Conversational AI is transforming how companies interact with customers. According to Accenture, around 80% of CEOs want to update their customers’ interaction by using conversational AI tools.1 However, there are 2 different conversational AI solutions for the companies:
- Intelligent virtual assistant
- Chatbots
Their distinctive features make one tool better than another for unique use cases. Therefore, for specific investment decisions, it becomes critical to which technology you pick. In this 2500+ word article, we comprehensively compare chatbots with intelligent virtual assistants across 6 use case scenarios to inform executives and technical leaders.
Defining Chatbots and Intelligent Virtual Assistants
Before comparing chatbots and IVAs, let‘s define these conversational AI technologies and understand their capabilities:
What is a Chatbot?
A chatbot is an automation tool for client interaction that has limited natural language processing (NLP) and artificial intelligence skills.
Despite the name “chatbot” being used as a catch-all term for conversational AI, chatbots are typically rule-based systems. They work by matching user input to predefined rules and providing the appropriate response.
For example, a chatbot may be programmed to detect keywords like "store locations" and respond with your store‘s address. The rules are defined during development by the company implementing the chatbot.
This rule-based approach makes chatbots ideal for automating repetitive tasks like responding to frequently asked questions. Developing a chatbot can also be faster and cheaper compared to more advanced conversational AI technologies because it does not require in-depth NLU capabilities.
According to Oracle, chatbots can deliver ROI of up to 300% by reducing customer service costs.2 And by 2022, Gartner predicts that 70% of customer interactions will involve chatbots, cutting costs by $0.70 per interaction.3
What is an Intelligent Virtual Assistant?
An intelligent virtual assistant (IVA) utilizes more advanced AI and conversational capabilities. The two main components that allow IVAs to handle complex interactions are:
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Natural language understanding (NLU) – This allows the IVA to correctly interpret the intent and context behind user messages, even if they contain slang, typos, or ambiguous language.
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Artificial emotional intelligence (AeI) – IVAs can detect emotion like frustration or urgency and respond appropriately to improve customer satisfaction.
With these capabilities, IVAs can understand and respond naturally to users as if having a conversation with a human. They can be programmed to perform a wide range of tasks from answering simple questions to making recommendations and even providing psychotherapy or medical assistance.
According to Salesforce, 61% of customers prefer chatbots for quick inquiries, while 56% want human agents for more complex needs.4 This demonstrates how IVAs are ideal for automating complex interactions that require true conversational ability.
Comparing Chatbots vs IVAs
When should you choose a chatbot or an IVA? Here are some key differences:
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Development time: Chatbots can be built within days or weeks using simple rules. IVAs require extensive AI training so can take months to develop.
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Implementation cost: Chatbot costs range from $15 to $100 per month. IVAs incur hosting fees of $100 to $500 monthly.5 Upfront build costs are also higher for IVAs given the AI development required.
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Conversational complexity: Chatbots handle simple preset interactions. IVAs excel at complex natural conversations.
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Use cases: Chatbots work for FAQs, surveys, notifications. IVAs are preferred for recommendations, customer service, therapy.
Considering these differences, chatbots present a faster and more affordable option when conversational complexity is low. But IVAs unlock more possibilities for advanced automation.
A hybrid approach combining both technologies is also commonly used. Chatbots handle simple repetitive questions while an IVA provides backup for complex interactions.
Deploying Chatbots and IVAs Across Channels
A key benefit of both chatbots and IVAs is the ability to deploy them across multiple channels, including:
- Messaging platforms like WhatsApp, Facebook Messenger
- Mobile apps
- Websites
- SMS
- Smart speakers
This omnichannel approach allows businesses to engage customers in the channels they already use.
For example, 1-800-Flowers increased conversions by 50% using a chatbot on Facebook Messenger.6 And Sephora saw an 11% increase in sales after launching a chatbot on their mobile app.7
Offering conversational AI across channels provides a seamless experience and boosts engagement. But the right platform must be chosen based on use case and audience.
WhatsApp in particular stands out as a top channel for chatbots and IVAs. WhatsApp has over 2 billion users and offers fast deployment with the WhatsApp Business API.
According to Gupshup, 66% of consumers prefer WhatsApp for customer service. And their research shows a conversational commerce order value 2.9x higher on WhatsApp compared to other channels.8
With omnichannel deployment key for success, companies must consider which platforms their audiences prefer and plan their conversational AI strategy accordingly.
Comparing Chatbots and IVAs Across Use Cases
When deciding between chatbots and IVAs, it is also crucial to evaluate them across your specific use cases. The best technology depends on the complexity of the tasks you aim to automate.
We will analyze chatbots vs IVAs across some common conversational AI use cases:
Sales Use Cases
Conversational AI can assist sales in multiple ways:
Answering FAQs
Both chatbots and IVAs can be effective for resolving frequently asked customer questions. The main goal is providing quick answers to common inquiries like store hours, product details, returns policies, etc.
For instance, 1-800-Flowers saw a 13X ROI after implementing an AI-powered chatbot to handle FAQs on Facebook Messenger. It provided instant responses 24/7 while reducing call volume.9
And Cars24, an online used car marketplace, automated 60% of customer queries using an IVA from Haptik. It answered questions on pricing, documentation, and more.10
But since FAQ resolution is a relatively simple use case, chatbots present a faster and more affordable option here. You can build a chatbot to handle FAQs for a fraction of the cost and time of developing a production-ready IVA.
According to Inbenta, chatbots reduce human workloads for FAQs and simple inquiries by up to 70%.11 So unless you intend to expand to more complex use cases, a chatbot is recommended for FAQ automation.
