Top 10 prompt engineering use cases for business
Think of prompt engineering as crafting the perfect instructions to get the AI to do exactly what you want.
7 August, 2024
If you’ve ever tried building AI-powered products or had any part in it whatsoever, you've likely encountered some frustrating challenges when working with large language models.
Your users may be getting inconsistent or irrelevant responses. Or perhaps the AI keeps going off on tangents instead of addressing the core question. Maybe you're worried about inappropriate content slipping through.
This is where prompt engineering comes in. It's a set of techniques to guide AI models to produce better, more reliable outputs. Think of it as crafting the perfect instructions to get the AI to do exactly what you want.
We’ve used it in our work and helped other companies with it. If you are still hesitant about the benefits and use cases of prompt engineering for business, fret not - here’s a helpful guide to get you started.
Prompt engineering for business: problems and solutions
In one of our previous blog posts, we covered what is the purpose of prompt engineering in gen AI systems. Simply put, it’s to better understand user intent.
With that in mind, let's now look at some common problems prompt engineering can solve:
- Inconsistent responses. Designing precise prompts gives better guarantees that the AI stays on topic and provides uniform answers to similar queries. You get a more dependable user experience.
- Lack of expertise. Need your AI to sound like an expert in a specific domain? Carefully engineered prompts can instruct the model to adopt the right tone and reference appropriate sources.
- Generating irrelevant content. Well-crafted prompts act like guardrails and keep AI focused on producing more relevant information that better fits the user intent.
- Safety concerns. Prompt engineering allows you to build in safeguards against generating harmful or inappropriate content.
- Inefficient interactions. Strategic prompts can extract more value from each API call.
- Limited creativity. The right prompts can enhance the AI's ability to generate novel ideas and solutions.
Based on all these perks, we can now more clearly see the best uses of prompt engineering for business. Hop on to the next chapter!
Top 10 business applications of prompt engineering
Here are ten of the best use cases for prompt engineering in a business setting, along with real-life examples, tips, and benefits of prompt engineering in that specific case.
1. Product recommendations
Prompt engineering helps develop personalized product recommendation systems. Prompts that include customer data, preferences, and behavior can be designed to offer specific product suggestions.
Example:
Amazon's "You may also like..." section uses AI to offer product recommendations based on a customer's purchase history and browsing behavior.
Techniques:
Use machine learning algorithms to analyze customer data and patterns. Natural language processing (NLP) helps generate personalized prompts that feel like a natural conversation with the customer.
Benefits:
- Increased sales
- Improved customer satisfaction
- Reduced customer churn
2. Employee onboarding and training
Prompt engineering can streamline employee onboarding and training processes. Interactive prompts designed in the right way can be used to guide new hires through the necessary steps, provide relevant information, and offer more precise training materials.
Example:
Microsoft's "First Day" chatbot uses AI to welcome new employees, answer common questions, and direct them to important resources and documents.
Techniques:
Create dynamic prompts that adapt to the user's responses, simulating a conversational experience. Use a combination of text, images, and videos to make the onboarding process more engaging.
Benefits:
- Faster and more efficient onboarding
- Reduced time spent on administrative tasks
- Improved employee satisfaction
3. Brainstorming
Spark creativity and innovation within your organization with this next one on the list of the business applications of prompt engineering. Did you know that carefully crafted prompts can stimulate employees to think outside the box, generating fresh ideas and potential solutions to business challenges?
Example:
Google's "20% time" policy encourages employees to use one day a week for creative projects outside their regular job descriptions. Who says they are not often sparked by innovative prompts?
Techniques:
Use open-ended prompts that provide a broad framework while allowing freedom for exploration. Set up an idea-generation platform or chatbot that periodically sends out creative prompts to employees
Benefits:
- Increased innovation
- Improved problem-solving skills
- Enhanced employee engagement
4. Customer service and support
Enhance your customer service by responding quickly and more accurately to common inquiries. Well-designed prompts can anticipate customer needs and even provide solutions.
Example:
Apple's Siri and Amazon's Alexa use AI to understand and respond to user queries. They usually provide information, recommendations, and troubleshooting steps.
Techniques:
Develop a comprehensive knowledge base of customer inquiries and corresponding prompts. Train AI models on it to recognize patterns and provide appropriate responses.
