Product support can be a double-edged sword. There’s a built-in contradiction:
Support teams are working under a certain time constraint. They don’t have all the time in the world to make sure the information they relay is as accurate as possible. To answer the customer on the other end of the line, they must be knowledgeable enough to do so fast.
This makes product support inherently difficult to scale. It can take up to six months to onboard a new representative just to train them on the product. Documentation is often scattered and hard to read. Constantly looking through PDFs for that one specific technical information and communicating that back to an impatient client is not the most efficient way to work.
But there is a way out of this.
With today’s technology, it has become possible and viable to build a centralized database to store product information that’s easily accessible for everyone. Product teams can scale because each new team member has the same information as everyone else.
Knowledge communicated fast is the key to great product support.
Below, we’ll go over the different stages of scaling before diving into the components that make up a streamlined product support workflow.
Most companies start out answering the tickets that come in through email or answer phone calls for one-on-one chats. Eventually, they may move their operations to support software like Zendesk that lets them answer tickets in a central place so it’s easier to manage.
But for businesses that depend on technology products, this kind of support system simply isn’t enough. A centralized ticketing system will help you organize better but doesn’t tackle the fundamental problem––the lack of centralized product-specific knowledge connected to your support workflow.
Building a knowledge base for your team is a great start. But eventually, you’ll want to connect the information that’s stored in your knowledge base directly to your support system so that it’ll be easier to look up information and relay them to the customer right away.
Once you’re at a place where everyone on the support team can see the tickets and information, it’s time to move onto the next stage.
As your company scales, the volume of tickets will grow, along with the variations in your requests. Older customers might want more information about features in beta or development. At the same time, you’ll still field requests from new customers requesting less advanced information.
To better serve your diverse customer base, it becomes necessary to categorize your support system to direct them to the right place. It might look something like this:
At this stage, you’ve got a comprehensive flow that works to support a growing team and customer base. The next step is to streamline this process with automation.
Instead of manually looking up information from customer details to product knowledge, using an automated system that tells you what you need to know right then and there can speed things up considerably.
When you have an AI-powered knowledge base, your support team can rely on previously stored information that shows customer details and history, as well as specific product knowledge.
This translates to skipping a step in the support process because there’s no need to look up or ask for further information. AI-based tools enable your support team to do their work with more confidence and efficiency.
Another advantage of AI is that it gives you detailed analytics to help improve your workflow. These automatically generated reports give your team more overall information that may be difficult to track manually, such as:
The AI spots trends so you can prepare your support workflow to better serve your customers by allocating the appropriate resources where they’re needed most.
For product teams that want to scale, it’s essential to run a data-driven operation to make sure things don’t fall through the cracks.
Wherever you are on the scaling journey, there are some vital elements that go into any well-run product support workflow. If you haven’t implemented these key ingredients yet, it’s worth thinking about getting started.
Here are some actionable items for driving excellence in product support.
The biggest challenge of creating an excellent product support team is centralizing knowledge so that every rep you onboard knows as much as possible about the product. After all, the most important ingredient in support is providing your customers with the information they need.
But many technology products are complex and ever-evolving. It’s not always possible to expect everyone to have the same amount of expertise in every department. So what often ends up happening is a slowed down support workflow as representatives pass on the baton to those who can provide accurate information.
Yet customers don’t like being bounced around and would rather their assigned rep answers their queries right away.
The solution? Create a solid knowledge base.
A good knowledge base isn’t exactly hard to build but it does take time. Companies may feel that they don’t have the time to devote to this effort. But this investment is one that pays off handsomely in the end, and the earlier you start, the better.
Not only does a knowledge base help reduce the time it takes to onboard new representatives but it also helps customers help themselves. It’s easy for information to get lost in the training process––with a knowledge base, support reps can always look up the specifics they need at their own pace and on their own time.
And by directing customers to the information they need, representatives can focus more on advanced support issues and spend less time answering tickets that only require basic information.
One important thing to mention is that your knowledge base doesn’t need to be perfect from the start. As things change, you can add and tweak as you go. It can also be a team effort rather than one individual being responsible for managing the whole database.
One way to measure efficiency in your support workflow is to compare the volume of tickets with the number of representatives required to handle those requests. The fewer people it takes to answer more tickets, the more productive your product support.
But just how do you make that happen?
Once you reach full capacity, there’s not a whole lot you can do other than expand the team. What you can do is automate answering frequent questions with chatbots.
By allowing the customer to interact with a chatbot to direct them to the right documentation or provide information, you’ll be able to answer more tickets without requiring more reps.
Customers no longer rely on one channel for support. They fully expect customer support to be available to them in as many mediums as possible. However, that doesn’t mean you should spread yourself thin by serving every channel there is.
Rather, decide on a cohesive strategy that works for your product. Where are your customers spending the most time? Is it through a pop-up chat on your website? Email? Twitter? Phone?
Once you pick the ones you want to focus on, make sure you’re providing an omnichannel support experience. This means you don’t have to log on to each individual platform to answer support queries. Customers get consistent service across all channels.
What happens on each platform isn’t kept separate––it’s integrated into your support ecosystem so that everyone can see what’s happening. Everywhere. At all times.
Finally, preventing a problem before it even occurs is the hallmark of great product support. If you notice trends, take a proactive approach to solve them before it impacts customers. They may never know what didn’t hit them, but you do.
Not everything needs to be a new feature. But if you do notice a pattern where your customers always come to you asking about a nonexistent function or process, it’s worth taking note.
Having a better idea of your product support through analytics can provide a path forward for your product roadmap.
A great product support workflow works in two ways––it serves both internal and external needs.
Looking for an automated product support platform? Schedule a demo with Boomtown today.
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