“Hi, how can I help you?”
Chatbots have taken websites by storm. Conversational AI technologies have transformed customer service point-of-contact interactions in sectors like eCommerce, airlines, banking & financial services, insurance, manufacturing, telecommunications, and many others. They can be lightning quick to deploy, saving considerable time for both the client and the company.
In a world driven by the culture of immediacy and self-service, the provision of fast, high-quality responses to every request from customers and interested parties, all while reducing direct service contact, has become critical. To do so, chatbots are your best friend – but, not all chatbots are built the same. Here are some factors to consider when selecting your chatbot.
Different types of chatbot to drive your conversations
Many types of chatbots are available to meet different business needs and with so much choice available it can be challenging to make up your mind with confidence. First, ask yourself a few questions:
- What is your goal? Do you want to provide short replies to simple questions or engage in deep conversations?
- Do you want to give full freedom of inquiry to the customer, or do you want to limit the action options presented?
- Where do you want to have the chatbot? (Website? Social Media? Everywhere?)
- How much time do you have and what is your budget?
Having your replies to these questions in mind, you can start considering different types of chatbot and their relative complexity. However, even if your needs seem the height of simplicity, chatbots that are very basic may end up being an additional source of frustration for your customers. Fully-featured enterprise chatbots offer various functionalities to meet users’ expectations, and may be a better choice even in a comparatively simple application.
- Menu/Button-based Chatbots
The most basic type of chatbot, this variety limits possibilities by offering the user a specific number of buttons. They can answer pre-defined questions and can facilitate the buying journey, for example by guiding user navigation of a website, but they are not able to solve complex requests.
- Keyword Recognition-based Chatbots
This type uses a basic analysis engine that recognizes some keywords, thus adding more interaction than menu/button-based chatbots. Users can interact by entering free text and receive a pre-loaded response based on the keywords identified and understood by the chatbot. This kind of system is good for exercising close control of your brand’s automated messaging. Inherent limitations include the potential misunderstanding of misspelled words, potentially generating user dissatisfaction.
- AI Chatbots – Service Quality on Another Level
Also called “contextual chatbots” or “conversational AI chatbots”, enterprise chatbots use advanced technology such as Machine Learning, Artificial Intelligence and/or Natural Language Processing to interact with users, and thereby are by far the most flexible and interactive solution.
Not only do they understand whatever the user requests, from simple to complex, but they also remember conversations with previous users and improve their responses based on the context, can anticipate follow up questions, or even generate and send suggestions for customer’s next need on the basis of previous cases.
Enterprise chatbots can be specifically and finely tailored to requirements. Here are some features you will want to consider as you work through your chatbot project.
Must-have criteria for a great chatbot conversation
The shorter the path to information, the better. To do so, you need to implement a chatbot which can be accessible from multiple channels such as your website, Facebook, WhatsApp, and wherever else users or customers interact with you. Manage all these discussions through a single platform.
- Third-Party Integrations
Chatbots can serve different aspects of a business. Whether you want to help customer department, support the HR department or boost sales, you need a chatbot able to integrate with related third-party software: CRM software, Human Resource Information Systems (HRIS), or billing systems etc. By doing so, you open the gates for information to circulate easily from each third party to the bot to the person asking the question.
- Escalation to Live Chat
Most customer interactions can be handled without a human agent, but technology cannot yet replace live agents in all cases. When complex cases arise, or when someone just wants to talk to a human, chatbots need to be able to transfer the conversation – including history and any other useful information – to a real agent.
- User Friendly
It is axiomatic that good design improves user experience. Chatbots do not offer many options in terms of flexibility in design but simply put, having an accessible and user-friendly platform will make the chatbot more pleasing to use. For instance, you want to have a chatbot that is going to display nicely on all types of devices, or that makes content easier to digest by avoiding long text blocs, or at most basic merely has a comfortable color scheme.
- Analytics and Continuous Learning
A bot should also be able to learn from previous conversations and feedback to enhance customer experience. You want to know which are the popular interactions, discover the busiest moments, track the number of messages or users in a given frame of time. To do so, an archive of all past chats, errors, and failures should be recorded and downloadable to monitor and provide insights on the customer experience.
- First-Party Technology
Is it a first or a third-party technology? In the first-party case, the software editor completely manages, and owns the technology. Not only this ensures more responsiveness from the chatbot software vendor, but also it contributes to lowering costs of the overall project.
A multilingual chatbot can lead a conversation in multiple languages during a live chat. The chat user selects the language in which they are most comfortable, and the bot adapts to the request. Having the multilingual option gives you broader horizons for business (better customer experience a greater geographic span, increased database etc.). The Inbenta Chatbot module has symbolic AI-fueled Natural Language Processing (NLP) technology at its core and can understand the nuances in 30+ languages.
Symbolic AI & NLP remain the key ingredients for success
To avoid the “it does not understand my request” feeling from the user, you need to invest in an NLP-based chatbot, using deep learning techniques to detect user intent. Thus, effectively imitated human interactions give the end-user the feeling that they are well understood and are having a real conversation rather than just being guided through a limited list of options, links, or FAQ chapters.
Unlike keyword-based chatbots, enterprise chatbots associating Conversational AI technology and NLP understand the meaning behind words, or adapt to misspellings or slang, and thus provide a more smoothly organic user experience than any other type of chatbot.
The Inbenta enterprise chatbot goes one step further by detecting the meaning of words without the lengthy data training that is usually required by brute-force machine learning algorithms. With Inbenta’s chatbot module, you get the best solution in the market and remove the question of timing – Inbenta can be deployed within a matter of days.
Reduce your customer issue resolution times. Discover how the Inbenta AI Chatbot automatically engages in complex conversations, with minimal training.
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