18 chatbot best practices for your business

Chatbots have recently emerged as a powerful tool within the modern business landscape—but they’re only as powerful as the companies utilizing them allow them to be. The ultimate success or failure of your bot is heavily dependent on how well it’s trained, integrated with existing systems, and maintained over time. Thus, it’s essential to introduce and clearly communicate a collection of best practices to help guide the actions of both your chatbot and staff tasked with managing its performance.

These comprehensive guidelines serve to walk your organization through every phase of chatbot implementation, from the planning stage to building your bot and verifying its continued effectiveness. A proven set of best practices can position your company to get in front of any potential hurdles that lie in your path and quickly rectify any inefficiencies that might hinder your bot’s performance.

Today, we’ll take an in-depth look at what chatbot best practices are, why they’re so beneficial, and the specific strategies that your business can employ as part of its own approach.

What are chatbot best practices?

Chatbot best practices refer to a set of guidelines that ensure the effective design, implementation, and ongoing management of bots. These practices help ensure that the chatbot provides accurate responses, maintains a natural conversational flow, and continuously meets user expectations. Best practices can cover everything from planning for chatbot implementation, building it to suit your business needs, and monitoring its performance after introduction to a live environment.

Why are following chatbot best practices important?

Following a set of proven best practices is crucial for ensuring that chatbots deliver accurate, helpful, and consistent responses. By adhering to established frameworks, organizations can create bots that not only meet customer expectations, but also enhance satisfaction, reduce operational costs, and improve overall efficiency.

Some of the main ways in which these guidelines can enhance your businesses operations include:

Enhance customer experience & satisfaction

When a chatbot is equipped with advanced natural language processing (NLP) and machine learning algorithms, it can comprehend detailed or multi-step requests, which reduces the need for customers to repeat their questions. This leads to faster, more accurate responses, thus enhancing the efficiency of support.

Bots can also personalize responses based on user data—such as previous interactions, preferences, or purchase history—to make individuals feel more valued and understood. This not only increases the effectiveness of the interaction, but also builds rapport with end-users.

Better efficiency & productivity

When chatbots encounter queries beyond their programmed scope, such as complex technical problems or emotionally sensitive issues, transferring the conversation to a human agent can ensure the customer gets the best possible support. This intelligent handoff allows the chatbot to focus on routine tasks while live reps deal with more challenging cases, optimizing resource use.

Additionally, connecting a bot to customer relationship management (CRM), inventory management, or knowledge base platforms can further enhance efficiency. By integrating the chatbot with these systems, it can access real-time data to provide more accurate and personalized responses. For instance, when connected to a CRM, a bot can retrieve a customer's order status, recommend relevant products, or answer policy questions directly from the company's knowledge base.

Increased accuracy & consistency

Businesses often opt to designate suggested responses that are tailored to address frequently asked questions (FAQs) and provide step-by-step instructions for solving common customer problems. By stipulating predefined replies, businesses can maintain control over the information being delivered, ensuring it aligns with organizational policies, product details, and support standards. This not only improves the chatbot’s efficiency in handling requests, but also reduces the chance of providing inconsistent answers.

In addition, regular testing further guarantees accuracy by allowing companies to monitor and refine their bot’s performance over time. By running tests that simulate real-world interactions, businesses can identify areas where the chatbot may misinterpret queries or provide unsatisfactory responses.

Security & compliance

By continually tracking chatbot performance, organizations can detect unusual patterns and quickly take corrective actions to mitigate security risks. Monitoring also helps ensure that bots adhere to regulatory requirements, such as GDPR or HIPAA, by regularly reviewing how it handles user data and verifying that it doesn’t store or share sensitive information improperly.

Choosing the right tools for maintaining your chatbot plays a critical role in upholding security as well. Advanced chatbot platforms often come with built-in safeguards like encryption, user authentication, and secure data storage to protect sensitive customer information. Some solutions are even designed to meet industry-specific compliance standards, which can help companies avoid legal issues related to data privacy.

Continual improvement

Frequently measuring key performance indicators (KPIs) is vital for ensuring a chatbot's ongoing effectiveness and continuous improvement. Metrics such as response accuracy, resolution time, and customer satisfaction scores (CSATs) can all provide valuable insights into how well the bot is performing. By regularly tracking these KPIs, businesses can pinpoint areas where the chatbot may fall short—such as misunderstanding queries or failing to resolve certain types of issues.

Gathering feedback from support agents and customers can further contribute to these efforts. Representatives who deal with escalated cases can offer insights into the types of queries that the bot struggles with, while customers can share their direct experiences with the chatbot, including any frustrations or suggestions for improvement.

