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Exploring the Effect of AI In Improving Customer Support on Discord and Telegram

Exploring the Effect of AI In Improving Customer Support on Discord and Telegram

May 2, 2024

Your server is growing quickly, support requests are flooding in, and your mods are nowhere to be found. It’s a more common scenario than many online community managers would like to admit.

Discord and Telegram have become essential platforms for community-building and customer interaction in gaming, tech, crypto, and many other sectors. But how can growing communities efficiently manage the inflow of support requests (without hiring an army of mods)?

Like everything these days, artificial intelligence (AI) and machine learning (ML) might hold the key.

By deploying AI-driven chatbots powered by large language models on platforms like Discord and Telegram, companies are improving response times and customer satisfaction while reducing the load on human agents.

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How AI Chatbots Effect Customer Support on Discord and Telegram

No one wants to wait for an answer. Customers expect on-demand support that responds immediately with the right answers (and steps to follow). Two-thirds say speed is as important as price when choosing a brand.

But frankly, a lot of support tickets can be answered with a simple: “Have you read the FAQ?” or “Did you follow the install guide?” Even those simple responses take up valuable time that could be spent on complex issues needing human expertise.

Enter AI chatbots. Advanced systems use natural language processing (NLP) to answer questions conversationally, providing an experience that feels less like talking to a robot and more like interacting with a knowledgeable support agent.

Let’s take a look at some of the ways they’re changing customer support on Discord and Telegram.

Ticket Deflection

One of the most promising capabilities of AI in customer support is what’s called ticket deflection. Customers are directed to the right information before they create a ticket.

On platforms like Discord and Telegram, the fast-paced, real-time nature of conversation can lead to an overwhelming number of inquiries. Many of those can be addressed without human intervention.

By deflecting tickets, you’ll see:

  • Reduced workload for human agents: With AI handling routine questions and guiding users to self-help resources, human agents can tackle more intricate and complex topics that require a personal touch.

  • Decreased response times: When users get immediate answers from a chatbot, they don't have to wait in a queue.

  • Improved availability: AI chatbots with human like responses are available 24/7, which means customers can receive support at their convenience regardless of their time zone.

Shaving off 20% of tickets can make a huge difference, but there’s potential for even more. When Scroll implemented AwesomeQA’s bot, 66% of their community questions were answered automatically.

Product Development Insights

When you’ve deflected all the simple requests, suddenly, you’re left with a treasure trove of feedback. Every undeflected ticket—the ones that require direct human intervention—highlights a potential new feature or areas where the product or service can be improved.

They break down into multiple channels:

Feature Requests and Enhancements

Tickets that ask, “How do I do _____?” are like direct communication from the market to your product development team. The customers who take the time to reach out are engaged and invested in your product, which makes their input particularly valuable.

Anything the AI chatbots can’t satisfy reflects a user’s unmet needs or expectations, which is a potential new feature. They can also affirm or challenge the direction of your current development roadmap. They ensure that what you’re building is actually what your users want or need.

Self-Service Opportunities

Some customers reach out because they can’t solve their issues through available self-service options. Their struggles can reveal shortcomings in your knowledge base, help articles, or automated troubleshooting wizards.

It can highlight issues that may need human assistance today but won’t in the future. By examining these inquiries, you can continuously expand and improve your self-help resources.

Agent Actions

Tickets that need specific action from support agents, like toggling a setting or making account changes, can suggest areas where users could be given more control. They can also highlight limitations, signaling problematic user flows to developers and designers.

Support Team Distribution

The advent of AI-powered chat is also reshaping the composition and structure of support teams themselves. With lower-level inquiries being effectively managed, the demand shifts from quantity to quality in human support staff.

In traditional support models, the structure often resembles a pyramid. There is a large base of level 1 support agents focused on addressing the most common and easily resolvable issues.

These agents field the bulk of incoming tickets, providing the first line of defense. More complex issues are escalated up the pyramid to more specialized and experienced staff.

