You’ve determined that you need a chatbot on your website or on your other user-facing business services. But now, you must still decide which type of chatbot best suits your requirements.
Do you need an AI-powered chatbot capable of natural sounding conversation? Or are you better off with a simpler, FAQ-focused bot trained to answer your top inbound queries?
This leads us to the titular question: do you need an NLP chatbot? NLP – natural language processing – bots are now rising in availability, popularity, and functionality. Many organisations are turning towards them as the cutting-edge bot choice of the times.
But what is an NLP chatbot, how are they different, and do you need one?
What is NLP?
NLP is short for natural language processing. It’s a subsection of artificial intelligence (AI) that deals with how humans and machines communicate. Its focus is teaching machines to communicate using – as the name suggests – ‘natural language’.
The term natural language means language the way we humans use it every day. So, it refers to the way we talk and communicate with other humans in our daily interactions. Think casual chit-chat, idioms, slang; all the informalities and grammatical rule-bending that occur with an informal conversation.
This natural language is contrasted to, say, a restrictive keyword method of communicating with a machine. Or, the formal language we use when writing essays or giving an important speech.
What is an NLP chatbot?
NLP chatbots answer to this focus on a more natural mode of human-machine interaction. An NLP chatbot, then, is a chatbot program equipped with natural language processing functionality.
This means it’s able to interpret messages that are written the way users would write normally. The bot can detect the intent of the message, and respond to typos, synonyms, and colloquialisms, just like a person can.
Pros and cons of the NLP chatbot
So, do you need a sophisticated NLP chatbot? They come with both benefits and drawbacks.
Pros
- • Natural conversations rather than robotic ones
An NLP chatbot doesn’t require the user to input specific phrases or words for it to ‘understand’ and work. This then makes for a smoother flow to the conversation, and allows for more diversity in the way the user can interact with the bot.
- • Flexibility — fewer restrictions than other bots
Simpler, FAQ-based chatbots can only follow pre-set conversational pathways. This is not the case with NLP chatbots.
Chatbots with natural language processing capabilities can adapt to users changing their minds, support more conversational variations, and keep track of the context of long conversations.
- • They’re considered the future of chatbots
With the continued proliferation of AI, it’s thought that NLP is the future for chatbots. As technology advances, flow or rule-based chatbot technology may begin to feel clunky. In turn, NLP could become a staple for every business that needs a chatbot.
Cons
- • Resource cost
NLP chatbots use complex technology that’s costly and takes time to ‘train’. Compared to their counterparts, they cost more.
- • Can be overkill
As cool as the NLP chatbot is, it isn’t always necessary for businesses. Where a chatbot that follows rules would do the job, an NLP chatbot could be considered overkill. If the chatbot is simply to collect customer information before a chat or call, for instance, there’s no need for an NLP chatbot.
- • Can fall into the trap of overreliance
Even with the heightened abilities of the NLP chatbot compared to its counterparts, it can be easy to fall into overreliance. That is, to use the bot for more than it’s best suited to.
This translates to customers getting frustrated when they can’t reach a human, or the chatbot isn’t yet able to help them. Whether you choose an NLP chatbot or not, they’re still not a replacement for all human support. You’ll still need humans to take on complex conversations, to monitor the bot, and to provide the human touch in your service.
The non-NLP chatbot
When deciding whether you need an NLP chatbot, knowing the alternative option(s) can be very helpful.
These chatbots are not able to ‘understand’ human language in the same way that an NLP chatbot can. Instead of being able to detect user intent, these bots work by looking for pre-defined key terms and phrases. Sometimes, they use buttons with the answers for users to choose from.
The non-NLP chatbot comes with its own pros and cons in comparison to the NLP chatbot. For example, with a rule-based bot, it’s often instantly clear what the chatbot can do and talk about. This isn’t always the case with the more natural conversation enabled by NLP. But, in the same way, this means that chatbots without NLP are much less flexible and can produce boring, robotic interactions.
When you need an NLP chatbot
So, when asking whether you need an NLP chatbot, the answer depends on the role you want your chatbot to fill.
Most organisations use bots to handle simple administrative tasks, such as:
- Collecting user data (names, contact details, order numbers etc.)
- Answering routine FAQ
- Directing users to relevant resources
- Fielding inbound queries to the relevant department
For these types of tasks, an NLP chatbot is simply unnecessary. You don’t need (or indeed want) a conversational bot for such use cases.
You do need to invest in an NLP chatbot if you are looking for a bot that generates entertaining conversations, rather than just functional ones. Or, if you are looking to apply the bot to slightly more nuanced conversations and find that the need for intent detection is necessary. However, in such instances, a human agent will always be more effective than a bot.
To NLP, or not to NLP
TL;DR: An NLP chatbot can do all the things the flow-based bots can, but using them for this kind of administrative service means you aren’t using the full potential of the chatbot.
Deciding if you need an NLP chatbot, then, boils down to outlining exactly what it is you want your chatbot to achieve. For most businesses, they’re nice to have, but probably overkill for your needs.
Useful links
What is an intent-based chatbot?
Chatbots vs conversational AI: what’s the difference?
The customer service battle: digitalisation vs the human touch