Chatbots have become integral to modern business operations, from handling basic customer inquiries to guiding users through complex processes.
But what exactly are chatbots used for?
Chatbots are digital assistants powered by artificial intelligence (AI) that automate tasks and provide real-time support.
Customized chatbots can handle everything from answering frequently asked questions (FAQs) to processing orders. For businesses, this means less reliance on human agents for repetitive tasks. It allows teams to focus on higher-value interactions.
Chatbots are particularly useful in customer service, as they can offer 24/7 support, reduce wait times, and improve response rates.
But beyond customer service, chatbots have found applications in sales, marketing, and even internal business operations. They can help guide potential customers through the sales funnel, assist with lead generation, and even manage administrative tasks.
With advanced capabilities like natural language processing (NLP), chatbots can mimic human conversation for more personalized and natural interaction.
In this article, we'll explore the many uses of chatbots and how you can tailor them to align with your unique business needs.
How Do Chatbots Work?
Chatbots are designed to simulate human interaction using advanced natural language processing to understand and respond to user queries conversationally.
They interact through text or voice, making them useful tools for businesses and organizations to automate customer service, marketing, and sales processes. But how do they work?
There are two primary types of chatbots: rule-based and AI-powered. Each type functions differently, depending on the complexity of the tasks they are designed to handle.
Rule-Based Chatbots
Rule-based chatbots operate based on a predefined set of rules. They follow a script to respond to specific commands or keywords. These chatbots are ideal for handling routine and predictable interactions, such as answering frequently asked questions or assisting users with simple requests.
For example, a rule-based chatbot on a retail website might respond to questions like, "What time do you open?" or "How do I track my order?" Because the bot works from a predetermined script, it matches the input with the programmed response. However, the chatbot may struggle to provide an accurate answer if the user asks a more complex or unconventional question.
Rule-based chatbots are limited in functionality but relatively easy to deploy and maintain. They work well in environments where the questions and answers are known and straightforward.
Ai-Powered Chatbots
In contrast, AI-powered chatbots are designed to handle more complex interactions. These chatbots use artificial intelligence and machine learning to understand keywords and the intent behind a user's question.
NLP allows AI-powered chatbots to interpret and process human language, enabling their responses to sound more natural.
For instance, if a user asks something, the AI-powered chatbot can interpret the intent behind the question, even if the exact phrasing isn't what the bot was initially programmed to handle.
Over time, AI-powered chatbots can improve their responses by learning from previous conversations. This adaptability makes them suitable for more dynamic customer interactions, such as troubleshooting, personalized recommendations, and even managing complex queries that involve multiple steps.
Chatbot Use Cases in Sales & Customer Service
Instead of sending the same message to every customer, customer service bots can tailor their interactions based on their behavior, preferences, and past purchases. Here's a look at several key use cases where chatbots add great value to sales and customer service teams.
Chatbots Handle Questions and Inquiries
One of the primary ways chatbots are used is to handle questions and inquiries. Customers no longer need to wait for human agents to respond to basic queries, such as checking order statuses or learning about return policies.
If a customer wants to know, "What's your return policy?", the chatbot delivers a detailed response immediately. This reduces wait times, allows customers to quickly resolve their concerns, and frees human agents to manage more complex interactions.
Chatbots as Virtual Assistants
Instead of manually searching through various options, customers receive personalized suggestions that match their needs to make the buying process faster.
When a customer asks for assistance finding a product, the intelligent website virtual assistant immediately suggests options based on their previous interactions or browsing history. This boosts customer experience and helps promote the right products to customers.
Chatbots as Digital Sales Reps
Chatbots can interact directly with potential customers to help them through their purchase journey. These bots can answer detailed product-related questions, provide comparisons, and offer incentives, which makes them effective in closing sales.
For example, a customer looking to purchase a laptop may inquire about features like battery life or performance. The chatbot will respond with relevant information and highlight special deals or promotions.
