PromptEngineering

Compiled and presented by KisStartup

Using AI to make decisions that are more accurate, faster, and smarter

In an era where data has become a core asset, small and medium-sized enterprises (SMEs) now have access to an unprecedentedly powerful “analytical assistant”: AI combined with strong prompt-writing skills.

When pricing products and services, instead of relying on intuition or time-consuming manual models, businesses can leverage well-designed prompts to:

• Clearly understand cost structures and break-even points
• Analyze the market, competitors, and optimal pricing levels
• Test customer price acceptance
• Create multiple pricing scenarios
• Reduce risk and make data-driven decisions

A good prompt does not merely help AI generate accurate answers; it also enables business owners to think more strategically about price, value, and market positioning.

Why do businesses need good prompts for pricing?

Pricing is always a difficult challenge:
price too high, and products are hard to sell; price too low, and profits shrink or brand value is diluted.

However, AI cannot truly help if the prompt is too generic, such as:

“Help me price this product.”

This type of question is insufficient.

A good prompt must clearly define the context, objectives, data, and constraints, enabling AI to deliver recommendations that are practical and actionable.

The structure of a good prompt for product and service pricing

Below is the “B.O.S.T” framework, standardized for SMEs:

B – Background

• What is the business selling?
• Which market segment?
• What competitive advantages does it have?
• What is the current price level?

O – Objective (Pricing Objective)

Do you want to:

• Calculate production cost?
• Propose a retail price?
• Benchmark against competitors?
• Optimize profit or accelerate sales?

S – Specific Data

The more specific, the more accurate:

• Costs of materials, packaging, labor, utilities
• Target profit margin
• Customer segments
• Current market prices

T – Target Output

What kind of result do you want AI to deliver?
For example: a cost breakdown table, break-even analysis, three pricing options, and pricing strategy recommendations.

Examples of effective prompts
Sample Prompt 1 – Cost calculation and suggested pricing

“Act as a product pricing expert. Based on the following data:

• Raw material cost: 140,000 VND/kg
• Waste rate: 10%
• Packaging: 5,500 VND per 200g pack
• Labor + utilities: 12,000 VND per pack
• Target profit margin: 30%

Please calculate the cost per 200g pack and propose three suitable retail price options for the mid-range and premium markets. Present the results in a table and provide explanations.”

Sample Prompt 2 – Competitive pricing strategy

“Analyze appropriate pricing for Service X, given that Competitor A charges 2.5 million VND and Competitor B charges 3 million VND. My service has two key advantages: … and … The target customers are SMEs. Please propose three pricing strategies and explain the rationale behind each.”

Sample Prompt 3 – Testing customer price acceptance

“Simulate feedback from target customers (office workers – middle-income – quality-oriented). Given three price points of 150k, 180k, and 220k VND for a Tet gift product, identify the optimal price and explain why.”

Benefits for businesses that master prompt writing

When businesses master effective prompt design, they can:

• Make more accurate decisions without hiring expensive consultants
• Save time on analysis and forecasting
• Quickly test multiple pricing scenarios
• Reduce mistakes when expanding products or entering new markets
• Shift from intuition-based thinking to data-driven decision-making

Pricing is no longer a matter of “guesswork”; it becomes a scientific, executable process.

AI does not replace business decision-makers—but a good prompt can turn AI into the strongest collaborator in every strategic decision.

A business that knows how to use prompts effectively is faster, smarter, less risky, and more profitable.

If your business wants to learn how to build standardized prompts for management, marketing, sales, and pricing, let KisStartup accompany you on this journey.

Keep Innovation Simple, Stupid – Simplify to break through.

© Copyright belongs to KisStartup. Any form of copying, quoting, or reuse must clearly cite KisStartup as the source.

In the digital age, AI has become a familiar tool for businesses in planning, customer care, market research, and content creation.However, behind every AI command is a data center that consumes electricity, water, and emits CO₂. Without mindful usage, the environmental cost can quickly exceed expectations.

KisStartup – with experience supporting thousands of businesses on their innovation and digital transformation journeys – has compiled this guide to help companies use AI responsibly, efficiently, and in an environmentally friendly way.We call it Green Standard Prompting: boosting productivity while reducing emissions.

