Identifying and prioritising your chatbot use cases is a critical part of your chatbot strategy. It involves a lot of research and careful thinking.
What do you want your chatbot to accomplish?
What type of customer does your chatbot care for?
And more important: What problem does your chatbot solve? In this post, I’m going to walk you through the most common use cases, how to identify and prioritise your own. Let’s get started.
What Can Chatbots Be Used For?
According to research, chatbots are only getting more popular every day. New applications surge all the time. There are several reasons for that.
First, chatbots become more popular as industries discover the benefits of chatbot technology for customer experience.
Fifty-six percent say conversational bots are driving disruption in their industry, and 43 percent report their competitors are already implementing the technology (Accenture report in Conversational Bots)
According to the Accenture report, conversational bots deliver large ROI with minimal effort required from the company.
Another consideration is the situation of chatbots in the #hypecycle curve. In our previous post, we analysed the chatbot position in the Gartner’s Hype Cycle Curve. The report showed that chatbot technology is beyond the peak, meaning chatbots are here to stay.
So, you want to get in the chatbot benefits, but where do you start?
How do you know what to use your chat for?
You can start by looking at use cases inside your company. Below are some examples:
Chatbot Use Cases for Business
Chatbots for Customer Service
According to research, this is the top use case for chatbots. When you use a chatbot for customer support, you have the following uses:
- Instant answer to customer queries
- Taking care of repetitive questions
- Guiding visitors on their customer journey
- Taking care of payments
- Engage customers in fun conversations
- Gather customer feedback
Sales and Marketing
Chatbots can be invaluable to push sales. Let’s see some ways chatbots can work for your sales and marketing team.
- Give personalized recommendations according to the user’s behaviour on the site.
- Help with lead generation by subscribing visitors to events, newsletters or webinars.
- Promote contests and share campaigns.
- Engage visitors in conversations and boost sales.
- Book demo appointments.
- Onboard customers and handle bookings.
The applications of chatbots in human resources are still young, but companies are increasingly adopting this technology. Let’s see why:
- Assist employees with finding documentation or navigating the internal company site.
- Take care of employee onboarding.
- Assisting with time log, time-off requests. Also helping employees retrieve documentation or answering common questions.
Chatbot Use Cases by Industry
When looking to identify your chatbot use cases, you can look at how companies like yours implement chatbot technology. Let’s see the most popular uses by industry:
Chatbot Use Cases for Banking
Banks have embraced chatbot technology as part of their digital transformation efforts. Studies show that chatbots can save costs to the banking and healthcare industry of over $8 billion/year by 2022.
A bank chatbot can:
- Answer repetitive or common questions
- Help solve problems such as retrieving a password or looking at the account balance.
- Process payments
- Generate leads engaging visitors to the bank site in conversation
- Capture fraud tickets and elevate to security staff.
Source: Mastercard’s KAI chatbot.
Chatbots have been critical to retail shops during the 2020 COVID-19 pandemic, allowing them to stay open. Chatbots enabled customers to reach businesses, placing orders and track deliveries. Some common use cases for retail:
- Lead generation
- Manage orders and deliveries
- Offer instant purchases.
- Answer FAQs.
Chatbots Use Cases for Healthcare
Chatbots are highly popular in healthcare. They save time in triage and have proved essential during the COVID-19 pandemic and beyond. Here some uses for chatbots in healthcare:
- Gather patient information for triage
- Book consultations and tests
- Sharing safety and healthcare tips
- Send physician recommendations
Government institutions use chatbots to provide citizens with a better experience when dealing with government services. Conversational AI saves time and effort since it doesn’t require people to wait in line or on the phone. Here are some common use cases:
- Provide quick access to information. An example could be Transport Bot, which the team at Pure Speech Technology lead at the NSW government.
- Help citizens with government processes, filling forms, registering for services, and so on.
- Handle complaints and answer questions.
A Quick Guide to Identifying and Prioritizing Chatbot Use Cases
You’ve got ideas from your own company processes and your industry. Now it is time to get handy and plan your chatbot roadmap.
