Chatbot vs ChatGPT: Differences, features, and use cases

Over half of American adults have now used a chatbot powered by AI to get speedy, accurate answers to their questions. Your business can benefit from this growing trend. 

Adding a conversational chatbot to your site can increase lead generation, improve the customer experience, and generate new sales revenue. But do you need a chatbot or ChatGPT? The answer isn’t always clear, and they differ significantly in design, reasoning ability, and scalability.

That’s why we’ve published this guide. It’s a straightforward comparison of chatbots vs ChatGPT to help you find the right fit for growing your brand. Keep reading to discover key differences, when to use each tool, and factors to consider while making your decision.

Chatbot vs ChatGPT: Side-by-side comparison table

You’re not alone if you don’t know the differences between traditional chatbots and ChatGPT. Both answer users’ questions with AI. But there are important distinctions to determine which is the best fit for your business. Here are the key takeaways:

	Traditional Chatbots	ChatGPT
Use case	Structured, repetitive responses, like answering your customers’ FAQs	Open-ended conversations that are more like talking to a human than answering a direct question
Underlying technology	Rule-based logic with narrow AI	Large language models, like GPT-3.5 and GPT-4
Customization and training	Requires manual scripting and updates	Learns from large datasets, can adapt with minimal training
Creativity in responses	Low, only offers fixed-response paths	High, generates varied, human-like responses
Scalability	Custom	Custom
Cost	Lower up front and ongoing	Higher up front and ongoing
Response predictability	High, the same question will always be answered the same way	Variable, the same question can be answered differently

So, traditional chatbots offer predictable answers to common questions at a relatively affordable price. They’re also easy to scale, as long as your scaling process doesn’t include diversifying output. ChatGPT and generative AI chatbots are more dynamic, mirroring the way humans would answer your customers’ questions. They cost more than traditional chatbots but improve without your input and can scale in any direction your business growth takes you. 

What is a chatbot? Overview of types and capabilities

A chatbot is an app that simulates human conversation through predefined logic. It follows scripted flows and decision trees to help customers, answer questions, and generate leads. A chatbot’s effectiveness depends on how well it’s programmed. If you can accurately predict the vast majority of user questions, a chatbot may be all you need. But when questions get more complex and personalized, chatbots can become more frustrating than helpful.

Traditional chatbots typically follow this process to answer users’ questions:

1. Input detection: The user types into a field or selects an option from a menu.
2. Intent recognition: The bot matches the input to a known intent. (You’ll need to program this unless you choose a generative model.)
3. Response selection: A predefined response or action gets triggered based on the intent.
4. Output delivery: The bot replies or performs the action.

Your company’s responsibilities within this workflow will vary based on the model you choose. There are three main types of chatbots:

• Rule-based: These follow strict if-then logic, guiding users through predefined conversation paths. They’re good for FAQs, capturing basic lead information, and processing basic requests.
• AI-powered: AI chatbots use machine learning to identify user intent and then draft personalized responses. They can analyze keywords, previous interactions, and sentiment to determine the best answer. But they aren’t generative, meaning they still depend heavily on manual training.
• Generative: Generative chatbots, like ChatGPT, are the most advanced option available. They provide personalized answers in real time, allowing for more natural, helpful conversations.

What is ChatGPT? The generative AI behind the name

ChatGPT is a generative chatbot. It uses large language models to create human-like responses in real time. The app can understand and respond to infinite prompts because it has context awareness and offers smooth conversation flow.

ChatGPT is based on the transformer model, which achieves language processing by understanding the relationships between words, phrases, and context. The typical return process includes

• Pre-training: ChatGPT is trained on massive datasets to learn language patterns.
• Tokenization: A user inputs a query, and ChatGPT breaks it down into smaller, tokenized units before analyzing and crafting a response.
• Context modeling: The platform keeps track of conversation history to use personal information when generating replies.

OpenAI, the developer of ChatGPT, regularly releases new upgraded models. For example, GPT-3.5 and GPT-4 enable the platform to carry out more complex tasks, including summarizing documents, writing code, and interpreting tone. 

Upgrades like these help ChatGPT handle more nuanced queries. You can leverage those benefits to provide additional value to people who visit your site. This is an important factor to consider when comparing an AI chatbot to ChatGPT. The latter may cost more, but the value it creates helps companies generate a positive ROI.

How chatbots and ChatGPT work: Architecture comparison

The major differences between chatbots and ChatGPT stem from their architecture. The way each tool is built impacts the kind of performance your business can expect from it. Understanding these distinctions can help you make a more informed decision about what’s best for your team.

Traditional chatbots work by following a linear logic path. Their architecture features

1. Intent detection: A chatbot uses keyword recognition or basic language understanding to identify what the user wants.
2. Entity extraction: The tool pulls specific values, like dates, names, and numbers, from the user’s request.
3. Decision tree mapping: The model follows a pre-defined flowpath, based on the intent detected.
4. Response selection: The platform pushes out a scripted message or action.

ChatGPT does things a little differently. Its workflow looks like this:

1. Tokenization: ChatGPT breaks a user’s input into tokens, e.g., individual words or phrases.
2. Context embedding: The model reads the full input and looks for context clues before crafting a message.
3. Pre-trained knowledge activation: The platform predicts the next likely word based on its training to form responses.
4. Generative output: The model returns a personalized answer to the user’s question.