Answering Complex Questions
Customers often need help choosing between products or services based on their specific needs. This requires understanding the intent behind open-ended queries and providing tailored recommendations.
For example, a customer may know they need a laptop but be unsure which model is right for them. The conversational AI would need to ask about usage, price range, and features to recommend options.
Successfully automating these complex interactions requires the advanced NLU and conversation skills of an IVA. Chatbots cannot interpret open-ended questions and personalize responses.
An IVA helped Tata CliQ, an ecommerce marketplace in India, drive 11X ROI by providing intelligent purchase assistance. It answered ambiguous queries and recommended products based on customers‘ needs.12
Complex purchase advising and recommendation use cases need the AI sophistication of virtual assistants over limited chatbots.
Healthcare Use Cases
Conversational AI is also transforming healthcare by automating patient interactions for:
Providing Medical Information
Both chatbots and IVAs can be used to share general health information with patients. This includes:
- Common symptoms and conditions
- Preventative health tips
- Available clinic services and specialties
For example, a leading hospital in Thailand added an IVA on Facebook Messenger to answer patient questions 24/7. It provided information on treatments, specialties, insurance, and appointments. The IVA handled 87% of inquiries without human intervention, saving over 4,800 work hours per year.13
However, a chatbot is likely sufficient if medical details will be simple. The faster implementation can allow quicker rollout to meet patient demand. But for more advanced health information, an IVA would be required.
Digital Health Assistance
More capable IVAs are being leveraged as virtual health assistants to assess symptoms, triage patients, and offer health advice.
Startups like Infermedica and Babylon Health are pioneering these AI-powered chatbots that act as virtual nurses and doctors. Infermedica‘s IVA asks patients diagnostic questions and suggests possible conditions. It achieved 95% accuracy in early testing.14
Automating healthcare tasks like digital triage and symptom checking requires the robust conversational skills of intelligent virtual assistants. Chatbots lack the depth of understanding needed.
Hospitality Use Cases
For restaurants and hotels, conversational AI can enhance customer engagement through:
Menu Introduction
Both chatbots and IVAs can interact with customers to introduce menu offerings. The bot can describe dishes, ingredients, prices, and make recommendations.
For example, Landbot.io developed a restaurant chatbot that provides a digital menu and helps users order food for delivery or pickup.15 Customers can browse menu items via conversation instead of a static menu.
This use case is relatively straightforward so developing an affordable chatbot to introduce and discuss menus is recommended. An IVA would enable more complex recommendations but provides overkill for basic menu interactions.
Recommending Dishes or Beverages
More advanced recommendations based on customer preferences require an IVA‘s conversational abilities. The virtual assistant can have a natural dialogue to learn the occasion, tastes, budget and suggest suitable menu options.
For instance, TravelBird‘s IVA helps travelers discover restaurant recommendations for their trip based on their needs and interests shared through conversation.16 Without robust NLU, a chatbot could not interpret unique preferences and tailor dish suggestions.
The human-like dialogue needed for contextual recommendations makes IVAs the ideal solution for this use case over limited chatbots.
Key Takeaways
When determining if a chatbot or IVA is the right solution, consider:
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Cost and speed: Chatbots are cheaper and faster to develop. Prefer them for basic uses.
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Conversational complexity: IVAs are better for complex dialogue and understanding.
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Use case needs: Align the technology with your specific automation goal.
Although capabilities are improving, IVAs still come at a premium. For affordable automation of simple repetitive tasks, chatbots offer strong ROI. But for advanced interactions, IVAs are worth the investment.
Evaluating use cases and priorities will determine the best technology for your needs. For most impactful results, a hybrid model is ideal – combining chatbots for simple queries and IVAs for sophisticated conversations.
Conversational AI offers immense opportunities to improve customer engagement and reduce service costs. Applying the right technology for your needs is key to maximizing results. Please reach out if you need any assistance navigating chatbots, IVAs, and use cases for your business. I would be happy to offer guidance based on my decade of experience.
1 “The future of customer conversation: More than words, more than AI”. Accenture. (2021).
2 “Cut Costs and Improve Efficiency with Chatbots”. Oracle.
3 “4 Trends Impacting Customer Service in 2024”. Gartner. (2021).
4 “2018 State of Service”. Salesforce. (2018).
5 “How much does it cost to build a chatbot in 2024?”. Hubspot.
6 “1-800-FLOWERS.COM, Inc. Floraland Gifts Chatbot Case Study”. Drift.
7 “Sephora shoppers can now get makeup tips and product recommendations from an AI bot”. CNBC. (2019).
8 “Everything About WhatsApp Chatbots”. Gupshup. (2022).
9 “1-800-FLOWERS.COM, Inc. Floraland Gifts Chatbot Case Study”. Drift.
10 “Cars24 Automates 60% Support Queries With WhatsApp IVR And AI-Based Chatbot”. Entrackr. (2022).
11 “Conversational AI Assistants Are Helping Businesses Improve Customer Experience”. Inbenta. (2021).
12 “Tata Cliq Shopping Bot – Ecommerce Personal Shopping Assistant”. Haptik.
13 “Automated Virtual Assistant Curbs Calls, Captures Patients”. NTT DATA. (2019).
14 “Infermedica uses NLP & AI to save lives”. NLU Summit. (2020).
15 “Restaurant Chatbot: Conversational Menu for In-House Orders & Deliveries”. Landbot.io. (2020).
16 “Travelbird virtual travel agent”. Creative Virtual.