When AI chatbots effectively absorb the majority of routine, low-level support inquiries, the pyramid structure begins to flatten. Instead of a broad base of entry-level agents, organizations now require skilled specialists and experts equipped to handle the nuanced, complex problems that AI models cannot resolve.

Cost Considerations

Implementing AI tools in customer support isn't without financial implications. Organizations have to decide between open-source and proprietary chatbots while also considering their budget constraints and the potential return on investment.

Open-source chatbots often appeal to those with the requisite technical expertise and resources to customize their solutions. These AI chatbots can be less expensive upfront since there are no licensing fees.

However, tailoring them to specific needs requires a significant investment in time and development, and there can be hidden costs associated with ongoing maintenance and updates.

Proprietary or closed-source AI chatbots, on the other hand, generally come with licensing fees. These bots are often more user-friendly with dedicated support and maintenance from the supplier, but they can become costly, particularly for large-scale deployments. Some also charge per resolution, leading to unpredictable costs as support queries fluctuate.

Companies must strike a delicate balance when evaluating the costs of AI support bots. Solutions like AwesomeQA have recognized the need for a more predictable cost structure in AI support tools.

With a free-forever plan, AwesomeQA allows organizations to begin realizing the benefits of an AI assistant without upfront investment. This can be a game-changer for small to medium-sized communities that might otherwise struggle to justify the cost of more sophisticated systems.

As the community grows and support needs become more demanding, transitioning to a monthly subscription can keep costs manageable. The regular fee gives organizations the predictability they need for budgeting purposes and the flexibility to plan for future growth.

Interaction Volume

One unintended consequence of integrating AI chatbots into Discord or Telegram could be a surge in the volume of interactions due to the simple, user-friendly nature of chatbots.

As they become known for providing quick answers, users may start treating them like a search engine instead of a support agent. While a spike in interaction seems positive on the surface, it could also lead to increased costs (especially with per-resolution pricing) or clutter the server with redundant questions.

To mitigate this issue, there are a few strategies:

  • Accessible knowledge base: Ensure that your FAQs and resource library are accessible and easy to navigate.

  • Proactive engagement: Design your AI chatbot to proactively offer help or suggest resources.

  • Feedback loops: Use data from the questions to refine the AI’s understanding and responses.

  • Structured user journeys: Guide users through structured pathways that lead them to the right information without open-ended questions.

  • Limitations and filters: Thresholds or filters for the AI chatbot to recognize when an issue is beyond its scope.

By intelligently curbing the excess and focusing on meaningful engagements, companies can ensure their customer support systems are robust, responsive, and cost-effective.

Software Integration

It’s easy to imagine how AI support bots could integrate with other systems. Instead of simply being able to answer questions or conduct a web search, it could take action itself.

For instance, a user running into an access issue could be helped right on the spot:

  • User - I’m trying to access the moderator panel, but I can’t.

  • AI Chatbot - It seems you don’t have the required permissions. Would you like me to adjust them for you?

  • User - Yes

  • AI Chatbot - Done! You now have moderator access. Is there anything else I can assist you with?

These kinds of integrations can elevate the responsibility of the AI, though, meaning organizations have to ensure security and privacy.

Knowledge Base Value

The effectiveness of AI chatbots relies heavily on the quality and comprehensiveness of the underlying knowledge base. As AI chatbots become more scalable and accessible, the significance of a well-maintained and structured knowledge base skyrockets.

It becomes an essential asset that can significantly influence customer experience, ticket resolution rates, and overall efficiency.

However, many companies fall short in this area—their training data is not structured with AI in mind nor maintained with the necessary diligence. Organizations should view their chat history and knowledge bases as strategic assets that require investment in ongoing development and integration with AI systems.

Final Thoughts

Intelligent AI chatbots, backed by well-structured and diligently maintained knowledge bases, set a new standard for responsive, intuitive customer service. They deftly handle routine queries, direct essential human attention to complex issues, and continuously learn from chat history to serve better.

Why not try AI-powered customer support firsthand? Try AwesomeQA. Install it on your Discord server, test its capabilities, and witness the impact it can make on your support workflow. With a free-forever plan, there’s no barrier to entry—only opportunities to seize.