Conversational AI Platforms: An Essential Guide for Businesses
Conversational AI is like a knowledgeable librarian ready to help you find the resources you need from stacks of information.
Instead of manually searching for answers, you can use a chat conversation to point customers to personalized recommendations. It uses natural language processing and machine learning to answer inquiries and learn exactly what the user is looking for.
As a result, businesses can expect improved customer satisfaction, increased efficiency and reduced operational costs.
With the ability to handle multiple customer inquiries simultaneously, conversational AI also frees up human support and sales agents so they can focus on more complex issues and interesting leads.
In this article, we'll explore the benefits of conversational AI in customer support and how businesses can leverage this technology to enhance their customer service.
- What is conversational AI?
- What is a key differentiator of conversational AI?
- Popular use cases of conversational AI
- Conversational AI examples
- 7 steps to program and deploy conversational AI
- How much does conversational AI cost?
- Get started with an intuitive conversational AI platform
What is conversational AI?
Conversational AI (Artificial Intelligence) is technology, such as chatbots and virtual assistants, that relies on natural language processing and machine learning algorithms to simulate human-like conversation.
It’s predominantly used to create advanced chatbots and virtual assistants for websites, messaging channels and social media.
What is a key differentiator of conversational AI?
Chatbots have been around for some time, but they haven’t always used AI technology. Even today you find many chatbot providers using simple if-then programming, strongly limiting the conversation flow to defined keywords and button menus.
The key differentiator of conversational AI is its ability to lead a conversation in a natural and intuitive way.
Conversational AI is designed to understand user intent, interpret natural language inputs, and provide meaningful responses that mimic human conversation. It can also recognize context, remember previous interactions and personalize its responses.
This is what sets conversational AI apart from standard, decision tree chatbots and makes it well-suited for customer service and sales.
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Popular use cases of conversational AI
Many industries benefit from offering conversational AI on their website and in popular messaging apps. Sometimes “talking” is better than clicking through a stiff button-based menu — customers can receive personalized support without having to get your agents involved.
Here are some popular use cases for businesses:
- Customer support: Conversational AI can take over common inquiries, reduce response times and provide personalized instant support that feels natural.
- Sales and marketing: A conversational AI chatbot can help drive your sales and marketing efforts by collecting interesting leads, making product recommendations, collecting contact info and upselling or cross selling products and services.
- Lead generation: Conversational AI can help qualify leads by asking important questions in the chat to identify if they’re high quality. It can then save these contacts in your CRM, provide personalized recommendations and build trust and credibility by always being instantly available.
- Assistance: For common tasks, conversational AI chatbots are a great help. It can check order and process statuses, submit refunds, schedule appointments, offer advice and forward the chat to a human agent when the issue is too complex.
- Recruitment: Conversational AI can be used to streamline the recruitment process. Chatbots can conduct initial interviews and screenings, schedule interviews, and answer candidate questions, freeing up recruiters' time to focus on more strategic tasks.
Overall, conversational AI has the potential to improve customer engagement, increase your operational efficiency and drive business growth.
Conversational AI examples
Here are three examples of intelligent chatbots assisting customers using different conversational AI platforms.
Norbot is a Userlike chatbot used by German energy company Stadtwerke Düren. It uses both keyword recognition and button options to respond to users about common or pressing energy topics.
Norbot also cleverly shares a contact form mid-chat, so customers can receive further help from an agent — and Stadtwerke Düren can collect data on new leads.
Live chat software with built-in AI is a powerful combination for coordinated support between your automation and agents.
Cora is a banking chatbot created with IBM’s conversational AI platform. Cora has thousands of answers to more than 200 common customer intents and speaks to over 40k customers a day.
It can fully assist 27% of conversations and the rest are forwarded when the customer needs more specialized help.
When Cora doesn’t understand a request after a couple tries, it lets the user choose to ask another question, check their FAQ or speak to an agent.
The chatbot platform Roof AI specializes in real estate automation. The chatbot helps qualify real estate, mortgage and agent recruiting prospects, answer inquiries, schedule tours and create customer profiles.
A notable example is Sunny, a chatbot created for The Keyes Company. It uses natural language processing and button options in the conversation to help narrow down what customers are looking for.
Conversations with Roof AI’s chatbot are very human-like — it “types” and sends responses at a realistic pace. It also uses short, precise questions to learn what the user is looking for and, in the case of Sunny, has a calm, helpful persona and feel to it.
Chatbot Olivia was created with the conversational AI platform Paradox AI. “She” is an HR assistant bot that takes over repetitive questions and follow-up messages. It uses conversational AI so applicants can freely type to the bot and receive warm, human-sounding replies instantly.
