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Chatbots vs. Knowledge Bases

Chatbots Vs. Knowledge Bases: Choose the Ideal Support Tool

Category: Customer Support

Last updated on Oct 1, 2024

Chatbots vs. Knowledge bases is a tricky choice to make.

Surely, keeping up with customer engagement is a 24/7 job.

Coming out of the pandemic, we’re on the other side in 2024, where customer expectations are rising. If you resist them, they prefer to handle resolutions themselves.

As per the state survey of customer service, three overly discussed topics we heard from leaders were:

  • Rapid changes in customer expectations
  • The advent of AI-powered chatbots
  • More focus on internal collaboration

That made us realize companies are constantly putting more demand on support teams to provide better experiences to customers.

As people-focused professionals, we believe the only thing that can make the difference is ‘Agility’. That’s what CRM and support leaders are building strategies around that involve

  • self-service capabilities,
  • AI-powered tools and
  • Streamlining workflows

All this makes sense when you onboard a new user, and they need more visibility or peeping into your product.

This is where chatbots and knowledge bases come into play. They act as a gated strategy to help your customer provide better CX.

Again, it circles us back to the main question: Chatbot or Knowledge Base: Which one should you choose? Let us help you choose the right self-service strategy for your needs.

We’ll break the blog talking on both sides and open the end for you to decide.

Let’s start!

How Chatbots Help in SaaS Customer Support

Research says AI chatbots are the most preferred channel for customer service. Is it? We’ll see.

By definition, AI chatbots work the same way as humans when solving customer queries via online chat. They answer customer queries, offer solutions by asking relevant questions, and assign the queries to humans when they’re out of their capabilities. AI chatbots work on NLP models and learn from real-time interactions.

Learn how you can turn to AI chatbots to handle queries and alleviate pressure on service reps:

1. Always On, Always Responsive

AI chatbots never sleep.

Chatbots provide 24/7 customer support. Always monitor your website, checking queries, answering them, or escalating problems to service reps if or when they arise. It’s working even when your team member is on vacation. The customer journey is never fixed; every single time a customer comes with different levels of service questions, AI chatbots handle varying complexity levels within the same conversation.

For example, a customer in a different time zone is facing an issue with software access late at night. Instead of waiting for business hours, they can ask the chatbot and get immediate help, such as resetting their password or checking account settings.

2. Instant Responses to Queries/Help to reduce churn

“For a SaaS company, and I will stake my reputation on this, the most important metric is net revenue retention, “ says  Janet Schijns, CEO of channel consultancy JS Group. Later in the conversation, she also mentioned that churn saturates your revenue.

A customer shared an experience, in which the sales team was very active until a deal was sold and then stopped communicating with the customer until the renewal period came around.

For B2B SaaS buyers, the partnership is more valuable than a mere transaction; hence, they always look for top-notch customer support. In such cases, AI chatbots prevent top-level churn by instantly responding to surface-level queries, and if trained well, it help to solve high-level tickets as well.

Freshworks chat

Image Source: Freshworks

3. Reduces the burden on the support team/Frees up support agents

28% of agents quit their jobs largely due to burnout; AI chatbots significantly reduce their workload and increase the current support agents’ productivity.

Chatbots take over routine tasks, and agents can focus on building a smooth support workflow so that SaaS companies can build high-authority customer support.

4. Handles Multiple Queries with Personalized Touch

Chatbots utilize stored customer information to quickly analyze and provide tailored support.

They retain a record of each user interaction, ensuring customers don’t need to re-explain their issues during future conversations, enhancing the overall user experience with consistent and personalized responses. It’s all about how you are training your advanced chatbots using machine learning (ML) and natural language processing (NLP).

The more you explore it, the more you reap the benefits. AI can sharpen your self-service chatbots to handle highly granular customer service requests in less time.

Schedule a demo with one of our experts to take a deeper dive into Document360

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How Does Knowledge Base Help in Customer Self-Service?

A knowledge base, also known as a help center, is a self-help portal designed to help users navigate the product without the hassle of customer support. The knowledge base is a strategic asset to customer success. To deliver a great customer experience, there is no way to cut corners (reduce customer service costs); customers must have a knowledge database to use as a source of single-truth information.

Research shows that companies that use knowledge see 2.5 times the rate of customer self-service. Make a mark that it’s simply not a switch to have the full potential of AI self-service; you need AI knowledge base software that supports quality self-service experiences.

1. Empowers Customers to Find Answers Independently

Modern knowledge bases skip the traditional step of finding relevant links to find the specific answer to the question. With Document360’s Ask Eddy, AI search capabilities are enhanced by deep integration into their platforms. You can seamlessly integrate AskEddy AI into your products and deliver precise, relevant information without redirecting customers through multiple links. This improves the experience and reduces customers spending time searching for answers.

Results? Increased customer satisfaction and trust in self-service tools.

self-service tools

2. Provides detailed guides and documentation

Content creation takes time and effort; knowledge-based software like Document360 aids your documentation process. Using AI writer tools, you can perform actions like outline creation, improving text, changing tone, converting speech, and more.
You can create a database of your product’s technical specifications in depth, structure it clearly without worrying about the word limit, and host the knowledge base on your website.

documentation guide

3. Consistent Information

You can update content without any coding required, unlike chatbots, where you need to train NLP processors to provide the right answers. Here you can update content in multiple verticals like videos, text-only information pages, audio, or guided interaction with the app.

