6 Steps to Chatbot Conversation Improvement – How-To Guide

Chatbot Conversation Improvement Guide

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Your chatbot is live, congratulations! Now starts the real work. Real-world users can throw all types of inputs to your fresh bot, which may or not be ready to answer them.

Chatbots need to learn constantly so they can identify and answer user queries, improving the conversational experience. To ensure your bot conversation doesn’t fall flat, you need a systematic chatbot conversation improvement plan to detect issues and adapt to new inputs. In this post, we bring you a step-by-step plan to continuous chatbot conversation improvement. Let’s get started. 

Common Chatbot Conversation Fails

Chatbots offer an innovative way to connect consumers with companies. However, these are still the early stages, and both bots and consumers are still improving the communication. 

Despite the popularity, some companies are wary of the potential damage caused by chatbot pitfalls. For instance, a poll by Digitas and Harris showed that almost ¾ of consumers wouldn’t be back to a chatbot if the conversation went wrong the first time. 

The chatbot’s conversation flow can fail because of several causes. Sometimes chat bots don’t understand properly. Other times the conversation falls into a loop, causing users to tire of a bot and leave. See below some common chatbot mishaps to avoid: 

1. Dead Ends

While AI chatbots are gaining terrain, many chatbots available in the market are still rule-based. This means they answer according to a defined chart flow. Sometimes the decision tree is too limited, causing the chat to come to a dead end. 

chatbot example

This frustrates the user, which will quickly abandon the chat. Sometimes the bot engages enough in conversation and actually starts giving an answer, but then gets stuck because it doesn’t understand. Here, you can save the customer by referring to a human representative or offering an alternative communication way. For instance, if the bot doesn’t understand something two times, break the loop with clear next steps. 

2. Too Much Info, Too Soon

Users want quick responses. When the bot starts telling about offers and one message after the other, it can overwhelm the user. Take the Jamie Oliver recipe bot. It offers quick recipes based on an ingredient emoji. However, it fills the screen with so many messages before you actually can get the recipe. That makes the chatbot conversation flow tiring for the user. Check the video below to see the example:

image of a chatbot conversation flow with too many messages one after the other
Image source

The solution here could be to shorten the promotional part and go straight to the point that is offering the recipes to the user. You can add the promotions after delivering. That way you don’t risk the user leaving because it got annoyed by so many messages.

3. Too Dry or Too Friendly

Yes, your chatbot needs to have a personality, that’s right. But be careful to keep it friendly and match the tone of your company. If your company is more formal, avoid slang and witty remarks. If your company is more casual, let’s say a fashion store, a food delivery service, you should avoid sounding too stiff. 

Too friendly is also a no-go. Too talkative annoys the customer. Check this example with Poncho the weather cat:

weather chatbot demo

Image Credit: I just want to know the weather

While these cute messages are nice, sometimes you just want to know the weather. Keep your bot friendly, but not a chatterbox. 

4. Get Stuck On the Fallback Message 

This happens when your chatbot doesn’t understand what the customer is saying and gets stuck in a loop. If the bot doesn’t understand, don’t leave the customer hanging. Instead, let the bot admit the error with an error message, for example: “I don’t understand” and immediately direct the customer to the next steps

5. The Bot Doesn’t give Small Talk

Customers like the bot to feel personable. Even if they know they are talking to a machine, it should feel humanlike. Bots that get straight to the point without small talk are perceived as dry and may put off customers. Be sure the chatbot starts with a friendly greeting that encourages the customers to talk. 

Learn more about designing the perfect chatbot in this article

6 Steps to Continue Chatbot Conversation Improvement

So, how can you prevent these kinds of pitfalls? You can avoid some of them in the design itself, but others can appear after the launch. The only way is by continuously monitoring and improving the bot.  Follow these steps or a successful continue chatbot conversation improvement:

#1. Monitor the Chat Metrics

To monitor the bot performance, set conversation success metrics. This will help you identify weak spots and improve the chatbot. To achieve an effective chatbot enhancement, you should align the metrics to the purpose of the bot and your business goals.  