Successful chatbot use cases across the industry

In recent years, chatbots have evolved far beyond simple customer service tools, now finding applications across a wide range of industries. From retail to travel and financial services to education, organizations are increasingly adopting bots to automate processes, enhance customer interactions, and improve overall efficiency.

Let’s take a look at some of the ways in which chatbots might be used across different industries:

eCommerce and retail

In the ecommerce and retail sectors, chatbots have established themselves as reliable virtual shopping assistants, offering product recommendations, guiding individuals through their purchasing journey, and handling inquiries in a prompt manner 24/7. This recent evolution has done more than just simplify the shopping experience — it has turbocharged sales and forged stronger customer loyalty as well.

Travel / hospitality

Chatbots have emerged as valuable digital travel companions in the travel and hospitality industry. Here, they serve to provide real-time updates, assist with bookings, and offer personalized recommendations. They’re focused on making the traveler's journey smoother and more enjoyable, enhancing the customer experience (CX) from beginning to end.

Financial services

Finance bots are transforming the way customers manage their cash flow and investments. They're often tasked with tackling everything from routine account inquiries to complex transaction support, delivering quick and accurate responses that can build customer trust and loyalty.

Education

In the education space, chatbots have begun taking on the role of digital academic advisors. Bots can be leveraged to streamline processes, offer quick answers to FAQs, and enhance student engagement. Their primary objective typically revolves around making the educational journey more efficient and accessible for students and educators alike.

Enterprise

Enterprise-level organizations are increasingly utilizing chatbots to automate internal workflows and customer support, thereby improving efficiency and reducing operational costs. They can handle myriad routine inquiries simultaneously and at any time of day or night, which drives efficiency, cuts operating costs, and frees up human talent to tackle more complex challenges.

SMB

For small- and medium-sized businesses (SMBs), chatbots have positioned themselves as a go-to solution for scaling customer support and enhancing user interactions. They're capable of managing high volumes of queries without needing a large customer service team, helping to support business growth and improved efficiency.

5 chatbots best practices for the planning phase

Deploying a chatbot involves much more than simply choosing the right software—it requires thoughtful planning to ensure its functionality aligns with both business goals and user needs. The planning phase is where crucial decisions are often made, from defining the bot’s purpose to identifying the target audience and selecting the appropriate technology.

Some practices you can employ from the onset to ensure that your chatbot is poised for success include:

1. Set clear goals

Before development begins, companies should establish the primary purpose of the chatbot—whether it's to reduce customer service wait times, improve lead generation, or assist with internal processes. Defining specific objectives allows companies to tailor their bot’s capabilities to meet these goals, ensuring it effectively addresses identified pain points. 

Moreover, defining relevant KPIs like response times, resolution rates, and CSATs enables organizations to track how well their chatbot is achieving its intended outcomes. This continuous evaluation not only ensures that the bot remains aligned with its original purpose, but also highlights opportunities for further optimization as business needs evolve.

2. Ensure you are utilizing the best communication channels

Different customer segments prefer different platforms; some may opt to interact on social media, while others may lean toward mobile apps or websites. Conducting customer surveys or analyzing user behavior data can provide valuable insights into individuals’ preferred communication methods. Once you have a clear understanding of where your audience spends its time, you can deploy your chatbot on those channels.

While it is important to operate on multiple platforms, you should also ensure that conversations are interconnected across them all. Users often switch between different channels depending on the context or device they’re using, so providing a consistent chatbot experience across these touchpoints is crucial.

3. Determine KPIs to continually monitor

Here, the first step is to align your KPIs with the specific goals of the chatbot. For instance, if your bot’s primary objective is to improve customer service efficiency, metrics like average response time, resolution rate, and chatbot containment rate should be prioritized. Understanding your chatbot's purpose ensures that chosen KPIs reflect its role in achieving broader business goals.

Beyond organizational alignment, it’s important to emphasize metrics that provide insights into both customer satisfaction and operational efficiency. Monitoring user satisfaction metrics, such as Net Promoter Score (NPS) or CSAT, can help evaluate how individuals perceive their interactions with the chatbot.

4. Choose the right tools & software

Whether your focus is on customer support, sales, or internal task automation, different chatbot platforms offer distinct features designed for varying use cases. For example, if your objective is customer service automation, you may want a software that integrates well with your existing CRM and has advanced NLP capabilities to handle complex queries. 

Alignment with security, compliance, and scalability requirements is also essential. Chatbots that handle sensitive customer data, such as payment information or healthcare records, must be built on platforms that prioritize data security with features like encryption and user authentication. 

5. Determine how you want your chatbot to function

By outlining your bot’s intended purpose prior to implementation, your organization can verify that its functionality aligns with key business goals. For instance, if the primary focus is on improving customer service, your chatbot should be equipped with a robust knowledge base and the ability to escalate complex queries when necessary. Understanding the different activities the bot will need to handle helps ensure that it’s developed with the appropriate capabilities to meet those goals.