You process the information like a new feature or a transition in an existing feature. It’s good practice to update the knowledge base. This takes very little effort, and the information stays consistent without breaking the flow as multiple stakeholders are working on the document. Using self-service, you can share your company’s brand and values without any confusion.

What are the differences between a knowledge base and a chatbot?

If you ask us, our vote goes to the knowledge base, it’s a dedicated AI assistant that helps you scale self-support by creating an in-house help center with full access to your knowledge base.

The user can access all the resources without leaving your product, even your chatbot that’s integrated into your website. So, all hail knowledge-base sites or knowledge-base software like Document360 for enhancing customer self-service.

With fair intention, here’s a detailed differentiation between a chatbot and a knowledge base.

Here you go!

 

Knowledge Base

Chatbot

Information Access

 

Information is presented in a static, searchable format. Customers manually browse or search through articles, FAQs, and guides to find relevant information.

 

Offers an interactive, query-based experience. Users type their questions, and the chatbot dynamically provides answers or directs them to specific resources.

 

User Experience

It relies on self-guided exploration, where users read articles or instructions at their own pace, often requiring them to interpret the material and apply solutions on their own.

 

It provides a conversational experience that mimics human interaction. It guides users step-by-step, asks follow-up questions, and offers personalized suggestions based on their specific queries.

 

Update and Maintenance

 

Generally easier to update. Content creators can modify or add information directly to articles or FAQs without needing technical adjustments.

It requires more complex optimization. Regular training and tweaking are needed to improve the chatbot’s ability to understand new queries for relevant responses.

Explore learning

The knowledge base allows users to navigate and explore more deeper learning. It provides the advantage of learning and onboarding with visual effects.

A Chatbot still relies on a Knowledge base for any further learning.

Still in a dilemma?  Read further.

What is AI Chatbots in Knowledge Bases: A next-gen Customer Self-Service

65% of CX leaders say traditional customer service methods are outdated compared to the self-service bots.

Traditional knowledge-base chatbots search for keywords and drop down the list of top knowledge-base articles to answer FAQs. But AI agents have more to it.

“AI Chatbots in knowledge bases provide AI-powered self-service, which includes a wide range of applications from evolved bots (aka AI agents) to automated responses to sentiment analysis—as well as tips for ensuring accurate advice, enabling smooth bot interactions, and striking the right tone or personality of bots. “

For example, Kommunicate is chat software for websites that allows customers to contact website handlers in real-time. Document360 comes with an integration feature where you can integrate Kommunicate with your Document360 knowledge base. Using Communicate also cuts costs, as a single agent can talk with several customers simultaneously and still retain the same high customer satisfaction rates.

What do these AI-powered chatbots do?

  • Search through your knowledge base to find and summarize relevant information.
  • Integrate with conversation flows and backend systems to offer personalized and precise responses to more complex inquiries.
  • Deliver smarter, context-aware assistance for users.
  • Recommend relevant articles or resources from the knowledge base.
  • Analysis of the content gaps to help businesses optimize their content and refine their knowledge base for better accessibility.

The Verdict

Both chatbots and knowledge bases have their ups and downs in self-service. But if we count chatbots, they have many limitations, like complex training and compact support. And most importantly it still relies on a Knowledge base for training and fetching the answers.

Whereas, a knowledge base is a great self-service option as it helps SaaS users get their answers in a brief manner anytime without any delays.

Everything aside, your knowledge base reflects your product learning curve. It acts as an education hub for new users and helps them learn your product.

Want to start offering in-app self-service support?

An intuitive AI-powered knowledge base software to easily add your content and integrate it with any application. Give Document360 a try!

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Frequently Asked Questions

  • What is the difference between knowledge base and chatbot?

    Knowledge Base is a centralized repository of information (documents, FAQs, guides) where users search manually using keywords or categories. Wheras, chatbors is an AI-powered tool that uses NLP to respond to user queries in a conversational format, often retrieving information from a knowledge base without requiring manual search.

  • 1Rule-Based Chatbots: Follow predefined conversation paths using set rules. Example: A customer service bot that answers basic questions like “What are your working hours?” AI-Powered Chatbots: Use machine learning and NLP to understand and respond to complex queries, improving over time. Example: Google Assistant or Siri. Hybrid Chatbots: Combine rule-based logic with AI, switching to AI for more complex queries. Example: A bot that escalates to AI for advanced responses. Voice-Activated Chatbots: Respond to voice commands and engage in spoken conversations. Example: Amazon Alexa or Google Home.

  • NLP is the technology that allows chatbots to understand and process language, while a chatbot is the actual interactive system that uses NLP (among other technologies) to engage with users. In essence, NLP powers the chatbot’s language capabilities.

  • 1. Identify Key Topics: Analyse user queries to determine relevant content, focusing on FAQs and troubleshooting guides. 2. Organize Content: Structure information logically into categories (e.g., Product, Features, Support) for easy retrieval. 3. Create Searchable Content: Write clear, concise articles with relevant keywords to improve searchability. 5. Integrate with the Chatbot: Use APIs to connect the chatbot with the knowledge base for efficient information retrieval. 6. Add NLP Capabilities: Implement NLP to help the chatbot understand diverse user queries. 7. Implement Feedback Mechanisms: Enable user feedback to refine and update the knowledge base continuously 8. Test and Iterate: Regularly test the chatbot’s performance and refine the knowledge base based on user interactions.

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