Ecommerce AnalystPricing AnalyticsIntermediateSingle prompt

Discount and Promotion Analysis AI Prompt

Analyze the effectiveness of discounts and promotions and optimize the promotional strategy. Promotion data: {{promotion_data}} (promotion type, discount %, products, period, or... Copy this prompt template, run it in your AI tool, and use related prompts to continue the workflow.

Prompt text
Analyze the effectiveness of discounts and promotions and optimize the promotional strategy.

Promotion data: {{promotion_data}} (promotion type, discount %, products, period, orders, revenue)
Baseline data: {{baseline_data}} (same period last year or non-promotional baseline)

1. Promotion performance metrics:
   For each promotion:
   - Revenue during promotion vs baseline (lift)
   - Gross margin during promotion vs baseline (margin impact)
   - Orders count and AOV during vs baseline
   - New vs returning customer mix during promotion

2. Revenue vs margin trade-off:
   - Revenue lift (%) from promotion
   - Gross profit change (%) from promotion (may be negative even if revenue is up)
   - Break-even volume: how much incremental volume is needed to offset the margin give-away?
     Break-even lift = Discount % / (Gross Margin % - Discount %)
     Example: 20% discount on a 40% margin product requires 100% volume increase to maintain gross profit

3. Promotion types comparison:
   - % off: drives broadest participation, margins most exposed
   - BOGO (Buy One Get One): volume driver, effective for high-margin products
   - Free shipping threshold: AOV driver (set threshold at 30% above current AOV)
   - Gift with purchase: drives specific product trial, protects revenue
   - Flash sale (time-limited): urgency driver, but trains customers to wait for discounts

4. Customer behavior post-promotion:
   - Are customers acquired during promotions at lower LTV than non-promotion customers?
   - Do promotional buyers return at similar or lower rates than full-price buyers?
   - Are existing customers simply shifting their planned purchases to discount periods?

5. Discount addiction signals:
   - Is there a trend toward increasing discount frequency to maintain revenue?
   - What % of revenue is generated at a discount?
   - Are customers waiting for promotions before purchasing? (Signal: conversion rate declines in weeks before promotions)

6. Optimized promotional calendar:
   - Based on analysis: which promotion types drive the best net margin impact?
   - Recommended promotional cadence: how often and at what depth?
   - Products that should never be promoted (inelastic, premium positioning)

Return: promotion performance table, break-even analysis, type comparison, post-promotion behavior analysis, discount addiction signals, and promotional calendar recommendation.

When to use this prompt

Use case 01

Use it when you want to begin pricing analytics work without writing the first draft from scratch.

Use case 02

Use it when you want a more consistent structure for AI output across projects or datasets.

Use case 03

Use it when you want prompt-driven work to turn into a reusable notebook or repeatable workflow later.

Use case 04

Use it when you want a clear next step into adjacent prompts in Pricing Analytics or the wider Ecommerce Analyst library.

What the AI should return

The AI should return a structured result that covers the main requested outputs, such as Promotion performance metrics:, Revenue during promotion vs baseline (lift), Gross margin during promotion vs baseline (margin impact). The final answer should stay clear, actionable, and easy to review inside a pricing analytics workflow for ecommerce analyst work.

How to use this prompt

1

Open your data context

Load your dataset, notebook, or working environment so the AI can operate on the actual project context.

2

Copy the prompt text

Use the copy button above and paste the prompt into the AI assistant or prompt input area.

3

Review the output critically

Check whether the result matches your data, assumptions, and desired format before moving on.

4

Chain into the next prompt

Once you have the first result, continue deeper with related prompts in Pricing Analytics.

Frequently asked questions

What does the Discount and Promotion Analysis prompt do?+

It gives you a structured pricing analytics starting point for ecommerce analyst work and helps you move faster without starting from a blank page.

Who is this prompt for?+

It is designed for ecommerce analyst workflows and marked as intermediate, so it works well as a guided starting point for that level of experience.

What type of prompt is this?+

Discount and Promotion Analysis is a single prompt. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.

Can I use this outside MLJAR Studio?+

Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.

What should I open next?+

Natural next steps from here are Dynamic Pricing Strategy, Price Elasticity and Optimization.