Step #1: Identify your Chatbot Use Case
To identify what your chatbot should do, start by asking the following questions:
Who are the customers?
First, you need to know what the pain points of your customers are. What process is causing them trouble? Defining precisely your target audience helps you get the maximum interaction from your customers. Know their activities, ages and location. A bot geared for youngsters under 25 is not the same as one geared to senior citizens.
What’s the purpose of your chatbot?
Define what problem you need your chatbot to solve. It is probable that you will have more than one problem to solve. Therefore, choose the most critical for your company. More on how to prioritise your use cases in the sections below.
Keep digital transformation in mind
Implementing a chatbot can transform the way your business interacts with customers. When considering your bot use cases, don’t think of the bot as a way to emulate your current workflows. Instead, think of the bot as a tool to automate repetitive tasks, reduce effort, and improve productivity.
Step #2: Choose your Chatbot Type
Bots are not all equal. In fact, we can divide them into two big groups: decision-tree chatbots and conversational AI chatbots. The first provides answers according to a previously set decision tree with either ‘quick reply’ buttons or short snippets of text. The latter uses Natural Language Processing to understand the user’s request and provide the answer.
The chatbot you choose for your case will depend on the problem you need to solve. This will help determine the features you need. For instance, chatbots that only fulfil one or two functions can get away with a tree-log model. If you need your chatbot to handle complex operations or queries, an AI-powered bot will be more successful.
Take into account which channels do your customers use with chatbots. Do they use chatbots in Facebook Messenger, WhatsApp? Maybe they use Smart Speakers, like Google Home/ Alexa? Go where your customers are. Analyse the customers’ preferred platforms and use this information to select the right channel to launch your chatbot.
Step #3: Prioritise the Use Cases
Each use case is unique and will answer to a unique need of your company and your industry. What can be a priority for your industry?. For instance, engaging conversation for retail and e-commerce is not so a priority for others, (like healthcare).
Think about what is the biggest pain point for your customers or users and choose a chatbot to solve that. Then follow with other use cases. The insurance industry does this wonderfully, deploying different chatbots at different stages of the customer journey. Keep in mind also to prioritise the cases that bring more value to the business.
To ensure you don’t miss a thing, follow a prioritisation framework. The top three are MoSCow, RICE and Kano.
It is commonly used in Agile Product Management. The method focuses on four prioritization categories that help understand what features are important and whatnot.
- Must have – the vital requirements without which you cannot launch.
- Should have – things that are recommended to include but the product can do without.
- Could have – features that would be nice to have but don’t make a real impact in customer experience
- Won’t have – requirements that cannot be included in this version.
It is represented by a graph showing the intersection of three vectors:
- Delighters – what features customers will consider above expectations
- Performance – usually customers respond well to an increase in performance features.
- Basic – the minimum that your customers expect from the product to solve their problems.
The Rice prioritization method has also four categories to evaluate priority:
- Reach – how many customers will this feature impact?
- Impact – how will this feature affect people as individuals?
- Confidence – estimate a confidence percentage to the feature.
- Effort – how much monthly effort will take?
At Pure Speech Technology, we tweak the RICE model with Intelligent Automation, adding AI-driven data for a more comprehensive analysis. We add the scoring of factors:
- ROI/Benefits – forecasting the future ROI of the project.
- Process length – how many steps the process requires.
- Consistency – if the process is consistent or has a high level of variance.
- Infrastructure availability – how the process fits relative to other IT projects or needed infrastructure.
Final Thoughts: Choose the Right Technology Partner
All these steps may seem overwhelming. That’s why choosing the right company to develop your chatbot solution is critical for success. Choose a company that can guide and assist you in developing your chatbot strategy from scratch. The right technology partner not only takes care of the technical aspects but also of the strategy and the analytics to bring the most ROI for your chatbot investment.
Conversational AI represents not only a customer support solution, but one of the keys of digital transformation, permeating several departments of your company. As a result, implementing a chatbot that addresses the right use cases to deliver ROI is not easy. Contact us at Pure Speech Technology to learn more about how we can guide you to a successful chatbot strategy.