This article was originally published on Botium’s blog on April 6, 2021, prior to Cyara’s acquisition of Botium. Learn more about Cyara + Botium
The first thing we need to know: There is no such thing as the perfect chatbot!
Even in the creation of a chatbot, there is no best practice guide. Every chatbot behaves differently, depending on the purpose, topic coverage, and the target group. In general, however, there are various ways to build a chatbot and improve the quality in order to achieve a better conversion rate.
In the following article, we discuss the most important facts to build your “perfect” chatbot.
Personas: Understand and guide your users
A successful chatbot is not characterized by the technology behind it, but by a well-thought-out conversational design. We, therefore, have to put ourselves in the visitors’ shoes and adapt the flow of the conversations so that the chatbot delivers the appropriate answer as quickly as possible.
Less is more: When we start to create a chatbot we should only focus on the most important scenarios and optimize these processes accordingly. If these work well then we can add more stuff then.
Pre-train your Conversational AI
When our chatbot comes to life, it often only has a small amount of training data. We should therefore feed our AI engine with various phrases in advance in order to recognize the correct intent. Answers should be as generic and simple as possible so that the system does not have to distinguish between small things.
It is best if there is already existing data from previous communication channels (e.g. email or messenger). From this, intents can be derived and extracted in advance.
Train and test your chatbot continuously
Users will ask all kinds of questions that you don’t know at first. These new questions must then be fed quickly. However, this also changes the behavior of the chatbot. You should not assume that the chatbot project is finished at a certain point, because there is always something to improve.
So, once the chatbot is live, we need to continuously validate, adapt and test the newly trained data in order to improve chatbot quality.
Besides testing conversation flows, there are other important factors and methods to reach the state of a “perfect” chatbot:
- NLP Testing — Improve your chatbot understanding
- E2E Testing — Verifying the end-user experience
- Voice Testing — Understand your users on voice channels
- Performance Testing — Ensure your chatbot is responsive under high load
- Security Testing — Making your chatbot secure
- Monitoring — Get notified when problems arise
Choose the right chatbot engine/platform
As you may have noticed, there are a large number of vendors on the market, so it often seems impossible to know which ones fit your needs.
When choosing a platform also think about future plans so that you don’t have to change engines. You also could test platforms internally and use which fits best.
To help you to choose the right platform, here are a few points to pay special attention to:
- Coding or Non-Coding — You are a developer and know how to code? Or do you have developers on your side? Platforms that rely on coding are usually cheaper than those that offer a purely visual interface.
- Multilingual AI — Depending on whether your users are internationally based or just local: sometimes chatting in one language is not enough. There are platforms that speak local languages with region-specific terminology and nuances to ensure a natural and meaningful interaction.
- Multi-Channel Integration — Your users may use multiple channels like Facebook or Whatsapp. Think about which channels you want to cover in the future and choose your platform accordingly.
- Backend Integration — A chatbot has to be useful: This is where integration with backend interfaces comes into play. Make sure that the connection of your chatbot to the backend system is possible (e.g. CRM, ERP, SAP, Salesforce, and so on).
- Security & Privacy — When you look at the daily increase in cybercrime, security is critical. Chatbot platforms have different security standards, only partially comply with European data protection regulations, and should therefore be chosen carefully, especially if the conversations contain sensitive data.
- Sentiment Analysis — It’s important to see how your customers are reacting so that you can improve the experience and service. This can be done by manual analysis or automatically with a sentiment analysis feature
- Hybrid Chat — Some chatbot platforms can automatically handover to human agents when fallback intents occur to ensure high customer satisfaction
- Contextual Understanding — If needed, ensure that the system you choose can hold context, which means that the chatbot can associate information from the previous conversation flow and the current conversation step
Regardless of which platform you will use, from testing perspective you are always on the safe side by using Botium Box. It brings a plenty of connectors to connect to the respective platforms
Use a fallback strategy
There is one fact that cannot be denied about chatbots: Chatbots can’t answer all questions. Why? Either because the AI is not fully trained yet or questions that the chatbot is not designed to answer.
As chatbot developers, we also have to worry about fallback intents and handle them in detail. Often, the bad reputation of chatbots comes from exactly that.
There are several ways to handle these fallback intents, for example, you could capture the contact details and forward them to an employee who will get back to you later. Another way, for example, is to resolve the already triggered fallback intent with the intent that deals with the confusion of the questioner.
Give an idea of what your chatbot can do
Explain upfront how and what your chatbot can help with. This avoids annoyed users wasting their precious time asking questions that the chatbot can’t answer anyway.
Make your chatbot public
In order for users to use your chatbot, it must be made known. The strategy behind it depends on the status quo. In the beginning, it would maybe be better to maintain the current communication channels and run the chatbot in parallel.
Here are a few strategies you could use:
- Reference the chatbot in the emails via signature or in the newsletter
- Launch marketing campaign via social media
- Place a web widget on the website
Getting feedback is a must-have
Besides the information you get from analyzing sessions, simply ask users for feedback and suggestions for improvement. Getting negative feedback can identify opportunities for improvement. Keep it simple, leading to higher response rates. If the feedback is negative, ask the user how you can improve. This can provide a wealth of suggestions and ideas to further improve the chatbot.
Give your bot a personality
Instead of annoying customers with a robotic character, chatbots should have a personality. Especially for enterprise chatbots, one of the most important features is its personality.
Your chatbot’s personality represents your company on a personal level and should be present at every stage.
Here are some examples of how you can brand your bot:
- Avatar — a memorable image representing the chatbot
- A personalized greeting
- Individual asking and answering questions
- Providing information and services
Think about user experience
Designing a chatbot window is similar to designing other visual products. You should focus on including elements that follow the company’s branding, such as typography, color, and bubble background.
When interacting with the content, you should use rich interactions like buttons, quick replies, and cards to give the user predefined options to choose from. Using such elements enhances user experience extremely because users often don’t know how to write the question or what information the chatbot needs.
Conclusion
In summary, independent of which chatbot platform you will use, creating a “perfect” chatbot is a complex task, with many factors playing a role. For example, backend functionalities, the correct creation of conversations, and the design of the frontend have a high priority.
But the key factors are continuous training and the import of new intents, as well as testing on all levels and aspects. This is the only way to improve or maintain the quality to give your users the best experience.