Chat robots are here to stay, and will improve in the near future. Here’s how to use them to get better ROI.
The age of immediate engagement and artificial intelligence has made it possible for people to hold a decent conversation with non-living things. I am talking about the chatbots—a derivative of “chat robots” which are nothing but a computer programme that sits in a boring server and simulates how a human being would communicate, using auditory or textual methods. With over 300,000 of them on Facebook Messenger alone, in the past year, you’ve probably spoken to at least one. I bet there will even be a day when a chatbot might talk to another chatbot to get things done. At the Google I/O event, the search behemoth showcased how a Google Assistant could converse with a human to place reservations at a restaurant in your name. One day, chatbots might be so ubiquitous that a Google Assistant would converse with said restaurant’s chatbot.
Now the question is, do you have a bot in place? If yes, is it ready for this kind of scenario? Or do you really need one for such a scenario? Big companies are cashing in, with Apple’s Siri and Amazon Alexa reaching celebrity status with their myriad of abilities and natural speech that is sometimes even sassy. With the help of their user base, these big companies improve their chatbots as they have access to what is needed to make things work, i.e. data.
Businesses looking into getting one or have one in place know that chatbot can help them get that additional data that they need for better analysis on various aspects of their prospects or existing customers.
But the question remains: how do companies yield an ROI from chatbots?
While chatbots might not be something we “need” right now or might not even be “perfect”, they are ultimately an investment for the future, there are small wins here and there: by incorporating it in customer service, for example, companies can trim business costs, speed up problem solving, and shorten the pathway towards conversion.
The solution lies in how to use the technology in your overall business strategy—including in crafting the content and integrating it in the customer journey and experience. To start, you will need to figure out what chatbot your company needs, or essentially, how much is worth investing right now.
Types of chatbots
The behaviour of this type of chatbot depends on a predefined set of questions. For every step, the user is given a set of options—presented to the user with a text, voice, or touch response. Each choice determines the next step in the conversation. Following this programmed questionnaire, conversations with this type of chatbot can only follow a certain predetermined path.
Short for Natural Language Processing, NLP is a computer science subfield that is concerned with how computers can process and analyse natural language data. A chatbot utilising NLP or NLU i.e. Natural Language Understanding thus is capable of interpreting and classifying messages using intent and then deriving meaning. It is sophisticated enough to break down sentences into its data components called entities.
Service or Action chatbots:
Chatbots under this category ask for relevant data from the user (such as flight details) in order to take or complete an action (such as flight updates). These chatbots are built on top of basic NLP-based chatbots, and they utilise data captured in the form of entities to take action. They might not be built with a thought of conversational bot and hence these chatbots need not sound sophisticated, but are fancy enough that they are capable of understanding what the user is saying, run an API according to that action in backend and get the job done with displaying the final result. They just need to make the customer inquiry process faster and more efficient.
These chatbots are the most advanced kind of conversational bots, with Siri and Alexa falling into this category. Utilising Machine Learning and Artificial Intelligence, the bots learn to understand different keywords, questions or commands in the manner that an actual person would phrase them. They learn from repeated experiences and improve as they mature.
These combine bots and humans: frequent and simple requests are attended to faster by bots, while complex requests that bots are unable to attend to are redirected to humans. This type of chatbot combines the best of both worlds, reducing the customer service cost and increasing customer satisfaction at the same time.
After figuring out the chatbot that is most appropriate for your needs, consider these:
What kind of output are you looking for? There’s a plethora of chatbot platforms and corresponding merits. Do you need your chatbot to be embedded on your site? Do you need it to be integrated with another enterprise software platform? And more importantly, are you technically capable to use the selected platform with ease?
You will need to decide if the chatbot code will be the basis for use in other platforms, and if you will use an API (application programming interface) which will allow it to communicate with another app, like Facebook. Are there any webhooks or API’s that you can integrate with your system at a later stage and will that be supported with current type of chatbot you are working with?
Do you want your chatbot to become smarter and smarter, or do you just need it to perform basic tasks? True, it is more attractive to have your own witty, sassy Siri, but do you really need it?
What happens to the data you’ve managed to gather? Do you want to pass the data on to a customer relationship management (CRM) software directly? Moreover, does your data gathering comply with data regulations such as the GDPR?
The entire process to finish a project from end-to-end can be challenging, but feel free to contact us for expert advice. Allow us to cop a line from our favourite robots:
“What can we do for you?”