Product Demos and Showcases
When a customer expresses interest in a product, the chatbot can provide detailed specifications, key features, and links to videos or reviews. It lets customers understand the product's value more clearly and feel confident in purchasing decisions.
Book Tickets for Events and Shows
Customers can browse available dates, select seats, and complete their purchases through an intuitive chat interface. This makes buying tickets much faster and more convenient, as customers no longer need to navigate multiple screens.
Automated Lead Qualifiers
Chatbots engage visitors with targeted questions to assess their needs and determine whether they are high-quality leads. Automation helps the customer support team focus on qualified leads and can make the sales process more efficient.
Lead generation chatbots also gather essential details, such as budget and specific product interests, then pass the lead to a sales agent if the prospect is ready to convert. It keeps engagement high without overburdening sales staff with unnecessary inquiries.
Personalized Sales Recommendations
Chatbots use advanced data analysis to offer personalized product recommendations based on customer preferences. Tracking user behavior and previous purchases helps the chatbot suggest products that align with individual tastes and needs.
A frequent customer returning to the website may be shown items that complement their past purchases. A personalized approach increases the likelihood of repeat purchases while improving the shopping experience.
Instant Quotes and Pricing Estimates
Chatbots simplify this process, especially in industries where products or services are customizable. Customers can interact with the chatbot, providing specific details about their project or order and receive an immediate pricing estimate.
This eliminates the need for lengthy email exchanges or phone calls, speeding up the transaction process and improving the overall customer experience.
Booking Demos and Sales Calls
Scheduling product demos or sales consultations is made effortless with chatbots. They handle the logistics of booking appointments by checking availability, suggesting times, and sending out invitations automatically.
Chatbots also send reminders about scheduled meetings, keeping customers and sales teams informed and engaged.
Handling Promotions and Special Offers
Chatbots can notify users about discounts, exclusive deals, and limited-time promotions as soon as they become available. This ensures customers are always informed of the best offers, driving more sales during key promotional periods.
Seamless Handoff Between Sales and Support Teams
When a customer inquiry escalates beyond the chatbot's capabilities, it can transfer the conversation to a customer service agent to promptly address the customer's needs.
This integration between sales, customer support, and other departments guarantees no customer inquiry remains unresolved.
Gathering Post-Sale Feedback
It's important to collect customer feedback after sales to help improve products and services. Chatbots simplify this process by prompting customers to provide post-sale feedback, such as a short survey or a request for a review.
Chatbot Use Cases in E-commerce
E-commerce chatbots are also invaluable in retail sectors for their personalized customer support. Below are some of the most impactful chatbot use cases in e-commerce, where they simplify operations and improve customer satisfaction.
Instant Order Tracking and Status Updates
Chatbots provide instant order status updates by pulling real-time data from backend systems. Customers can simply ask, "Where's my order?" and the chatbot will provide immediate answers, including estimated delivery times and potential delays.
Managing Returns and Refunds
Handling returns and refunds can be time-consuming for both customers and retailers. Chatbots simplify this by automating the process of return requests and refund management.
Customers can initiate a return or request a refund directly through the chatbot, which guides them through the necessary steps.
The chatbot can also provide updates on the status of the return, whether it's been approved or processed, saving both customers and retailers from lengthy support calls or emails.
Promotions and Discount Notifications
Chatbots are excellent at informing customers about promotions, sales, and discounts. They can analyze customer behavior and notify users about upcoming or ongoing deals tailored to their interests.
Timely and relevant communication boosts customer engagement and increases the likelihood of conversions during key promotional periods.
Assisting With Product Search and Navigation
Searching through large product catalogs can be overwhelming for customers. Chatbots act as virtual store guides to help users find products by filtering search results based on specific criteria, such as size, color, or price range.
Handling Customer Queries and FAQs
A well-designed chatbot can handle a wide range of customer queries and FAQs. Chatbots provide immediate, accurate responses, reducing the need for human customer support intervention. They can handle anything from questions about shipping policies and payment options to store hours and product availability.