This advanced bot can also screen candidates through conversation, schedule interviews, answer questions from candidates and send reminders. It’s a great approach to reducing long, frustrating hiring processes for both hiring managers and candidates.
7 steps to program and deploy conversational AI
- Define the purpose of the conversational AI
- Choose a platform
- Write a conversation flow
- Build your conversational AI
- Test and refine
- Deploy your conversational AI
- Monitor and make improvements
Determine your specific use cases for using conversational AI, such as customer service, answering FAQs or assisting with purchases. Without a purpose or clear goals, your chatbot or any other automation features will become redundant and cost your business unnecessary time and money.
To create a conversational AI application for your unique use cases, you need a conversational AI platform, such as Userlike’s AI Automation Hub, IBM Watson or Ada. Here you can create a knowledge base and conversation flows for an AI chatbot or other smart automation features to use when supporting customers.
A general rule of thumb is to choose an all-in-one provider that has a combination of live chat, messaging and automation, like Userlike. Then all of your agents and bots are managed in one place. This will make it easier to monitor and adapt your chatbot, and is a cost-effective solution.
For a full comparison list of both AI and rule-based chatbots, read our post, “11 must-try chatbot providers for every budget.”
Create a conversation flow diagram or spreadsheet that shows possible customer requests and questions and bot responses. For inspiration, use your live chat transcripts, emails and other customer correspondence to make sure you include common questions and concerns.
You can then either upload or manually input these flows into your provider’s chatbot builder and/or knowledge base.
For help writing chatbot scripts, read our post, “6 steps for creating a smooth chatbot conversation flow.”
Using the platform you chose to build your conversational AI chatbot, transfer your flows into the bot builder. With the AI Automation Hub, you can upload your spreadsheet to fill in the text fields for your AI chatbot.
Depending on your approach, this step will take time to finalize. The beauty of the AI Automation Hub, however, is that it’s a self-learning system. As your conversational AI chatbot talks to customers, it learns from these interactions and improves its answers over time.
Test the conversational AI thoroughly to identify and fix any issues. Ask your team to chat with the bot or try these chatbot testing strategies.
You could even consider a soft release on a specific page of your website, such as your pricing page. There you can test and monitor its effectiveness, and learn how users interact with it before making it available across your website and channels.
Once your conversational AI has been thoroughly tested, deploy it on the pages and channels that make most sense for its purpose. For example, if you build a conversational AI customer support chatbot, it makes sense to have it on your website’s contact page and in important popular messaging channels like WhatsApp.
If your goal is to get more leads and sales, then it’s better to use your bot sitewide. Then it can proactively approach customers and keep them from abandoning your website, or worse, their cart.
Continuously monitor your conversational AI to identify areas for improvement and refine its capabilities. Collect user feedback and analyze its performance metrics to see where you can make changes.
One idea is to use a star rating system and feedback form at the end of the chat. This lets users give a quick opinion of the service they received without any effort.
With Userlike, you can trigger this feedback form after a set time of inactivity. Make sure to regularly review this feedback to fix acute issues or to see how your chatbot is performing.
How much does conversational AI cost?
Using conversational AI automation features as part of your support is cheaper (and smarter) than pushing repetitive work on agents, but how much does it cost, and what do you get?
We compared the top customer support conversational AI platforms. We researched their chatbot type, automation features, integrations and price to give you an overview of what these popular GDPR-compliant providers offer.
|Integrated live chat||✅||🆇||🆇||🆇||🆇|
|Smart FAQ page||✅||🆇||🆇||🆇||🆇|
|Contact form suggestions||✅||🆇||🆇||🆇||🆇|
|Compatible messaging apps||WhatsApp, Instagram, Facebook Messenger, Telegram, Threema, SMS||Facebook Messenger||Amazon Alexa Skills, Google Assistant Actions||Facebook Messenger||Facebook Messenger, WhatsApp, SMS|
|Price||€490 a month for 10 users||€790 for one account and chatbot||Must inquire for pricing||Must inquire for pricing||Free up to 10k messages & limited skills|
For a list of more providers, including rule-based solutions for comparison, check out our post, “11 must-try chatbot providers for every budget.”
Get started with an intuitive conversational AI platform
Perhaps you’re still wondering if conversational AI is worth it at your business. There are plenty of benefits, but of course it’s a huge step to take if you don’t currently offer a chatbot or automation on your website.
That’s why at Userlike we wanted to make the switch to AI automation a logical step forward for your customer support and lead generation. Everything is included in our software and controlled in the central Message Center: live chat, messaging and many automation features.
You can provide instant, personalized 24/7 support without overloading your agents or hiring new ones. Our AI chatbot uses conversational AI to make sure customers consistently receive high quality service on their channel of choice.