Jun 24, 2022

Building Chatbot Best Practices and Considerations

By [24]7.ai

In recent years, chatbots have surged in popularity, with more and more companies using them to automate and improve their customer experience. There are a number of chatbot solutions on the market, and if you’re ready to deploy, the upfront savings offered by a do-it-yourself (DIY) chatbot solution might be tempting—but a DIY chatbot will almost certainly cost your organization more in the long run.

That’s not to say they don’t have a place and a purpose – they most certainly do. It’s to say that not all chatbots are created equal, and for enterprises, chatbots need to be smart to be effective. If you make a chatbot on your own, it will not be able to offer the level of assistance enterprise level customers expect, and can actually damage your brand’s reputation by complicating your customer service experience. For smaller business needs, a DYI chatbot could very well do the trick.

Let’s dive deeper into chatbot building and what considerations to keep in mind to build a bot that makes the most sense for your unique needs. Ultimately, the end goal is the same – benefit your customers and benefit your business.

Choosing the Right Intelligent Virtual Assistant for Your Contact Center

The advancing capabilities of Intelligent Virtual Assistants (IVAs, a.k.a. virtual agents, chatbots) are driving dramatic improvements in customer experience and helping contact centers contain costs while improving agent productivity.

What is an intelligent virtual assistant?

An intelligent virtual assistant is an artificial intelligence-powered chatbot that can carry out tasks for a user. IVAs can be used for a variety of purposes, such as customer service, marketing, or product support.

What is the difference between a virtual agent and a virtual assistant?

There is a big difference between virtual agents and virtual assistants. Virtual agents are computer programs that customers can interact with through natural language, such as chatbots. Virtual assistants, on the other hand, are actual people, who provide customer service support through digital channels such as chat, email, and social media.

Virtual agents are used to automate customer interactions, whereas virtual assistants are used to provide human support.

Benefits of an Intelligent Virtual Assistant

As customers grow more accustomed to interacting with bots on a regular basis, their expectations for these interactions are changing. Whether engaging via phone, a digital channel, or a combination of both. Seems simple enough – the only problem is, not all IVAs can deliver.

Early generation IVAs simply can’t compete with today’s intelligent systems. Legacy systems are unable to retain context, and can only handle one single intent at a time, making the conversation disjointed and unnatural for customers – a far cry from the experiences they expect. And forcing customers to deal with this kind of system can cost you – 33% of customers say they’re likely to switch companies after just one bad customer service experience.

Conversely, today’s intelligent virtual assistants offer natural, human-like experiences that make it simple for customers to get the answers or assistance they need.

Top Considerations for Chatbot Development and Chatbot Personality Design

Every chatbot has a personality whether or not you consciously install one, so it’s wise to plan for it. Now the question becomes: How do you design a chatbot personality that meets customer expectations in an engaging experience? 

Designing the perfect conversational chatbot interface can be a bit like the tale of Goldilocks. A comfortable yet engaging experience requires just the right amount of personality, humanity, and emotiveness. 

Design Chatbots with Audience and Use in Mind

It’s crucial you consider the conversational chatbot’s system application or use case when developing chatbot personality. A healthcare system AI chatbot, for example, will have a different tone from a financial services one, or one designed purely for entertainment.

Likewise, it’s important to align the chatbot persona with the brand. A customer accustomed to a fun and light brand will be disappointed by a dry, boring personality bot on your company website.

Locale matters too. When dealing with multiple markets, you have to consider how chatbot interactions are perceived in each region. Markets have their own characteristics, so you can't blanket design across them.

Start with Chatbot Persona

We strongly advise you work off a frame of reference throughout the development process. That means, identifying who the bot is meant to emulate, and what kind of responses that person would give. Do they use emojis? Gifs? Do they like to use a lot of exclamation marks? Having this level of detail will help form the basis of who your chatbot will become.

Sorry (or) Not Sorry

How much should the persona of the chatbot emulate human behavior and empathy? It’s essential to find the right blend so you create rapport without seeming creepy.

For example, should a chatbot apologize? The short answer is no. Start with sympathy then get to empathy and then compassion. The concern is that saying “Sorry” stops the conversation at the level of sympathy when it should move beyond that. Also, it isn’t believable. Of course, it might not be believable coming from a person either.