Abandoned Cart Recovery
Abandoned carts are a common issue in e-commerce. However, chatbots can help recover lost sales by sending personalized reminders to customers who leave items in their carts. Interacting with customers in real time or sending follow-up messages encourages them to complete their purchases.
For example, a chatbot might send a message like, "You've left these items in your cart. Would you like to complete your purchase?" It may also offer a small discount as an incentive to close the sale.
Supporting Multichannel Retail Experiences
Customers often switch between online and in-store shopping. Chatbots support multichannel retail by seamlessly assisting customers across messaging platforms. If a customer is browsing on a website or mobile app or interacting via social media, chatbots can still provide a consistent experience.
Simplifying Payment and Checkout
Chatbots can reduce wait times in the checkout process by guiding customers through payment options, shipping methods, and discounts. Automating this process minimizes the chances of cart abandonment.
Chatbot Use Cases for Financial Analysis and Reporting
Financial analysts often deal with large amounts of data, from stock market trends to internal financial reports. Gathering and analyzing this data can be time-consuming, but using chatbots automates the process.
Chatbots can pull data from multiple sources, such as databases or financial systems, and compile it into clear, digestible reports. Analysts request specific data, like sales performance or stock trends, and the chatbot provides an updated report.
Chatbots also assist with forecasting and predictive analysis by analyzing historical data and generating future projections. Businesses use these insights to predict trends, market movements, or business performance for more proactive decision-making.
Chatbots Used Cases in Internal Business Processes
While chatbots are well known for their role in customer-facing operations, they are also useful for internal business processes. Let's explore how businesses are using chatbots to improve internal workflows.
Employee Onboarding and Training
Traditionally, onboarding can be lengthy and complex, involving paperwork, system setup, and information sharing. Chatbots can help by providing step-by-step instructions and answering common questions.
Chatbots also support ongoing training by offering access to tutorials, company resources, and quizzes. This makes it easier for employees to learn at their own pace and reduces the need for formal training sessions.
Internal Communication and Task Management
Communication within a team or across departments can be challenging, especially in large organizations. Rather than waiting for email responses or sifting through endless group chats, employees can simply ask a chatbot for information, updates, or reminders.
Regarding managing tasks, chatbots help keep teams organized and focused. They can assist with creating, assigning, and tracking tasks, setting deadlines, and sending reminders.
IT and Technical Support
Chatbots are also effective at providing real-time troubleshooting for employees' technical issues. Instead of waiting in line for IT support or navigating through long helpdesk tickets, employees can ask a chatbot for help and get immediate responses.
While chatbots are great for handling routine tasks, they also play an important role in escalating more complex issues to IT teams. When a problem requires more advanced support, chatbots can collect the necessary information and escalate the issue for human conversation.
The Challenges of Chatbot Technology and How to Overcome Them
While chatbots offer numerous benefits for businesses, they have certain challenges and limitations. Understanding these potential issues is key to optimizing chatbot performance and ensuring they deliver the best possible user experience.
Below are some common challenges and practical ways to overcome them associated with chatbots.
Limited Understanding of Complex Queries
Chatbots are great at handling simple tasks like answering FAQs or providing simple product recommendations. But, they can struggle with more complex requests or ambiguous language.
A basic chatbot might have difficulties offering a relevant response if a customer asks a vague or open-ended question without specific context. This can lead to customer frustration if the chatbot's answer doesn't meet expectations.
How to Resolve It:
Businesses can implement AI-powered chatbots with NLP capabilities to address this. Training the chatbot with various queries and using machine learning models helps improve its accuracy over time, enabling it to handle more complex interactions.
Additionally, integrating chatbots with a live agent handoff system ensures that when the chatbot encounters queries it can't handle, it can pass the conversation to a human agent.
Lack of Emotional Intelligence
Chatbots are often criticized for their lack of emotional understanding. While chatbots can process data and respond to factual queries, they struggle to understand or respond appropriately to emotional cues.