Why do we need "Green Standard Prompting"?
Every AI command consumes energy and water:
- Gemini (Google): approx. 0.24 Wh, emits 0.03 gCO₂, and uses 0.26 ml of water per average text prompt.
- ChatGPT (GPT-4o): approx. 0.3 Wh per prompt.

1 million prompts can consume around 300 KWh, equal to a household’s electricity use in one month.
So, every time you revise a prompt repeatedly, you're multiplying the power and water usage. That’s why carefully crafting your prompt is not only time- and cost-effective, but also a clear ESG (Environmental, Social, Governance) action.
Principles of Green Standard Prompting:

1. Be clear about your goal: what you want, for whom, and in what format.
2. Provide enough context: product, data, constraints.
3. Limit output length: specify word count or number of bullets.
4. Choose the right model: simple tasks → lightweight models.
5. Ask AI to request more info if needed, instead of guessing.​
6. Save and reuse good prompts to avoid repetition.

Example Green Standard Prompts
1. Planning Content Marketing
System (Role): You are a Sustainable Content Marketing expert.
User Prompt:

• Goal: Plan 2 weeks of content for a {industry} fanpage.
• Audience: {target customers}
• Context: product {...}, USP {...}, budget {...}
• Output (≤200 words):
  - 14-day content calendar
  - Captions ≤30 words
  - Hashtags ≤5 per post​
• Constraints: prioritize repurposing existing content, ask up to 3 follow-up questions if data is missing.

2. Developing a Green Export Plan
System (Role): You are a Green Export & ESG expert.
User Prompt:

• Goal: Create a 6-month export plan for {product} to {market}.
• Context: certifications, production capacity, current partners
• Output (≤250 words):
  1. 5 green requirements/VSS (Voluntary Sustainability Standards) for the marke.
  2. 3 current capability gaps
  3. 3 priority actions for the first 90 days
  4. 2 long-term opportunities​
• Constraints: include a checklist for executives, ask up to 5 follow-up questions if data is missing, cite sources.

​Steps to Build a “Green Standard” AI Assistant for Your Business

1. Define the assistant's role (e.g., Content Coach, Export Advisor).
2. Standardize the system prompt (role + green principles).
3. Create a sample prompt library (like examples above).
4. Train with real data (products, certifications, customer info).
5. Test & refine to minimize prompt iterations.
6. Integrate into workflows (chatbot, CRM, Notion/Slack).
7. Monitor & report on resource savings (tokens, kWh, CO₂, water).

Checklist Green AI Prompting
Before you type a command:

• Is the goal, target audience, and output format clear?
• Is the data sufficient so AI doesn’t have to guess?
• Have you set an output length limit?

When choosing a model:

• Do you really need a large model?
• Are you asking for images/slides unnecessarily when text suffices?

During execution:

• Does the AI ask follow-up questions when data is missing?
• Can this prompt be reused?

After completion:

• Is the output immediately usable, or does it require re-running?
• ​Can the prompt be shared with teammates?

• For an average text command:
  • Gemini (Google): approximately 0.24 Wh of electricity, emits 0.03 gCO₂, uses 0.26 ml of water.
  • ChatGPT (GPT-4o): estimated at around 0.3 Wh of electricity.
• These numbers may seem small, but for 1 million commands → approximately 300 kWh, which is the electricity consumption of a household in one month.
• Additionally, each 0.3 Wh of electricity could be equivalent to 0.03–0.21 gCO₂ depending on the "cleanliness" of the energy source.

• Vague prompt → AI gives incorrect responses → need to run again.
• No length limit → AI generates unnecessarily long text → consumes tokens, uses more electricity.
• Choosing an overly powerful model for a simple task → like using a truck to carry a bag of vegetables.

1. Clear goal: Specify exactly what you need, for whom, and in what format.
2. Provide sufficient context: Give data, conditions, and constraints upfront.
3. Limit output: Request specific word count or number of bullet points.
4. Choose the right model: Simple tasks → small models. Complex tasks → large models.
5. Avoid multimedia waste: Only ask for images/slides when absolutely necessary.
6. Save good prompts: Reuse them, don’t "reinvent the wheel."