The metrics can vary, from monitoring the chat length, the use of certain keywords, or you can compare how customers rate the chat experience. To ensure the success of the strategy, compare the metrics over set periods of time.

You should also monitor the funnel sequence. This will allow you to find out at which step the customer is dropping out. Then you can tweak and refine that step. 

#2. Gather Chat Data

Once you decide which metrics are most effective, it is time to gather the information for analysis. You can collect chat transcripts, taking care of avoiding sensitive or private data. 

Analyze the information, checking where the bot fails. For instance, you can monitor the customer’s satisfaction with the bot. Then, you can retrain the bot to overcome these weak spots and optimize the performance. If you are working with a consultant, make sure they have the skills and tools to properly gather and analyze the data. If they don’t, you risk getting the analysis wrong. At SCSS Consulting we check the metrics, making sure no piece of valuable data goes missing.  

#3. Add Surveys

Another useful way to understand how your chatbot is performing, is to gather the opinion of customers during and after the conversation. Adding an In Conversation Survey (ICS) allows you to take the feeling of the customer during the conversation. You can also include an optional survey after each chat. It can be a link or a simple question. Made it easier by following these tips:

  • Ask the customer to give a rating 1-5
  • Give a short survey during the conversation to check how it is going. 
  • Ask a simple question: Did you find the conversation helpful? 
  • Add emoji buttons to simplify the answer
chatbot sentiment analysis

#4. Improve the Chatbot Conversation Flow

Customers have high expectations when chatting with a bot and sometimes forget the limitations of a machine. Users expect the bot to be as conversational as a person. 

On one hand, it is important to set the chatbot limitations to avoid giving false pretenses to the customer. On the other hand, you should aim to make the conversation as natural as possible. You can achieve that by using an AI powered bot, with natural-language processing capabilities. Here at SCSS, we specialize in customized AI chatbots that can interpret the intent of the customers and answer their queries. 

#5. Create the Feedback Loop. 

The idea is to create a feedback loop you can use to analyze customers’ responses to the chatbot. Benefits of creating a feedback loop:

  • Understand your user’s intent: when you analyze your user’s responses, you can detect what users are actually saying. Sometimes users can say things you didn’t expect. Therefore, you can detect new queries, or ways people are asking the bot for help. 
  • Keep the chatbot up to date: you can quickly adapt the chatbot dialogue to overcome failures and weak spots. Also, it allows us to identify trending topics and add new product offers.  
  • Manage user expectations:  having swift access to user feedback can help to meet user expectations. You can respond promptly, improving the chatbot dialogue according to the feedback analysis. 

#6. Have a Simple Process to Train your Bot. 

At the end of the day, you should make sure the process to improve your chatbot conversation flow seamlessly. Chatbot conversation improvement requires moving quickly. You cannot afford to wait a week for changes in the chatbot conversation. In that time, the customers can get annoyed and your business will suffer. Our experts at SCSS Consulting creates a straight and easy to follow a process that effectively implements a continuous development process. 

Types of Chatbot Improvement

Now that you gathered and analyzed the feedback and information, how can you use this data to improve the chatbot?  You can do it manually or opt for a semi-automated solution:

  • Manual improvements: you can do it manually, look on the metrics and make fixes accordingly. Examples of improvements can include adding new intents or adjusting the greeting, setting the expectations. 
  • Semi-automated improvements: if you use a chatbot with machine-learning capabilities you can automate improvements. As the customers use the chatbot, you can use this conversational data to train your bot model. The AI suggests what intents we should add to improve the accuracy of the bot responses. An expert then will review and approve/disapprove the suggestion.

Tips to Continuous Chatbot Conversation Improvement

Establishing continuous improvement for your chatbot can be tricky. User intents vary as well as entities. Therefore, identifying the right user intent can be difficult to achieve. How can you make the interaction between bot and user simple and direct?. Below you have some useful tips to optimize your chatbot:

Improve the Accuracy of Predictions

One way you can refine the chatbot performance is by improving how the chatbot predicts the user intent. To fix unsure predictions, you can check the endpoint utterances by verifying the predicted intent. You can also label the entities predicted incorrectly. In addition, you can also implement batch testing to ensure your bot is predicting and understanding the intent correctly. 