That said, there is a difference between the discourse marker—Sorry—and the emotional declaration, ‘I’m sorry,’ It’s useful to use the discourse marker as a way to show participants in the conversation, ‘Hey, we’re not making the progress you were hoping to make… and I’m going to pivot to something else.’”

Pivoting from “Sorry” is valuable for correcting an initial misrecognition or to better match to the user’s request.

The High Cost of Cheap Chat

Chatbots have become incredibly popular in recent years, and for good reason. They provide instant access to information and help customers quickly and easily self-serve and complete their journeys. This convenience and accessibility has helped make them the channel of choice for many customers, especially millennials.

To capitalize on the chatbot trend and give customers what they want, a number of companies have been quick to deploy cheap chatbot solutions as a customer service tool, believing that offering customers something is better than nothing. But, as is often the case, if something seems too good to be true, it probably is.

When it comes to chatbots, you get what you pay for, and if you pay next to nothing, that's likely what you'll get.

How Much Cheap Chatbot Solutions Will Cost you as a Customer Service Tool 

Using free or cheap chat solutions might seem like it’s better than nothing, but the truth is, it will likely end up costing your company a bundle in the long run. It will also likely trigger losses you'll incur from frustrated, unhappy customers.

Though vendors will often promise you the world, cheap chatbots aren't capable of providing the experiences consumers have come to expect. They're unable to understand intent, they can’t identify when to engage a customer, and they can’t seamlessly transition customers to call agents. All too often, cheap chatbots are nothing more than a futile attempt to address the increasing demand for self-service customer support options, and not a functional customer service tool.

Customers who are engaging with these cheap chat solutions will not receive the assistance they need and will likely be unable to complete their journeys. This is frustrating and often leads to total journey abandonment or to customers escalating their queries to a human agent where they'll have to start from scratch. These are not the experiences you want to provide your customers.

Similarly, your agents will have to spend more time authenticating customers and determining their intent things they would already know if they were working with intelligent chatbots. Increased time spent with agents increases costs to your business, which is the exact opposite outcome chatbots should provide.

The Right Chat Solution 

Chat is a strategic investment that must be implemented thoughtfully and carefully. Getting it right might mean a greater cost to your organization up front, but the investment will save you money in the long run and ensure you're providing optimal experiences with every interaction.

The right chatbot solutions replicate all the best qualities of your top human agents they allow your customers to self-serve and find the answers they're after quickly and easily - just like they would if they were interacting with a live agent.

Intelligent chat can also empower your call center agents to perform more efficiently, help eliminate up to 40% of post-order inquiries from other channels, and enable more customers to solve problems and find answers on their own, in the shortest amount of time. These are the chatbot experiences consumers expect these are the experiences that will improve customer satisfaction and boost NPS.

Design Automated Live Chats with Conversational AI Chatbots

Armed with the latest natural language processing (NLP) technologies, companies are deploying conversational AI chatbots in an ever-widening range of use cases—from answering FAQs to recommending products and services to handling conversational commerce. And why not? Properly designed conversational AI chatbots improve customer satisfaction (by quickly identifying customer intent and efficiently resolving issues) and improve enterprise profitability (by reducing costs and strengthening customer loyalty). 

But what is “proper” chatbot design? To create memorable customer experiences—which lead to memorable business outcomes as well—conversational AI chatbot designers need to consider several factors:

Visualize the Automated Live Chat Conversation Flow

Human-to-chatbot conversations, much like human-to-human conversations, are extremely variable and often complex. To capture this in your chatbot design, first visualize the possible chatbot conversational paths as a flow chart; see below.

Conversational AI Chatbot Design: Chunk the Information

To identify customer intent and resolve customer issues, customers and chatbots must exchange a lot of information, which, in turn, must be “chunked” to reduce confusion and streamline resolution. Furthermore, that information needs to be chunked both when the chatbot requests/collects information from customers and also when it delivers information to customers. 

Let’s consider a Tracking use case to explore chunking in more detail. 

