Should I build a custom ChatGPT for customer service?

ChatGPT is everywhere. And for good reason.

It’s improving the day-to-day lives it’s over 200 million active users. Many people around the world use it for different tasks. They rewrite emails. They learn new coding languages.

They manage their schedules. They create cover letters. They even tell jokes. The list of uses is seemingly endless.

It’s no wonder businesses are taking notice. And for support teams, the application of ChatGPT in customer support and customer service is clear. Faster, more accurate, and personalized customer contact are in well within reach.

But using the public or even premium ChatGPT interface is not always ideal for business use. Which leads enthusiastic teams to wonder: Can I customize ChatGPT for my support team?

The short answer is yes (and we’ll show you how). But you’ll also learn that it may be a little more complicated than it seems. Let’s get into it.

ChatGPT customization for customer service

Building your own custom version of ChatGPT comes with a bunch of benefits that customer support teams want to tap into.

Why customize ChatGPT?

There are more than a few reasons why teams would want a custom version of ChatGPT to work with their support staff.

1. Fast and consistent responses: ChatGPT never misses a beat when it comes to standard responses. And it can deliver those responses in about 1.5 seconds.
2. 24/7 availability: When integrated into your tools and platforms, ChatGPT can provide “always-on” support. What business wouldn’t love a support agent that doesn’t need sleep, holidays, or time off?
3. Team efficiency: Support teams can use ChatGPT for many standard and repetitive tasks. This saves time for more important work that builds relationships.
4. Cost savings: By handling specific repetitive tasks, ChatGPT can help teams decrease the headcount needed for peak seasons.
5. Scalable support: ChatGPT can handle spikes in support requests without compromising on the quality of answers or service.
6. Personalization: When connected to your other platforms and tools, a custom ChatGPT solution can give personalized responses. It does this by using customer history, preferences, and past interactions. This way, you provide your customers with personalized answers and responses.
7. Agent productivity: ChatGPT helps your agents find, summarize, and rephrase information. This greatly reduces the time they spend switching between tabs and windows.
8. Escalation cues: ChatGPT can detect feelings in customer messages. It can alert you if a customer seems unhappy. It can also suggest that your agent ask for a review if the customer appears satisfied.
9. Multilingual: ChatGPT can speak many languages, providing great support for your customers in different countries.
10. Brand and tone of voice: Based on your prompt, ChatGPT can create customer responses. It will match your company’s tone of voice every time.
11. Analyze trends: ChatGPT can look into your customer contact trends. It can find recurring issues and opportunities for improvement.
12. You can tailor ChatGPT to meet industry rules and security standards, such as GDPR or HIPAA, ensuring compliance and security. This ensures that we handle customer data according to plan.
13. Faster support onboarding: If you often hire new support agents, you are not alone. ChatGPT can help your team learn quickly. It provides tailored support, policy insights, and customer information.

This list shows that ChatGPT can make your support team feel super-human. It can also help turn your customers into loyal fans with just a few prompts.

Well, not quite. To enjoy these benefits, you need to create specific prompts with the right settings. You also have to connect ChatGPT to your business systems, tools, and platforms. And we’ll get to that in a bit.

What can you customize in ChatGPT?

To set your team up with an AI solution for customer service, you can customize a few elements to ensure your team has the right knowledge and information.

So, can you train ChatGPT on custom data? Absolutely. And here’s the kind of instructions for ChatGPT what you’ll need to train it on and give it access to.

1. Knowledge base: You’ll need to give ChatGPT access to all of your frequently asked questions (FAQs), product information, policies, procedures, internal guides, and business-specific words.
2. Communication guidelines: Train ChatGPT on your specific communication guidelines so that it can recommend and interact as intended.
3. Conversation workflows: Define what ChatGPT should do or respond in specific customer scenarios including decision trees, escalations, or personalized responses.
4. Multilingual nuances: Auto translate is getting better, but for primary customer markets, you may want to consider training ChatGPT on the nuances within specific languages and regions.
5. Role-based access: Give different teams access to different versions of ChatGPT based on their function and ChatGPT’s access to specific knowledge bases and information.
6. Sentiment responses: Program ChatGPT to respond to certain customer sentiments with the right human emotional response.
7. CRM and support tools: Connect ChatGPT with your tech stack to allow it to update information, retrieve information, and follow up on issues.
8. Custom integrations: To access information in other systems (like order management, inventory), you will need to develop custom API, especially if this is a system that is custom to your business.
9. Security and compliance docs: ChatGPT doesn’t know which regulations and security protocol you’d like it to follow. Make sure to provide it with the right documentation
10. Feedback loops: Train your ChatGPT to initiate feedback loops where it analyzes its own and your teams’ effectiveness.

If you’ve trained a chatbot before, you may think that this pretty simple. But unlike a chatbot, ChatGPT doesn’t operate natively within your business ecosystem.

All of these things need very careful integration and need to be fine tuned by your team. If you allow ChatGPT to pull from outdated or incorrect data sources, your team and customers may suffer the consequences and you may negate any of the intended benefits.

What do you need in order to customize ChatGPT?

Alright, let’s get practical here. You’re in. You want to create a custom version of ChatGPT— what do you need?

• Knowledge base (most likely compiled from all of the customization possibilities above)
• Customization platform (OpenAI, Microsoft Azure, or a third-party platform)
• API keys and access to all the tools, platforms you’d like to integrate
• Data set of customer conversations
• Custom response logic based on what you’d like ChatGPT to handle
• ChatGPT Plus or enterprise subscription

But more than these items above, you’ll need two additional things: right team and time.

