How to turn Chat GPT into a powerful tool to improve user experience and work efficiency
Chat GPT can generate responses to user requests in a variety of contexts. This allows us to use it to create essays, gather information on a particular topic, and analyze data.
However, we can also use Chat GPT in our workflow, especially when designing the user interface. For example, Chat GPT can help determine a particular audience’s most accurate tone of voice, anticipating users’ questions to provide quick and precise answers. From this perspective, Chat GPT can be a powerful tool for improving the user experience and increasing efficiency.
I’ve previously reviewed Chat GPT and given examples of its use in a UX designer’s work:
This time I’ve collected new options for integrating this tool into our work.
1. Exploring user needs
Chat GPT can be used to create a virtual assistant who asks the user questions and, based on the answers, suggests ready-made solutions or develops new functionality. For example, a mobile app designer could use the Chat GPT-based virtual assistant to ask users what features are missing from the app. Then, based on the information, propose options to the team to improve the user interface.
2. Creating a bot for customer service and improving the website or app navigation
Chat GPT can be used to create a bot for customer service. It can help address issues related to the use of the product or application. For example, a website designer can create a bot based on GPT to help users find the right pages or information.
3. Validation of design concepts
Creating virtual users based on Chat GPT can be a relatively easy and effective way to validate the design concept and get feedback.
To do so, you can use the following algorithm:
- Define your target audience profile and compile a set of typical queries and phrases that might come from chat users.
- Use these queries to train the Chat GPT model on the platform of your choice (e.g. Google Colab, Hugging Face or others).
- Create virtual users using the generated Chat GPT model responses. You can set up different user profiles using additional requests and contexts.
- Use the created virtual users to test iterations of the design concept. See how well your design matches the users’ requests and needs.
Of course, when using the method, it’s essential to realize that the test results may not match honest feedback, as virtual users are different from real users. So it’s better to use this approach with other design testing methods.
Here are few more platforms which can be helpful to train Chat GPT models:
4. User experience analysis
Chat GPT effectively analyses user feedback on different platforms and creates user experience reports.
Examples of using Chat GPT for user feedback analysis and reporting:
5. Creating personalized recommendations
Chat GPT can create personalized user recommendations based on their preferences and behaviours. To do this, train the model on users’ legends (search and browse products or services, recent orders on the site, based on context) and then use it to analyze current user requests.
6. Creating a more natural conversational interface
A UX designer can use Chat GPT to create a chatbot that communicates with the user in a natural and understandable language. To do this, the Chat GPT model must first be trained using different contexts and scenarios, the more comprehensive the training dataset, the more efficiently the chatbot will handle user requests. When the model is ready, it can be used to create a chatbot.
Platforms and tools that can be used to create chatbots using Chat GPT:
- Google Dialogflow — https://cloud.google.com/dialogflow
2. Microsoft Bot Framework — https://dev.botframework.com/
3. Amazon Lex — https://aws.amazon.com/lex/
4. Hugging Face Transformers — https://huggingface.co/transformers/
5. OpenAI API — https://openai.com/api/
6. Rasa — https://rasa.com/
7. IBM Watson Assistant — https://www.ibm.com/watson/assistant/
8. Botpress — https://botpress.com/
7. Automating customer support processes
Chat GPT can be used for the automation of customer support processes. For example, you can create an automated order processing system that will quickly and efficiently process customer requests and notify them of order status.