Machine learning is a predictive analytics approach that allows computers to automatically learn by example, continuously adapting to new information. This approach involves highly advanced data science, but it does not mean that only advanced, well-established support teams can benefit from machine learning.
In fact, machine learning can play a valuable role in a team’s early stages and as the organization matures. From consistent messaging and improved user experience to taking productivity further than you ever thought possible, machine learning works to improve efficiencies. No matter what stage of the journey your support team is in, machine learning can help move you to the next.
You’ve Got it Covered
Maybe your team is brand new. Perhaps you’re easily managing the process of manually resolving each ticket as it comes in. Good news! Your needs are less complex and your agents are likely able to handle each and every task that is sent their way. It may seem like you have things under control. So, how does machine learning apply?
If the following list describes your current operations, then you’re right where you need to be to get your first leg-up from machine learning:
Tickets are manageable with no scalability issues
Basic ticket routing is set-up with limited macros
There are only a few views into the ticket system
At this stage, machine learning’s value is in providing a tool for consistent classifying and tagging. Without a consistent way to take in and tag tickets, routing and reporting are not as reliable as they could be. Putting a repetitive ticketing process in place means your team will be ready to take on even more as your organization continues to grow. As machine learning improves the process, customer support managers also have a better means for reporting real results back to the organization.
As your company scales, it’s also important that your agents deliver a cohesive voice for your brand message. Machine learning can start to identify common responses to questions, helping you get ahead of the curve on creating consistent templates and knowledge base articles. Which will let you scale in the future.
You’re Stretched Thin
You’ve been at this a while. Your ticket volume is high and there’s no sign of slowing. Perhaps agents are frustrated and your team is struggling under the weight of it all. You have support templates in place, but they aren’t necessarily consistent or easy to find - causing agents to go rogue and create templates of their own. You know productivity has to increase but you don’t want to add more overhead. So, how does machine learning apply?
If the following list describes your current operations, then you’re ready to leverage the automation power of machine learning:
A knowledge base exists for common issues
Basic triggers are set up
Ticket routing is set up with full macro coverage
Categorical views exist into the ticket system
At this stage of growth, your team is in the midst of balancing chaos and progress. Triage tactics aren’t as sophisticated as they could be and everyone feels it. Machine learning can match data from each support request (i.e. arrival time, request type, complexity, severity) with the best person on the team (i.e. skill level, account familiarity, specialty) to deliver each ticket into precisely the right hands. This skills based routing keeps agents from “cherry-picking” the tickets they consider to be high priority and keeps aggressive customers, who may not have the most important issue, from bullying their way to the top of the line.
Machine learning can also find patterns in tickets, analyzing the text and customer data, and match it to macros that agents used in the past to recommend the best response template. Easy access to consistent templates slashes the time and energy your support team spends searching through hundreds of templates. Machine learning can even find the most effective templates created by agents and allow you to roll those out globally for the whole team.
As more and more demands are made on your support team, machine learning can boost productivity and reduce response times to improve employee and customer satisfaction.
Your Team is Maxed Out
Busy doesn’t even begin to describe how your support team operates. Your volume is super high and you’re continually trying new ways to deflect tickets and reduce the amount of tickets coming at agents every minute.
If the following list describes your current operations, machine learning can tie together all of your automation tools to only bring in tickets that need a human touch:
Help tools already exist within the product
A comprehensive, self-service knowledge base is available
Support forms are available with internal system integration
Category specific auto-responses exist for customers
At this stage of growth, support teams can lean on machine learning to build up the value of the organization’s knowledge base - automating responses to relieve the pressure on support. Even more compelling is the technology’s ability to close the consistency gaps common to geographically dispersed team, such as tagging requests and assessing agent performance. Machine learning can shed light on internal process to suggest operational improvements that benefit the entire organization.
Plus, machine learning never gives up. As it learns from your team, your tickets and your customers, it adapts its predictions so it is always up-to-date with your current customer support needs and processes.
Learn how Wise.io can help your support team leverage machine learning to prepare for the next stage of their journey.