As a business owner, you don’t need to know the specific details of how each model works. The key thing you care about is the output that customers get relative to the costs you pay to generate it. So you’ll also need to perform a cost-benefit analysis while comparing ChatGPT to AI chatbots.

Reasoning abilities: A breakdown from o0 to o5+

One way to figure out the kind of chatbot you need is to consider how much reasoning power your goals require. There’s a standardized scale, ranging from o0 to 05+, which shows how much performance you can expect from different models.

Basic chatbots tend to fit within the o0 to o2 reasoning levels:

• o0 offers basic matching and responses based on exact keyword triggers.
• o1 adds pattern recognition, but still relies on known inputs.
• o2 follows simple decision trees to handle more complex flows with predefined logic.

ChatGPT takes things a step further. It’s available at levels ranging from o3 to o5+:

• o3 offers contextual understanding by maintaining and analyzing conversation histories.
• o4 introduces analytical reasoning to summarize more complex information.
• o5+ uses multistep logic and synthesis, performing analysis in multiple stages and achieving hypothetical reasoning.

For many companies, choosing a model comes down to paying as little as possible for the reasoning power they need. Even if you prefer ChatGPT, it isn’t always the best use of a company’s limited resources.

When to use a traditional chatbot

Traditional chatbots are a strong choice when your use case involves predictable, repeatable tasks. They work well when you have highly defined user flows that you rarely deviate from. For example, companies use traditional chatbots for

• Answering customer FAQs
• Qualifying leads with structured questions (e.g., “What’s your budget?”)
• Scheduling appointments 
• Assisting customers with filling out forms

A traditional chatbot could also be right for your business if you’re looking for a budget-friendly option with a simple setup process. They’re common in industries like retail (for order information), healthcare (for appointments), education (for course FAQs), and nonprofits (for basic outreach).

Some companies also use traditional chatbots as a funnel for live chat support. For example, you might greet customers who have questions with a chatbot so you can route them to the right support person. 

This can help you keep your support team relatively small while reducing wait times and improving the overall customer experience. It’s worth considering if you’ve been debating chatbots vs live chat for your business.

When to use ChatGPT or generative AI chatbots

ChatGPT and other generative AI bots are best for complex, dynamic conversations where users expect human-like understanding. Some of the best fits for this include

• Technical support: Assisting customers with detailed questions and troubleshooting in real time
• Internal knowledge assistance: Helping staff access and synthesize policy documents, manuals, and more
• Content generation: Writing social posts, blogs, and customer emails
• Global customer service: Handling diverse phrasing and tones across languages

The key benefit of ChatGPT is its ability to engage with customers nearly as well as a human service rep would. However, it has higher infrastructure requirements, and pricing often scales with usage. This essentially means you have to pay more to unlock these benefits, and that may or may not be worth doing, depending on your goals. 

For example, if offering global customer service expands your total addressable market, ChatGPT could pay for itself. But if you only get a few complex customer service questions per day, it may not deliver the value you need to justify the expense.

How to choose the right chatbot technology for your business

At this point, you’re ready to choose between a traditional chatbot and conversational AI, like ChatGPT. The better option will depend on your business goals, available resources, and the complexity of your users’ interactions. A good place to start is your budget. Does ChatGPT fit it? If not, your decision may already be made. But if it does fit your budget, you can move on to other considerations, like what your main goal is in adding a chatbot to your site.

If you want to replace human support agents to keep your overhead low, ChatGPT would be a much better way to do that than a traditional chatbot. But if you just want to capture more information from website visitors, a traditional chatbot may be all you need.

Other factors could impact your decision too, such as

• Maintenance requirements: Traditional chatbots require manual updates, which you may not want to make.
• Control over language: Chatbots let you script everything, while ChatGPT delivers dynamic responses. That’s not always a positive if you want tight control over the responses generated.
• Setup time: Traditional chatbots are easy to deploy, while ChatGPT requires more configuration and testing.

Ultimately, both options can help you deliver more value to customers through your website. It may even be worth experimenting with both to see which your users prefer. Some companies decide to use a hybrid approach, letting a traditional chatbot greet users before escalating to ChatGPT for more advanced questions. This can help to keep your support team small by minimizing unnecessary work and customer support request overload.

ChatGPT vs chatbot: What’s the right fit for your business?

Both types of chatbots can be effective. Your decision will come down to what you hope to achieve. If it’s speed, structure, and control, a traditional chatbot could be a better option. But if it’s delivering highly personalized, flexible responses that sound like they come from people, ChatGPT could be worth the investment. If you’re still unsure which to choose, consider starting with a pilot test. Try both options to see what works best for you, and then refine over time as you learn more about your needs. 

Let’s wrap up with a few actionable steps you can take to move your process forward:

• Map your most common user interactions: If they’re repetitive, a traditional bot could work; if they’re open-ended, ChatGPT will be a must.
• Explore chatbot tools: Check out no-code chatbot builders and other chatbot marketing tools to get more value out of whatever option you choose.
• Reassess regularly: Users’ expectations evolve over time, and your conversational strategy should too.

You can also take a look at Jotform for support with forms, templates, integrations, and more. Our platform can help you unlock the full potential of whichever chatbot you choose.