It becomes a limitation, especially in customer service scenarios where empathy and emotional intelligence are critical in resolving issues.
If a customer is upset or frustrated, a chatbot's inability to recognize and respond to this emotion may escalate the situation, leaving the customer unsatisfied with the interaction.
How to Resolve It:
Businesses can implement emotionally intelligent chatbot frameworks. While AI is not yet perfect at fully understanding human emotions, chatbots can be designed to recognize emotional keywords (e.g., "frustrated" or "angry").
In addition, integrating pre-built empathetic responses into the chatbot's scripts can help improve the tone of the conversation.
For example, if a customer uses words like "upset" or "unhappy," the chatbot can respond with, "I'm sorry you're feeling that way. Let me transfer you to someone who can assist you further." This small adjustment can make the interaction feel more compassionate and customer-centered.
Handling Multiple Languages
Businesses operating in global markets may need chatbots that can interact with customers in various languages. However, many chatbots are designed to work primarily in English or a single language. This creates a gap in serving a diverse, multilingual customer base.
How to Resolve It:
Businesses should deploy multilingual chatbots with robust language models that can be trained to understand and respond to users in different languages. In addition, businesses can localize chatbot responses to ensure they're culturally appropriate.
Implementing a language detection feature also helps the chatbot identify the language the user is communicating and switch to the appropriate language for that conversation.
Inability to Handle Complex Transactions
Chatbots often struggle to handle complex transactions requiring multiple steps or integrations with different systems. For example, processing a refund request that involves various departments (e.g., billing, shipping, and customer support) can be difficult for a chatbot to manage.
How to Resolve It:
Businesses can integrate chatbots with backend systems like CRM tools, inventory management, and payment gateways. This ensures the chatbot can access the relevant data and processes required to complete complex transactions.
When a customer requests a refund, the chatbot should be able to communicate with the order management and finance systems to process the refund in real time.
In cases where a transaction is too complex, chatbots can trigger escalation workflows and transfer the task to a human agent.
Over-Dependence on Scripts
Many chatbots operate using pre-written scripts, which means they can only respond to questions and tasks within the scope of those predefined responses. It works for simple interactions but becomes a limitation when users ask something outside the chatbot's scripted abilities.
Chatbots may fail to provide relevant responses, leading to poor user experiences.
How to Resolve It:
Businesses can develop AI-driven chatbots that use machine learning and natural language understanding (NLU). These chatbots adapt based on user inputs and learn from past interactions to provide more intelligent responses.
Over time, they’ll be able to handle more complex and varied questions, reducing reliance on rigid scripts.
Explore What Chatbots Can Do for Your Business
Denser offers you the ultimate solution to build powerful, personalized chatbots that are tailor-made for your business. You can integrate bots that help with sales inquiries, provide real-time support, or even recommend products based on customer preferences.
With this customer service chatbot software, you're not stuck with generic responses or basic features. You have complete control to design chatbots that match your brand's tone.
Discover how Denser's chatbot technology can impact how you interact with your customers. Sign up for a free trial, or schedule a demo today!
FAQs About What Are Chatbots Used For
Do chatbots help with product education and tutorials?
Chatbots are frequently used to deliver product education and interactive tutorials. They can guide customers step-by-step through complex product features or services, making it easier for users to understand how to get the most out of what they've purchased.
How do chatbots work together with human agents in hybrid models?
In hybrid customer service models, chatbots handle the initial stages of human interaction, answering basic questions or gathering information.
If the chatbot identifies needing a more detailed or personalized response, it transitions the conversation to a human agent. This balance between chatbot automation and human conversation allows businesses to offer quicker service while maintaining the personal touch for more complex cases.
Are chatbots able to understand emotions in human conversations?
While chatbots have improved in simulating human conversation, they still have limitations regarding understanding emotions. Some advanced chatbots can detect sentiments, such as frustration or satisfaction, based on keywords or the structure of the conversation.
However, they cannot fully interpret the emotional nuances that human agents naturally understand during more personal interactions.