ChatGPT/Business/AI • 8 min read

ChatGPT and GPT-4 for Business: How to Customize and Use in 2024?

How to customize and use ChatGPT for real business results? Discover GPT-4 for business: capabilities, use cases, and best practices from BotsCrew.

Alina Danilova
Alina Danilova
Apr. 5, 2023. Updated Jan. 25, 2024
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In recent months, ChatGPT has taken the world by storm with its unparalleled language generation capabilities. And now, with the imminent release of GPT-4, the potential applications for this technology are greater than ever before.

In this post, we’ll take a look into ChatGPT & GPT-4 models for a business.  

Intro: What’s GPT & what is it good at?

GPT (Generative Pre-trained Transformer) is a family of language models that use deep learning techniques to generate human-like language. The models are pre-trained on large amounts of text data such as web pages, books, and articles. This pre-training allows the models to learn patterns and relationships in language, making them better at generating human-like text.

The initial idea of GPT models was to tune them up specifically for translation from one language to another. Open AI took this idea much further.

The result: GPT creates unique and very specific initial request text outputs. And – what we all experienced in the last few months – ChatGPT caused incredible hype as it is…surprisingly human-like. 

ChatGPT vs GPT-4 vs GPT-3.5: the difference between models

Year after year, the GPT model was polished and constantly improved to reach linguistic excellence. On the last model, OpenAI’s team spent 6 months making GPT-4 safer and more aligned than the previous version. ChatGPT, which was made open to the public, played an important role here, as the team worked on the user feedback extensively.

The newest GPT-4 model is capable of performing a dozen of language tasks – creating unique content of any shape and context, as well as following complex non-language related tasks – for example, working with SQL and internal databases. Since it also works with images and was well-tuned after ChatGPT hype, it is more flexible and has many more possible use cases. Some of them we’ll cover below. 

Still, even after a grand progression, GPT models still seem to occasionally provide fake or not “aligned” (failing to be moral-stitched) information to users. 

Now that the GPT-4 model is available, anyone can test what it's good at and what it's not good at. To access the latest GPT-4, people have to subscribe to ChatGPT Plus for $20 per month. With this subscription, users can pick between two chatbots: one that uses GPT-3.5 and another that uses GPT-4.

What GPT is “good” at  

As we mentioned before, GPT was trained on the immersive amount of data. But it doesn’t mean it’s limited to what it already knows: GPT models can be trained on additional data (in other words, customized) and learn the patterns and structures of incoming data. This makes GPT highly context-aware and does the magic in recognizing patterns and relationships between words and phrases.

In other words: GPT can use the existing power of transformation to turn your data or prompts into something unique.

These two factors enable GPT in many ways: 

Being the large language model, GPT is intended to be used for: 

Question-answering (AI Chatbot)

One of the most obvious use cases – answering to questions. 

ChatGPT was specifically built to interact with users in chat. People can ask questions and receive answers right away. How's that? Not only is GPT able to understand what a user means, but it also builds a relevant reply – thanks to its huge database. 

So, a business that may want to use this GPT power and build a GPT-based chatbot, it's possible to connect your own trusted source, which is your website, knowledge base, internal documents etc. This way, a chatbot will refer to it as a source and use its language-generating capabilities to provide answers. 

Automate routine work

GPT already has billions of information it was trained on. It not only uses this amount of data as a source but is also capable of classifying it.

Why not use this superpower to work on top of your own data? 

Let's imagine we connected our own database – for example, a Knowledge Base – to GPT. Firstly, it can read the information stored, and then analyze to sort or group similar information. Secondly, GPT can run via chat to locate this information quickly and generate a text reply in seconds. Just like Google's Bard!

From user's side, instead of looking for a needed information, reading it and taking next steps, the GPT does all the work in a convenient way. 

Another example of using GPT for automation can be analyzing product feedback sentiment, support calls and transcripts. Same way, GPT can process the information instead of support agents. 

Writing assistance on specific topics

That's where marketing use cases are actually endless!

With GPT, users can create new content or rewrite content submitted by the user as a writing aid for business content or pre-defined topics. Users can only rewrite or create content for specific business purposes or pre-defined topics and cannot use the application as a general content creation tool for all topics. Examples of business content include proposals and reports. 

And in fact – here, the use cases are not limited. Many brand new business examples show how versatile the GPT applications can be. 

What about the Real Business Applications for GPT-4?

When ChatGPT was released, businesses actually stayed aside and watched the storm rise. 

With the GPT-4 release after 3 months, the situation has been totally different: a number of companies collaborated with Open AI to build their own solution before the GPT-4 or ChatGPT API has even been released.  