Companies will need to consider the type of user experience (UX) they want to deliver through their chatbot as well. This includes decisions about the tone and style of communication, personalization features, and how the bot integrates with existing systems. For example, a business aiming to create a personalized customer experience may want their chatbot to recall previous interactions, provide tailored recommendations, and access customer data from a CRM system.

8 chatbots best practices for the building phase

When building your chatbot, you’ll need to do more than simply selecting the right technology; you must train it sufficiently, verify that it can escalate to a human when necessary, and ensure proper feedback mechanisms are in place. By constructing your bot effectively, your company can make sure that it’s ready to provide real value and maintain a seamless UX at all times.

1. Train chatbot to understand complex queries

To start, developers must feed the chatbot a diverse dataset of conversations that reflect a wide range of queries it might encounter. This dataset should be annotated with intents (what the user wants to achieve) and entities (specific information like dates, names, or locations). As the bot processes this data, it learns how to associate different words, phrases, and sentence structures with specific actions, helping it handle varied user interactions.

Once deployed, your bot should be equipped with machine learning algorithms that allow it to refine its understanding based on feedback from live conversations. For instance, if your chatbot struggles with a particular type of question, developers can adjust its language models to improve performance.

2. Add suggested responses

Examining past interactions, support tickets, and feedback enable companies to determine the most prevalent topics and craft well-structured responses that address these inquiries effectively. These replies should be based on specific triggers or keywords, helping verify that the chatbot can quickly offer the most relevant suggestions, thus improving response speed and accuracy.

Don’t forget to regularly update these responses as customer needs evolve or your business introduces new offerings. This can be achieved by monitoring chatbot interactions and gathering insights on areas where suggested replies are lacking.

3. Use clear & concise language

You should strive for your chatbot to deliver straightforward answers that avoid jargon, overly technical terms, or lengthy explanations, as these can confuse users and lead to frustration. By keeping responses brief and to the point, bots can deliver information efficiently, helping individuals quickly find the solutions they need. 

Even more, clear language can help your chatbot handle diverse audiences with varying levels of technical knowledge or familiarity with your organization. Avoiding complex sentence structures and unnecessary details allows bots to communicate effectively with both new users and experienced customers.

4. Have easy access to human agent

To ensure that individuals can easily transfer to a live agent when necessary, it’s essential to design your chatbot with clear escalation paths that can guide users to manual support, a common staple of chatbot design best practices. For example, your bot might offer an option early in the conversation for users to request human assistance or automatically route them to an agent if it detects frustration or specific trigger phrases like “I need help from a person.”

In these situations, integrating the chatbot with customer service platforms and live chat tools allows for seamless handoffs to human agents. When a transfer is needed, your bot should relay key details about the interaction—such as the individual’s query, relevant context, and any prior troubleshooting steps—to the human agent. This prevents users from needing to repeat themselves, speeding up the entire resolution process.

5. Personalize chatbot interactions to customers

When building your chatbot, integrating it with CRM systems or external databases allows it to access details such as purchase history, location, or previous support inquiries. This information enables bots to deliver responses that are tailored to an individual's specific needs, such as offering personalized product recommendations or recalling previous conversations. 

Your chatbot should also be able to detect when a user prefers more formal language versus a casual tone or when they require detailed information versus a quick answer. To help achieve this, incorporating NLP techniques can help your bot to identify subtle nuances in user input, allowing it to adjust its style of communication accordingly.

6. Implement easy surveys to end of interactions

Implementing surveys or feedback forms directly within chatbot interactions serves as an effective way to gather valuable feedback while keeping the process user-friendly. When these surveys are offered directly within the chat window and immediately after a conversation ends, it’s more likely that individuals will participate since they don’t need to navigate away or spend extra time filling out long forms.

These surveys should be customizable based on the nature of the exchange as well. For instance, if the chatbot helped an individual with a purchase, the survey might focus on the ease of completing the transaction, while a customer service inquiry might ask about problem resolution and response quality. 

7. Integrate with current systems

Prior to building your bot, it’s paramount to identify the key systems that it will need to connect with to access customer data, retrieve order information, or manage support tickets. For example, integrating your chatbot with inventory or order management systems can help it to provide real-time updates on product availability or shipping status. These connections ensure that your bot can deliver relevant and accurate information across all touchpoints and on every occasion.

Additionally, connecting a chatbot with your existing infrastructure helps streamline business operations by automating routine tasks and improving data flow between departments. This not only improves efficiency, but also helps maintain consistency in customer interactions across different channels.

8. Provide easy exit options

Users should always have a clear and simple way to leave chatbot interactions at all times, whether they want to end the conversation or be transferred to a human agent. To achieve this, bots might offer commands like ‘exit,’ ‘end chat,’ or ‘talk to a human’ that can be triggered throughout an interaction.

