There are hundreds of tools for developing chatbots, ranging from general-purpose platforms to specific market niches. Enterprises may also use chatbot tools for functions including marketing channels, human resources, or improving internal workflows.
Whether building your chatbot or outsourcing development, these five chatbot features can aid in successfully implementing bots. Even when a tool on your shortlist supports a given feature, it’s worth considering how easy it is for developers to work with it in practice. While some chatbot platforms can support all the features on this list, some require workarounds and kludging to adapt to your specific needs.
Context management
Users generally approach a bot with a specific query in mind, usually relating to a new purchase, problem or request. Chatbots use different techniques to understand where a user comes from and what they want.
Ajay Pondicherry, co-founder of Block Party, a real estate marketing software platform, recommends developers provide contextual messaging based on what page a user is on, who referred them or the kinds of problems they may have encountered.
“This usually starts with customizing messages based on the user’s attributes, but then there are truly infinite possibilities,” he said. That could include following up with a personalized email that engages the user further.
He likes the Drift conversational sales and marketing platform because messages can appear in live chat and email. Business messaging platform Intercom takes it a step further by allowing push notifications, too. Other tools, like marketing bot system MobileMonkey, can chat across various social media platforms. However, it is worth investigating how contextualized responses work on different platforms since some platforms make it challenging to integrate context into custom data fields.
“The more a system can constrain the context, the better that chatbot can understand the conversation,” said Fang Cheng, CEO and co-founder of Linc, a customer experience automation platform.
For example, when a customer states, “I would like to return the leggings I got in April,” the digital worker should automatically ask the customer for their order number and when they would like to make their return.
Brand customization
Brand customization capabilities allow you to change the text and style of the chatbot to match your brand. Joren Wouters, founder of Chatimize, a blog that helps entrepreneurs use chatbots in their marketing, said basic brand customization is standard. However, these customized features aren’t always supported in website widgets. For example, with sales and marketing conversational platform ManyChat, you can only put a widget on your website in the style of Facebook Messenger. This is still the case for many leading chatbot tools, including low-code, no-code bot builder Chatfuel.
Wouters recommends looking for chatbot tools that provide what he calls a “native website widget” that you can customize to the branding of your website.
It’s also essential to consider the ability to customize the bot to your brand ethos, said Gillian McCann, head of cloud engineering and AI at Workgrid Software. Questions decision-makers should consider when evaluating brand customization features include:
What would your company or department sound like if it could chat?
Does it have a different persona for customers versus employees?
Do you envisage a formal or informal personality based on the domain or end-user persona?
“Answers to these should form the basis of your conversational strategy and help define how much customization you really need for those build versus buy decisions,” McCann said. No matter which bot style you choose, use a style guide so that your chatbot adheres to a conversational style that represents your brand and company.
Omnichannel capability
“Omnichannel capability is one of the most important features of a chatbot,” said Wouters. Enterprises can provide additional value by connecting to users on popular channels such as WhatsApp, Facebook, Instagram and Telegram. He recommends doing research to identify which conversation platforms your customers use and prioritizing tools that support those channels.
Chatbot
By using these top features, enterprises can build better chatbots.
Social media and conversation platforms also have specific rules for customizing chatbots. For example, Facebook and WhatsApp have strict rules regarding what kind of promotional messages you can send, while on Telegram, you do not have these kinds of rules. Also, you can send galleries and buttons on Facebook, while you can only send text messages on WhatsApp.
“A chatbot must be able to handle those differences between channels,” said Wouters.
Wouters found that most chatbot vendors work in a limited range of channels. For example, ManyChat, one of the most popular chatbots, only works with Facebook Messenger, SMS and email. Other chatbot builders, such as Xenioo, can handle more, but might be less easy to use.
Enterprises should also consider the back-end integrations built into chatbot tools. Jared Peterson, director of advanced analytics at SAS, said it is essential to consider how easily a chatbot platform integrates into an organization’s software, external systems and resources. Enabling these features can require considerable variation in technical expertise.
AI-enabled bots
In the chatbot industry, “AI-enabled” refers to the ability to infuse natural language understanding (NLU) into chatbot applications, which can help bots understand users’ questions. Wouters observed that some of the most popular chatbot builders, including ManyChat, Chatfuel and MobileMonkey, don’t provide this option in their software. Even if a tool does not support NLU natively, it is often possible to integrate chatbot apps into Google Dialogflow, a platform specifically designed to embed NLU capabilities in chatbots.
Wanda Roland, vice president and alliance leader, digital customer experience at Capgemini, said it is also worth exploring AI support for sentiment analysis capabilities that can understand how to best respond to customer queries. A bot with sentiment analysis could also automatically escalate issues to human employees if a situation warrants it.
Live chat
“A chatbot will always fail because customers will ask questions the chatbot has not been trained on yet,” Wouters said. When that happens, you need a human to ensure a good user experience via live chat.
This can work in different ways. Sometimes, it’s possible to direct chats to certain departments or specific people. Other times, you are limited to sending it to a generic group without providing any context, so the user has to repeat their question.
Source: searchenterpriseai.techtarget.com
