Back in the day, businesses were reluctant to rely on software to talk to potential customers. Why invest in software or chatbots when you can talk to people yourself right? Chatbots only respond to the type of questions they are programmed to respond to. Right?
It used to be so. But not anymore. Investing in a chatbot isn’t considered strange anymore. As a matter of fact, chatbots today are very different from what they used to be thanks to Artificial Intelligence. They are now smarter i.e. they don’t need to be programmed to respond to the kind of questions a visitor would ask. With AI and Machine Learning, modern chatbots can make conversations just like a human would.
But developing an ‘intelligent’ chatbot can be a major challenge as even the smallest mistake can do serious damage to a business. That said, this blog will provide an introduction to a few major mistakes bot-builders make in various phases of development. Furthermore, we have also included a few useful tips about chatbot development.
Phase 1 – Conception
It’s not the coding phase where chatbot development officially begins. We like to believe that true development starts at the Conception phase where the team defines the problem they want to solve with the bot while meeting business requirements.
Once the business need is defined properly, the team can brainstorm on how the bot’s conversation flow solves that particular issue. More than 4 exchanges in a conversation is not recommended by experts in chatbot development. Additionally, all chatbots are expected to understand and respond to various topics that aren’t related to their objective. Users most likely would test that out simply out of curiosity.
So disregarding the target audience, user experience, response to small talk and other commonly asked casual questions can be a mistake bot developers may regret.
Phase 2 – Training
Modern chatbots leverage powerful technologies like AI, machine learning and natural language processing. With machine learning and natural language processing, bots can be trained to handle almost every kind of query visitors would have, resulting in great performance and customer satisfaction. Training a bot requires the team to create intents and fill them with expressions. Each intent can have a number of expressions. And this number is important. Five expressions for intent won’t be enough. For the chatbot to efficiently serve its purpose, there should be over 50 expressions.
During this phase, companies often make the mistake of training the bot with just the development and testing team. This approach ends with a bot that trained on inaccurately represented target users as the development team most likely won’t be able to formulate questions that potential customers may ask.
Phase 3 – Coding & Development
Building the chatbot is possibly the most challenging of all phases mentioned in this blog; often assumed to be just a configuration of conversational flows. It isn’t. One of the biggest mistakes made during development is when the team uses one skill for one task. One skill doesn’t necessarily have to be used for one task or process. Experts recommend utilizing an ‘alpha skill’ or ‘mega skill’ that can redirect to different skills that manage specific procedures.
Phase 4 – User Experience
User experience is the single most important feature any digital solution should possess. Modern day users appreciate convenience. As long as they don’t have to spend a lot of time using a software to serve a purpose, they will be happy. A bad experience with a digital solution – be it a web app, mobile app or even a chatbot, could end up with a significant reduction in business revenue which is why almost every business with digital personas invest in an engaging, memorable user experience.
To provide a great UX, a chatbot should look attractive with strategic use of graphic elements, buttons, HD pictures, and a good virtual personality. The bot should then be integrated to where the business’ potential customers are. Choosing the right channel is also an important factor. Many companies make the mistake of attracting customers to a channel where they’ve integrated their chatbot instead.
Another surprisingly common mistake is when conversations with the bot are much more than simple exchanges i.e. the bot responds to a query with a long, descriptive reply which could be inconvenient to customers. If the reply is supposed to elaborate, the bot should separate it into different messages. To make the conversation lively, the bot can also be trained to use UX components, images, buttons etc. so that the users won’t have to reply to a lot of questions before they get the solution they seek from the bot.
Another important factor is the chatbot’s personality. A customer talking to a bot won’t expect a lot of interaction where they can ask about anything and everything. They would expect something robotic. But modern chatbots are overcoming past limitations to resemble humans when it comes to making conversations. To make the engagement memorable, the chatbot can be given a name and a personality (funny, playful or completely polite and humble).
Phase 5 – Maintenance
For the bot to keep succeeding, regular maintenance is key. And maintenance include improvements in training, tweaking the bot based on the feedback from users and creating new use cases. This is where one serious mistake may occur if the developers unbalance the already effective training while adding more user sentences (new expressions for intents). Ignoring user feedback is another common mistake. It’s important to pay attention to even the tiniest detail when leveraging an intelligent chatbot for customer support.
For a ‘smart bot’ to be smart, it has to be trained. With Machine Learning involved, this training should utilize the right data sets so that the bot won’t reach inaccurate conclusions post-training. When used the right way, chatbots can be a powerful asset that can encourage customers, who simply wanted some clarifications, to make a purchase. It can even make recommendations just like a human salesperson would.
Investing in a chatbot is gradually becoming a future-proofing strategy for enterprises. If you like to give a ‘smart bot’ a shot at handling your customers, start learning about the feasibility and benefits. Talk to AOT’s AI experts today.