Providing seamless transitions to other support channels, such as phone support or live chat with an agent, can enhance the overall UX as well. When your chatbot encounters a problem it can’t solve, it should automatically offer the user the choice to be connected with a human, ensuring a smooth handoff. 

5 chatbots best practices for the monitoring phase

It’s important to keep in mind that the work doesn’t end after your chatbot has been constructed and introduced into live production. Now, you’ll need to regularly track pertinent KPIs, such as response accuracy, resolution rates, and customer satisfaction levels, and collect user feedback to assess how well your bot is performing. Habitually reviewing this data empowers organizations to identify patterns and areas where the chatbot may need to be adjusted.

Factors to keep in mind throughout post-chatbot implementation implementation monitoring include:

1. Continually measure KPIs and respond as needed to data

Analyzing established KPIs regularly helps identify areas where your chatbot excels and where improvements are needed. By consistently monitoring relevant metrics, businesses can detect performance trends early, allowing them to respond proactively before issues escalate and negatively impact the user experience.

Responding quickly to KPI data involves making data-driven adjustments to your bot based on real-time performance insights. If metrics indicate a high abandonment rate, for example, it might signal that your chatbot is struggling with certain types of queries. In such cases, refining its NLP capabilities or updating its knowledge base could improve performance.

2. Run regular testing to ensure chatbots are functioning properly

Even after a successful launch, various factors like system updates or changes in customer behavior can impact your chatbot’s performance. Regularly testing can assist in identifying potential issues, such as response delays, broken links, or misinterpretation of user queries, before they negatively affect the UX. This might include conducting experiments across different communication channels to confirm that your bot consistently delivers accurate and timely responses across all touchpoints.

Frequent testing also enables companies to verify that any chatbot updates or new features are working as intended. For instance, if the bot has been trained to handle new types of queries or integrated with new systems, these changes should be thoroughly tested to confirm they enhance performance without introducing bugs. 

3. Ensure transparency

One of the primary ways to achieve transparency with users regarding your chatbot is by clearly informing individuals that they’re interacting with one from the outset. This can be done through introductory messages or visual indicators within the chat interface. By setting expectations from the beginning, users are less likely to feel deceived and more likely to willingly engage with your new technology.

Another critical aspect here involves being open about how user data is collected, stored, and utilized. Companies should provide clear privacy policies and verify that users are aware of what information is being gathered during their interactions. This includes explaining whether data will be used for improving services, personalizing experiences, or shared with third parties. 

4. Be open to new channels

Modern consumers tend to engage with businesses through various platforms—whether it's social media, messaging apps, or traditional websites. By expanding your chatbot’s reach to new and emerging channels like WhatsApp, Facebook Messenger, or even voice assistants like Alexa or Google Assistant, you can create more opportunities for individuals to interact with your brand.

Experimenting with new channels can also provide valuable insights into customer behavior and preferences. Each touchpoint presents unique opportunities and challenges; for instance, users on social media might expect quick, conversational responses, while those on a website may seek more detailed assistance. Remaining flexible and open to integrating new communication platforms allows your bot to be tailored to fit the specific requirements of them all.

5. Regularly survey employees & customers

Customers can often provide valuable feedback on how well your chatbot software is meeting their needs, whether it’s resolving their issues efficiently or offering relevant responses. Simple post-interaction surveys asking about satisfaction levels, ease of use, and whether the bot solved their problem can help identify areas where the bot excels or falls short. 

In addition to customers, employees—especially those in customer support—can offer critical insights into your chatbot’s performance. Frontline agents might share observations on how well the bot handles inquiries before escalating them to a human, whether it effectively reduces their workload, and what improvements could be made to streamline operations.

Begin optimizing your chatbot today with Freshchat!

Ready to take your chatbot’s performance to the next level? Freshchat acts as an all-in-one customer engagement system, combining versatile chatbots with powerful live chat capacity to create the market’s most comprehensive communication solution.

Freshchat bots are driven by Freddy AI, our cutting-edge intelligent assistant, which leverages NLP and machine learning capabilities to converse with users in a human-like manner and constantly learn from their interactions. Our bots are available around the clock and can be deployed cohesively across multiple channels to deliver users a well-rounded omnichannel experience.

With Freshchat, your chatbots are extremely flexible, able to be molded to fit your unique brand identity and adjusted to match users’ preferences. When a bot can’t sufficiently answer a question, it leverages our handy IntelliAssign tool, which escalates the interaction to the most relevant agent who’s currently available.

We’d love the opportunity to show you exactly why Freshchat is the preferred customer engagement platform for businesses across the globe—sign up for a free trial or request a demo today!