The machines are on their way, or rather have already arrived into every aspect of our being to help us live better, think smarter and solve all our questions.
From the time one types in a question into google, to when we place an order on Uber eats, AI powers every aspect of our interactions with our fellow beings and when it comes to supporting operations, the machines, specifically AI – is our absolute best friend.
This doesn’t mean that support agents are out of jobs. Let me elaborate. With the advent of ATM’S access to immediate cash meant that bank tellers were no longer needed, but we still feel comfortable drawing and depositing large amounts of money with a bank teller, rather than an ATM.
The bridge of effective customer support – that which works with agile First call resolutions, rarely breaches a Service Level agreement and one that maintains an acceptable average call handle time can be achieved when the powers of human and artificial intelligence culminate.
The Knowledge Base brings this vision to fruition. With a large amount of support queries being received on a daily basis, companies can implement the power of machine learning and AI to create a system where support agents can consistently refer to Knowledge bases to close tickets and leave customers with a smile.
Having said that, in order to create a seamless customer support experience, one needs to first step back to the basics and design a support hierarchy that works with a culmination of human and artificial intelligence combined.
Create a ticket triaging pyramid
While designing a ticketing module using a Customer service software, there are a few specific skillsets that agents need to possess to offer up effective solutions. For this, there needs to be a ticket routing strategy where your entire support force is put into a round-robin model where each agent can handle multiple calls at once. To put this into context there are 3 types of ticket routing techniques that you can implement, namely;
• Direct Routing
While using a traditional IVR model, customers are given an option to specifically pick the department they need to speak to, a post which the ticket is forwarded to the concerned agent
• Least Idle Routing
While all your agents are busy, a few may not have received a ticket for quite a while, the customer service software can be configured with an algorithm that sends the ticket to the agent that has been sitting idle for the longest time.
• Skills-Based Routing
This a higher level of support, wherein agents are specifically trained in a certain skill set. So when a ticket arrives that requires the assistance of said skill, the query is forwarded to this agent
Avoid using automation as quick fixes
Don’t turn to automation as a quick fix. While automated CRM chatbots seem like a great solution to self-service, customers reach out to your support team after having tried the self-service formula.
A support leader’s main focus is to have his customer satisfaction scores on the higher side, although this may seem like a good metric to judge the effectiveness of your team, often it may lead to unsatisfied customers because their tickets were closed in a huff.
In such a case your team needs to be equipped with a smart knowledge base. While maintaining FCR’S your agents can turn to these knowledge bases to further improve their ability to personalize their connections with customers. This personalization makes the customer feel that the agent is truly interested in figuring out the itch he is scratching. The knowledge base needs to be a storehouse of every possible iteration of a query that could arrive. As your team continues to operate, your knowledge base can be continuously updated.
Put Yourself In The Customers Shoes to Design a Strong Knowledge Base
Putting yourself in your customer’s shoes helps you brainstorm on the types of problems they may encounter. With these insights, you can write up faqs and articles with workflows on how to sort these problems out.
During the training phase, help your agents develop the skills needed to think about the needs the customer may be facing, this will help them ask the right questions using which they can track down the relevant information on the Knowledge Base.
CONCLUSION
While First Call resolutions and strict SLA’S are good key performance metrics for your support team, there has to be a good medley of AI and human intelligence, because at the end of the day AI is just a form of human intelligence. But if you can create a pyramid of support where AI and humans work together to keep your CSAT scores high, you can expect your support team to be the key indicator for customer retention and satisfaction.
