent out to the customer by default, thereby optimizing the incoming traffic of support queries. When no articles can be found to help the customer and contacting an agent is absolutely necessary, ML systems can still prove to be a godsend: they can pull up similar incidents from the past. Agents can thus understand the problem at hand better, and see what’s worked and what hasn’t for similar problems in the past.
Chatbots, by way of natural conversation, can collect information from people, letting you derive more context around customers and engineer the best experiences for them. Bots can deflect incoming queries to relevant solution articles, reducing the workload for agents and freeing up their time so they can spend their time on more complex issues. Based on customers’ descriptions, tickets can also be routed automatically to agents best suited to that particular issue. Bots can also effortlessly categorize incoming queries, saving agents hours of manual data entry and form-filling. Customers get what they want faster, and it’s all done conversationally too! With bots taking so much pressure off agents, they can direct their attentions towards making support interactions more personal and enjoyable for customers.
Collaboration is often considered a key component of any unit’s performance. And for most business functions, there are tools to enable it. However, support teams are somewhat lacking in this area. The way things are right now, working together is easier said than done; because the methods that currently exist are rather complex and it’s easy for customers to get lost in convoluted workflows.
The way we see it, agents should be able to work on a ticket simultaneously. Internal communication between agents spread across different time zones and geographies should be remarkably simple, it shouldn’t be a hassle for related teams to collaborate. Compartmentalisation should be possible, where complex issues are broken down to manageable chunks and they are taken care of separately even as someone keeps track of the entire picture. Everyone should be able to come together to make magic happen for the customer.
If you feel the same then boy, are you in for a treat! We’ve got something game-changing lined up for you.
When a support team with the right mindset capitalises on these trends, the possibilities are endless. They are enabled to handle more traffic in the same amounts of time, and because they’re always at their productive peak, the experiences that customers get are also greatly improved. Ultimately, it’s a matter of the right tools and technology empowering the ideal support philosophy and attitude.
Make sure you tune in to our blog for the final post in our series, Redefining Support #4, where we talk about why we think customer support should be everybody’s business.