Ways in which support teams can use AI to offer better support

With AI tools, your support teams can resolve queries in seconds and not hours, without having to navigate through different apps and a scattered knowledge base.
Author:
Priyanshu Anand
Last edited:
September 2, 2024

Latest data highlights a significant shift in customer service dynamics, with AI-powered agent support and customer service technologies making significant strides. Research indicates that integrating AI solutions can elevate agent efficiency by as much as 40% and slash customer service expenses by up to 30%. Additionally, AI-driven chatbots and self-service portals are now managing up to 80% of standard customer inquiries, allowing agents to dedicate their time to more intricate issues. The contribution of AI in augmenting the skills of support agents is just as critical, if not more so, than its direct involvement in customer engagements.

Preparing the team to work with AI

Cultivating a tech-friendly environment is the first step. Encourage curiosity about AI tools and provide access to training resources that highlight AI functionalities. Whether it's online courses, workshops, or hands-on training sessions, the goal is to make your team comfortable and confident in using AI as part of their toolkit.

Introduce them to the idea of AI Agent Assist and how can it benefit them when it comes to everyday support functions like resolving tickets, talking to customers, understanding problems, and more. Before being comfortable with working with AI, your agents should be comfortable with the idea of working with AI. There has to be acceptance towards AI Agent Assist and that will only come from educating agents about the benefits of AI in their existing processes and not by forcing them into change that’s unnecessary or they’re not comfortable with.

You can follow these steps to get your team in tune with AI -

  • Training and nurturing the team with AI tools.
  • Tailoring and customizing AI to become more personalized for the team.
  • Integrating and installing AI across multiple channels.
  • Leveraging AI Insights to improve how they work

Prioritize your agents

When your agents feel valued and supported, their job satisfaction skyrockets. This isn't just feel-good fluff. Satisfied agents are more engaged, more empathetic, and more motivated to go the extra mile for customers. The result? A customer service experience that feels genuine, attentive, and human.

When we talk about making your agents feel valued, this includes making certain changes to processes that might otherwise be strict when it comes to meeting individual targets like ticket resolutions or KPIs as a whole team like First Response Time, Average Handling Time, First Contact Resolution, and more. Working with higher ticket volume can be tricky but that shouldn’t put pressure on the agents just to ‘close’ tickets as fast as possible, without caring about what’s at stake in order to get there.

With AI tools like Threado AI assisting your agents, even with higher volume, customer satisfaction doesn’t suffer because you see much higher First Contact Resolutions from the bot being able to comprehend and answer queries accurately at once. With the help of the bot, agents save a few minutes searching and curating answers for customer queries which amounts to hours saved every day of manual redundancies. Therefore, higher agent throughput leads to higher customer satisfaction automatically.

Organize your entire knowledge base

Threado AI can be trained on help articles, support tickets, customer conversations, internal docs, and more across different integrations - Zendesk, Freshdesk, Confluence, and Notion. Furthermore, you can train the bot on any URL, knowledge base, PDF, or even community conversations on Slack and Discord. This gives the bot an edge in a way that it’s not only aware of knowledge bases, internal docs, and product knowledge but also intricate customer tickets and historical conversations with agents.

Once Threado AI has been trained, it automatically aligns with your entire knowledge base and organizes it. The best part is, when Threado AI responds to a query, it also gives links from where the information has been sourced so the team member can reference and verify the accuracy of the answer. This saves the team hours of time and effort of having to search through knowledge bases and instead resolve the queries in seconds.

Auto-suggestions and auto-improvements

Based on the data that it gets trained on, Threado AI can answer queries for teams without them having to spend hours searching, writing, and curating answers for customers. What’s more, Threado AI gives cited sources for the answers so users can verify the accuracy of those answers using the references.

You can also use the auto-improve feature and define the tone in which Threado AI should improve the answer. This feature personalizes your answers and improves them to match a custom tone to make them sound more professional, make it formal, keep it casual, or make it more empathetic.

Omnichannel support

The digital age has enabled customers to become tech-savvy and now, a lot of them use multiple social platforms and products which increases the channels through which they can communicate. And hence, they want the product that they use to be accessible via platforms that they’re comfortable with. This creates a necessity for organizations to offer support across platforms aka omnichannel support that can allow customers to comfortably raise their concerns without having to be confined to specific platforms they are familiar with.

Threado AI is the most efficient AI assistant for Slack where it automatically resolves queries across channels. Works as a Chrome extension that sits on top of ticketing and customer conversation tools like Zendesk and Freshdesk. Can be easily installed as a web widget on your product or website.

Optimize knowledge base for higher reliability

Through continuous monitoring of team interactions with Threado AI, you can understand and identify gaps in the knowledge base through the queries that weren’t answered or were downvoted as an expression of dissatisfaction with the answer. These gaps can be filled by upgrading and bulletproofing your knowledge base which doesn’t just help the team in getting more accurate and reliable answers, but also any public documentation for customers can be used for self-help, reducing the need for consulting a solution expert or support agent altogether.

Identifying shortcomings is key and can be achieved by tracking questions the bot struggles with or answers that are incorrect or unsatisfactory for customers. These instances present a chance to expand the bot's understanding of the product and therefore the ability to resolve queries faster, leading to a progressively optimized knowledge base.

Empower customer-facing teams with AI

Of course, it’s not always smooth sailing. Despite how much you try to remove friction from the process, it can be challenging to ensure your entire team is on the same page about things. Furthermore, there are other challenges like budgeting constraints, resistance from your team, technical limitations, etc. In all this, moving towards an AI tool can ease things, and the impact is felt almost instantaneously which is an even more significant factor for the acceptance of AI and even more so for the transition towards it.

One of the most important factors for support teams to consider is the ability to be able to find and answer queries faster. The whole process of searching, understanding, writing, and curating a response for customers is extremely time-consuming and therefore unproductive. With AI tools, your support teams can resolve queries in seconds and not hours, without having to navigate through different apps and a scattered knowledge base.

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