7-steps to create a custom ChatGPT

If you’re here looking for ChatGPT custom instructions, this is the part where we’ll show you how to make a custom ChatGPT. Let’s go.

1. Define your objectives

Clearly outline what you want your custom ChatGPT to achieve:

• Purpose: Is it for customer support, content generation, education, or something else?
• Tone & Style: Do you want it formal, playful, or domain-specific?
• Functionality: Will it integrate with external tools, databases, or APIs?

2. Choose a foundation

You have a few options for the base model:

1. Use OpenAI's GPT API: With OpenAI’s API, you can customize prompts, responses, and user interactions without building a model from scratch. Fine-tuning is available if needed to tailor the behavior further.
2. Open-source models:Use open-source alternatives like LLaMA 2, Falcon, or GPT-J. These models allow you to train or fine-tune locally or in the cloud.

3. Fine-tune the model (Optional)

Why fine-tune? To teach the model domain-specific knowledge or a particular tone.

• How to fine-tune:
• Collect relevant data (e.g., conversation logs, FAQs, etc.).
• Use tools like Hugging Face’s Transformers library to fine-tune the model.
• Fine-tuning requires computing resources, such as GPUs.

4. Build the application

Presumably you’ll want your custom GPT to “live” somewhere. In this case, you’ll need to build an application. This will require a frontend and backend, plus API connections. Make sure to define specific instructions or constraints in system prompts or via programmatic rules.

5. Add personalization

As previously discussed, there are a few ways you can personalize your GPT.

• Preloaded prompts: Set a personality or tone by crafting detailed instructions for the model’s behavior.
• Memory: If you need the model to remember conversations (beyond a session), implement a database to store and retrieve context.
• Integration: Connect to CRM tools, knowledge bases, or other platforms.

6. Deploy

To deploy your custom GPT, you’ll have to host your application on a server (e.g., AWS, Azure, or Google Cloud). Make sure you leave time to optimize for scalability if you anticipate heavy usage.

7. Monitor and improve

This is likely the most time-consuming step if you want to make sure that your GPT is functioning as expected. Continuously monitor performance and gather user feedback; update the model’s training data or prompt instructions based on these insights.

Are you already looking at this 7-step list to create your own ChatGPT and thinking: “no, this is not for me?” Don’t worry, this is not the only option available to you. Read on.

Pros and cons of a custom ChatGPT

Creating a custom ChatGPT for your specific situation may seem appealing if you have the right talent in-house and a commitment towards improving your organizational AI capacity. But, it may also distract from your core business; whether its e-commerce or hospitality, chances are that tech development may be better handled externally.

Pros of developing your own ChatGPT

• Learning the ins and outs of ChatGPT: As you can see above, by creating your own custom GPT, your team will learn the ins and outs of creating one. This can be an asset to your team based on expanding the use cases you’d like to apply custom GPTs to.
• Hands-on AI experience: Customizing your own ChatGPT is not for the faint of heart, but it certainly can bolster your team’s internal understanding of how Gen AI works. They’ll need to understand not just how to prompt, but how to set up rules and parameters to get the right responses from your GPT.
• Fully custom GPT: When done well, you could have your own AI solution, customized for your own business. And while there are other ways of doing this, a GPT that is able to deliver business-specific information to your team is invaluable when it comes to team efficiency.

Cons of customizing your own ChatGPT

• Adoption: With a custom ChatGPT, you cannot be sure how many of your support agents are using it as it won’t produce any reporting for you. Additionally, teams may struggle to use a fully custom (and (sometimes complex) GPT with a custom interface.
• Unreliable answers: First-time customizers have reported issues with unspecific and shallow answers. Additionally, if there’s not enough time for testing and monitoring, you may wind up with a solution that’s less than ideal for equipping your team with high-confidence responses.‍
• Time spent coaching team: And sometimes in order to get accurate answers, you need to coach your team on how to interact with the GPT which entails extra training.‍
• Needs development and topic expertise: The best results with custom GPTs are achieved with both technical development knowledge and topic expertise, meaning without both, you may be better off using the standard ChatGPT model.

Neople: the best alternative to building your own ChatGPT solution

If you reviewed the the 7-steps to create your own ChatGPT (plus all of the pros and cons) and decided that this isn’t in the cards for your team today, you wouldn’t be alone. But that doesn’t mean that you have to give up on the notion all together. In fact, the Neople team often work with teams that already explored the custom GPT option.

So, how can a Neople fill the gap of a custom GPT (and more) for your team? In short:

• Integrates with all of your existing tools: A Neople can already work in some of the most common support tools for e-commerce businesses. This means that you don’t have to worry about setting up any custom APIs.
• Trained on your company data: The Neople team will ensure that your Neople is trained specifically on your company data including your FAQs, policies, standardized answers, and more. We’ll even help your team build and track down this information to speed up the process.
• Delivers answers in your company tone of voice: Your Neople will be trained on your brand tone of voice, ensuring that every response is on brand.
• Premium service: Our team is responsible for the success and onboarding of your Neople. This means that we’ll make sure your team is trained and set up to work with your Neople to unlock team efficiencies from day one.

In short, a Neople can do all of the things that a custom GPT can (and more) and your team can unlock the benefits instantly, with no development time needed.

Curious to learn more? Book a meeting with our team today.

To customize, or not to customize?

The decision to build your own custom ChatGPT solution ultimately depends on your team's technical capabilities, resources, and long-term AI strategy. While creating a custom solution offers complete control and valuable learning opportunities, it requires significant investment in time, expertise, and ongoing maintenance. For many businesses, especially those focused on delivering exceptional customer service, partnering with a specialized solution like Neople offers the perfect balance of customization and immediate value.