  • A chatbot that needs to collect Name, Tracking Number, Type, and Email should ask for one quantity at a time: Name first, then the Tracking Number, and so on.
  • Alternatively, a chatbot could use a form, also known as a card, to ask for all quantities at once. Cards are an inherently chunking medium
  • Similarly, chatbots use chunking when conveying information to customers—either delivering one quantity at a time, or including multiple quantities in a single card. Cards work best for conveying large amounts of information; see below. 

Chatbot Pattern Matching

AI chatbot autoresponder uses a database in which each document has a particular pattern and template. When the chatbot receives input that matches a document's pattern, it sends the data stored in the template as a response. A standard structure for these patterns is "AIML" (artificial intelligence markup language).

Conversational AI Chatbot Design: Personalization

Personalization, which we broadly categorize into two types, often improves the customer experience by quickly determining customer intent. 

  • Context-based personalization: Personalization based on information created by customers during their website or application interactions. For example, when a customer views “how to track your package” information, the chatbot sends a personalized Tracking message enabling the customer to more quickly resolve their issue.
  • Historical personalization: Personalization based on information created over time by customers during their website or application interactions. For example, when a customer provides their account number (say, when looking up their account balance), a chatbot in a later conversation retrieves that account number to provide the account balance. 

Conversational AI Chatbot Autoresponder Design: Optimization

Customers’ requests change as time goes by, and chatbot autoresponders need to keep up with the dynamicity of these changes. You may best recognize and understand these changes by looking at performance reports measuring various KPIs. When a KPI falls short of your business expectations, the chatbot needs to be enhanced.

Tips for a Better Chatbot Customer Experience

More and more organizations are deploying chatbots in an effort to automate and improve their customer service channels, but all too often, these deployments do not return expected results. This happens for a number of reasons.

Frequently companies had not completely clarified their vision on where and how to deploy their chatbot, or their criteria for choosing a bot matching their needs. The chatbot may be lacking the ability to understand natural language or handle the types of customer questions the company receives.

Sometimes the problem lies in the interaction itself: the experience might feel inconsistent from previous brand interactions, causing customers to lose trust in the chatbot, or interactions could feel too robotic, which is frustrating, and often leads to customers picking up the phone to call an agent, completely defeating the purpose of the chatbot deployment.

To be a success, your chatbot must rival the level of service your best agents provide. It’s essential to choose the right level of technology for your needs, and train your chatbot so that customers are able to interact naturally, and receive natural, insightful responses in return.

If you’re ready to deploy a bot to improve your customer service, follow these tips to ensure you deliver an experience that’s virtually indistinguishable from your best human agents.

1. Talk in the First Person

Your chatbot should communicate the same way people communicate. Phrases like “How can I help you?” and “Is there anything else I can help you with today?” are first-person phrases that go a long way to make the interaction feel human and engaging.

2. Use a Conversational Tone for a Better Chatbot Experience

Wherever possible, use a conversational tone. In situations where your chatbot needs to provide legal or policy information, preface it with conversational human sounding language, like, “Here’s what I found for you. Click this link for the details of your policy.”

3. Stay Aligned with Your Brand to Ensure that Chatbots are Effective

Chatbot interactions have the potential to deliver quick resolutions to a customer’s immediate concerns, which make them great for building stronger relationships with your customers. Be sure to use language that is consistent with your brand. You don’t want the chatbot experience to ‘stand out’ as something that doesn’t quite match the feel of the rest of your digital experience.

4. Use a Conversational Tone for a Better Chatbot Experience

Make sure your chatbot experience mimics your agent best practices. For example, chat agents offer answers and information one piece at a time, rather than dump a long block of text into a conversation all at once. Your chatbot should do the same.

5. Make Handoffs Feel Personal

There will always be occasions where your chatbot has to hand the conversation over to a live agent. Ensure that the context of the conversation is preserved. Your agents should have full insight into what was already discussed so that customers don’t have to start over or repeat themselves. A ‘blind’ handoff will undo all of the goodwill you built up during the chatbot interaction, and leave the customer feeling as though the whole interaction was impersonal, mechanical, and a waste of time.

No, all chatbots are not created equal and no, any chatbot is not better than having no chatbot at all. With a bit of work, some due diligence, and with targeted focus on your audience and your business needs, everyone – the business, the agents and the customers – will benefit from a well-built and well managed chatbot, and that bot will make all the difference.

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