Benefits:
- Improved customer satisfaction
- Reduced response times
- Lowered customer support costs
5. Content creation and marketing
This next use of prompt engineering can assist in content creation, generating ideas and outlines for blog posts, social media copy, and advertising campaigns. Prompts can provide structure and inspiration, streamlining the content creation process
Copy.ai is a platform that uses AI to help marketers and writers generate copy for various purposes, from website copy to social media ads.
Techniques:
Build a prompt library relevant to your marketing and content creation needs. Provide prompts that include key messaging, target audience insights, and content goals. Use prompt engineering together with content creation tools like AI-powered writing assistants.
Benefits:
- Faster content creation
- Improved consistency across marketing materials
- Enhanced creativity
6. Meeting optimization
Prompt engineering can also make meetings more productive and focused. Prompts can be used to set clear agendas, encourage participation, and ensure that your discussions stay on track.
Example:
Slack's "Standup" app uses AI to structure daily stand-up meetings, ensuring everyone is aligned and important topics are covered.
Techniques:
Design prompts that outline the meeting's purpose, desired outcomes, and key discussion points. Use interactive features to encourage your employees to participate and collaborate.
Benefits:
- Improved meeting productivity
- Increased employee engagement
- Reduced time spent in unnecessary meetings
7. Process automation
The next use of prompt engineering is meant to automate repetitive tasks and streamline business processes. Proper prompts can trigger automated workflows better and reduce manual effort as a result.
Example:
A workflow automation platform Zapier uses AI to trigger automated tasks based on specific events or user actions.
Techniques:
Map out the processes you want to automate and design prompts that trigger the desired actions. Integrate prompt engineering with your existing systems and workflow management tools.
Benefits:
- Increased efficiency
- Reduced time spent on tedious tasks
- Improved accuracy
8. Data analysis
Prompt engineering can help extract valuable insights from data by inputting data sets and parameters. It can then guide data analysis tools to focus on specific areas of interest.
Example:
IBM Watson uses AI to analyze large volumes of data and provide insights to businesses so they can identify trends, patterns, and opportunities.
Techniques:
Integrate prompt engineering with your data analytics platforms. Provide prompts that specify the data sources, parameters, and areas of interest for analysis. Train the system to recognize relevant data patterns and provide insights.
Benefits:
- Improved decision-making
- Faster identification of trends
- Enhanced competitive advantage through data insights
9. Personalized UX
Prompt engineering can be used to create dynamic and personalized user experiences. By leveraging user data and preferences, prompts can tailor interactions, content, and offerings to individual users, increasing engagement and satisfaction.
Example:
Netflix uses AI to offer personalized content recommendations based on users' viewing histories and ratings.
Techniques:
Implement prompt engineering in your user interface designs. Use dynamic content that adjusts based on user interactions. Learn more about ChatGPT prompt engineering for UX design.
Benefits:
- Increased user engagement
- Improved customer retention
- Enhanced brand loyalty.
10. Knowledge sharing and documentation
Interactive prompts can guide employees through the process of documenting their tasks, sharing best practices, and capturing institutional knowledge for future reference.
Example:
Atlassian's Confluence platform uses AI to structure knowledge-base articles so that it’s easier for the employees to document and share information.
Techniques:
Provide templates and prompts that outline the key sections and information to include in knowledge-sharing documents. Allow employees to comment and contribute additional insights.
Benefits:
- Improved knowledge retention
- Easier onboarding for new employees
- Enhanced collaboration across teams.
Conclusion: prompt engineering best practices
To sum it all up, prompt engineering is one of the best tools and methods for improving your AI-powered products. Refining how you communicate with language models can help you very noticeably enhance your output quality and user experience.
We’d like to turn this prologue into a quick overview of the best practices to keep in mind if you want to do a bit of prompt engineering for business yourself:
- Clearly state what you want.
- Give the AI relevant background info.
- Specify the desired output format.
- Treat prompt engineering as an ongoing process. Test different phrasings and analyze results.
- Set up initial instructions to define the AI's role and behavior throughout the conversation.
- For more intricate problems, guide the AI through a step-by-step approach.
- Leverage few-shot learning. Provide examples of desired inputs and outputs to improve performance on new tasks.
- And finally, use prompts to steer the AI away from inappropriate or off-topic content.
And, as usual, if you need some guidance or an extra pair of skilled professionals, you should always reach out to Merge.