Some early adopters include:

  • Microsoft confirmed that versions of Bing using GPT had, in fact, been using GPT-4 before its official release. On March 17, 2023, Microsoft announced further integration of GPT-4 into its products, revealing Microsoft 365 Copilot, "embedded in the apps millions of people use daily: Word, Excel, PowerPoint, Outlook, Teams, and more". Basically, GPT is now built-in in the frequently used tools in the workplace. 
  • Snap Inc., introduced My AI for Snapchat+. My AI offers Snapchatters a friendly, customizable chatbot at their fingertips that offers recommendations, and can even write a haiku for friends in seconds. Snapchat, where communication and messaging is a daily behavior, has 750 million monthly Snapchatters.
  • Stripe, which uses GPT-4 to scan business websites and deliver a summary to customer support staff.
  • Duolingo built GPT-4 into a new language learning subscription tier. The team is creating a GPT-4-powered system that’ll retrieve info from company documents and serve it to financial analysts. 
  • Khan Academy is using GPT-4 to create a tutoring chatbot, which the organization names "Khanmigo". While in the "research phase", access to the chatbot is provided free to the students and teachers of 500 school districts who have "partnered" with Khan Academy. Public access is only offered to a limited number of users selected from a waitlist; after acceptance, a 20 USD per month fee is required to use the technology.
  • Instacart is augmenting the Instacart app to enable customers to ask about food and get inspirational, shoppable answers. This uses ChatGPT alongside Instacart’s own AI and product data from their 75,000+ retail partner store locations to help customers discover ideas for open-ended shopping goals, such as “How do I make great fish tacos?” or “What’s a healthy lunch for my kids?” Instacart plans to launch “Ask Instacart” later this year. 

What Can We Learn From the First Business Cases?

One of the most significant takeaways – giant companies, famous start-ups, and even the largest payment system trusted GPT. 

Each of these companies was invested and joined the game not to miss the competition. They chose their own use case and pushed it live to gather user feedback.

Probably, this approach is the most logical one in the context of GPT. How else do you test the technology at work? 

The time to act is now. As more businesses adopt GPT models, those that fail to keep up risk being left behind. By taking advantage of this technology now, you can gain a competitive advantage and position yourself as a leader in your industry.

 As a chatbot development company, we had experience with a lot of chatbot projects over time, as well as automation solutions. Here are our few best practices that we can recommend to follow when building a GPT solution:

Limit GPT to avoid mistakes & chatbot failure.

It's simple: connect your own source to GPT! This way, the chatbot will refer to your content first when generating a response. That could be the website, PDF, or any other database. You can try that for free with a gpt-4 chatbot generator

Choose a specific use case. 

The more specific it is, the more predicted results you will get. You've probably seen how many "bland" results GPT delivers when users ask very generic questions. So it's all about specific and well-designed prompts. 

For example, we at BotsCrew successfully use GPT for intent recognition in existing chatbots. This generative AI solution helps us to map what the user wants in order to give out the most relevant response. Some of our tests show an astonishing 86% of intent recognition without human intervention.

Another example is a free email extension, MailBuddy, The use case is very simple: achieve inbox 0. The extension allows generating responses to emails in seconds. We used GPT to analyze the incoming email and suggest ideas for a reply. Users can also specify what they want to include in the reply or let it do the job alone. As a result, anyone can reply to an email just by 2 clicks, a quick review, and hitting the button "send". 

 

Thanks to the open API, it works as a free Chrome extension directly from inbox without sign up or additional steps. 

Some other examples of how we use GPT include:

Make sure you're following AI security and overall, best practices

Multiple security concerns have been raised regarding ChatGPT.  Can ChatGPT store your data? 

Open AI has created ChatGPT to collect information and tune the GPT model for better understanding. So yes, it’s possible for ChatGPT to store your data. It’s a bad idea to share sensitive information to ChatGPT. It’s mentioned in Open AI’s privacy policy: When you use our Services, we may collect Personal Information that is included in the input, file uploads, or feedback that you provide to our Services (“Content”)

However, when using the GPT model via API, the risks of information leaks are less prominent. Security measures can vary from case to case: you could consider other practices like Microsoft Azure services. 

Here, there are a few approaches to Generative AI like (Chat)GPT that will help ensure the security and success of an independent GPT solution. 

We at BotsCrew believe that Generative AI will change how we perceive chatbots. After multiple experiments, we have built several approaches to try GPT for business – so you don’t have to study them yourself. A few well-tread ways to implement GPT at low risk include: 

The best choice if you're unsure how to use GPT-4 for business. Based on the Google Design Sprint methodology, the GPT Design Workshop lets you learn, map out ideas, and test a prototype to form a vision within two business days. Visit the page to learn more. 

Already have a GPT project in mind but unsure how to implement it into business? Learn how we leverage Generative AI with predictable results and up to security standards.