Ecommerce AnalystMerchandising AnalyticsIntermediateSingle prompt

Search and Discovery Analysis AI Prompt

Analyze on-site search behavior and product discovery patterns to improve findability and merchandising. Search data: {{search_data}} (search_term, frequency, click-through, add... Copy this prompt template, run it in your AI tool, and use related prompts to continue the workflow.

Prompt text
Analyze on-site search behavior and product discovery patterns to improve findability and merchandising.

Search data: {{search_data}} (search_term, frequency, click-through, add-to-cart, purchase)
Navigation data: {{navigation_data}}

1. Search usage metrics:
   - % of sessions using the search bar
   - Search users vs non-search users: conversion rate comparison
   - If search users convert at > 2x non-search users: search is a high-value entry point to optimize

2. Top search terms analysis:
   - Top 50 search terms by frequency
   - Click-through rate per search term: did the user find what they were looking for?
   - Add-to-cart rate per search term
   - Zero-results searches: searches that returned no results (high-priority fixes)

3. Zero-result and low-result searches:
   - What are customers searching for that the store does not carry?
   - Which zero-result searches represent a product gap opportunity?
   - Which low-result searches are caused by poor search configuration (typos, synonyms)?
   - Example: 'sneakers' returns 0 results but 'trainers' returns 200 (synonym issue)

4. Search-to-purchase funnel:
   - For the top 20 search terms: click rate, add-to-cart rate, and purchase rate
   - High search frequency but low purchase rate: search results not matching intent
   - Products receiving many searches but with low stock: restock priority

5. Category navigation analysis:
   - Which category pages have the highest bounce rate?
   - Click distribution on category pages: are users clicking the right products?
   - Category sort order: is the default sort (best sellers, new arrivals, featured) working?

6. Discovery optimization recommendations:
   - Add synonyms to search engine for top zero-result queries
   - Promote 'Hidden Gem' products (high conversion, low traffic) in search results and category pages
   - Create product collections or gift guides based on common search intent clusters
   - Improve autocomplete suggestions for top search terms

Return: search usage metrics, top and zero-result analysis, search-to-purchase funnel, category navigation insights, and discovery optimization recommendations.

When to use this prompt

Use case 01

Use it when you want to begin merchandising 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 Merchandising 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 Search usage metrics:, % of sessions using the search bar, Search users vs non-search users: conversion rate comparison. The final answer should stay clear, actionable, and easy to review inside a merchandising 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 Merchandising Analytics.

Frequently asked questions

What does the Search and Discovery Analysis prompt do?+

It gives you a structured merchandising 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?+

Search and Discovery 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 Cross-Sell and Upsell Analysis, Inventory Analytics, Product Catalog Performance Analysis.