Review endpoint utterances

You can check and fix utterances your model receives via the Natural Language Unit. Utterances can be incorrect on the intent or the entity. Your NLU can detect which utterances it is unsure of and compile a list for review. You should review the list periodically.  Below you can find an example of how it works on Microsoft Azure. 

Implement batch testing

Testing should be a part of your chatbot improvement process. You can use batch testing to find where are the utterance prediction issues in your bot. Train your model with a determined set of utterances and entities.Testing in batches allows you then to validate your model. Some pointers to consider:

  • Limit the number of utterances per test
  • Don’t allow duplicates
  • Allow only machine-learned entities 

These points will save you time and improve the results.  

Use Pattern Templates Utterances

Look for common utterances and entities and use that to make a pattern template. Check where intents and entities merge to find the pattern. To do this, you can select the intent and select which utterances will go with it. 

Next, you can use a template utterance example, to give your natural language processing unit more context about where intents and entities fit. You can use these template utterances to improve your model with multiple entities.

 Understand Casual Language with NLP

People use abbreviations and slang when they text. The difference between the way we talk and we text can make your bot work difficult. However, it is important that it understands the query. The chatbot also should be able to carry on small talk with visitors to engage them. 

To improve your chatbot conversational ability, use Natural Language Processing (NLP). This will allow your bot to understand users’ queries and carry a conversation more natural. Checking the analytics regularly can help you detect new words in the queries and train your model. 

Use Sentiment Analysis to Add Empathy to the Conversation

Showing empathy can go a long way with frustrated customers and in customer service situations. To include empathy to your bot’s conversational skill set, you can use sentiment analysis.  It is a process that interprets user emotions through AI text analysis technology.  This means your bot can identify and respond to the user’s feelings, making the conversation more fluid and natural to users. 

Recognize Frequent Users

Companies, such as stores or restaurants, have returning customers.Users can get annoyed if they have to give the bot the same information all the time. To avoid this, it is important that the bot remembers details about frequent customers. It can be their name or the usual order.  

You can achieve this by training the bot to pull the existing data on the user. Then it can verify it with the user to check if it is correct. The bot can also remind the user about the last order or query. 

Avoid Multiple Personalities

It is true, your bot needs a personality. That means all the communications, including the error messages and information requests, need to be consistent with the chatbot personality. Imagine you’re having a conversation of a friendly bot, and then it swifts to a dry, robotic dialogue. It can be annoying, to say the least. 

The chatbot should have a voice and tone coherent with your brand’s and the target audience. A good tip to make the conversation more fluid is to make the bot offer different responses when asked the same query. Also, it can recognize when the user asks the same question repeatedly. 

Be Careful with Off-the-shelf Chatbot Software

Some companies opt for using boxed chatbot software to save time and money. This also brings issues when the chatbot cannot identify the user intent, resulting in frustration and client’s disappointment. 

Most off-the-shelf chatbot software is based on a decision-tree that works on specific keywords. For example, it responds with a product list to any “buy” keyword, or the price list to any question with the “price” word. This can cause confusion because the algorithm cannot take into account all potential queries. 

Custom chatbot development, like we do at SCSS Consulting, is more effective at recognizing user intent. Since we develop the bot tailored according to the audience and user requirements, the chances of confusion are lower. 

Wrap Up

Chatbots are transforming the way companies interact with users. However, they still have issues with misunderstandings and malfunctions. Companies risk ending up with frustrated customers if the chat bot service doesn’t provide quick and efficient answers. 

That’s why we should continuously improve the bot, adding new words and queries, refining the dialogue and the voice of the bot. To summarize:

  • This will keep the bot updated with customer requests
  • Can help you fix failures quickly. 
  • Help you identify trends and add it to your chatbot offers. 

You can improve your bot manually or use automation. However, the improvement process can be uphill with shelf solutions, since they are more difficult to modify. 

Using a custom chatbot solution can help prevent many of the issues of adapting and updating the bot. At SCSS Consulting, we take care of including continuous updating processes in all our custom developed chatbots. Contact us today to learn how we can help. 

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