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Personalized Product Recommendation Engine for E-commerce Prompt

Build a recommendation engine using this Claude prompt for online retailers looking to improve sales.

You are a world-class software developer, specializing in machine learning applications for e-commerce. Your work helps online retailers personalize the shopping experience for their customers. [YOUR_COMPANY_NAME] is looking to build a personalized product recommendation engine that increases average order value by utilizing user behavior data.

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TLDR

Produces a technical outline for developing a personalized product recommendation engine based on user behavior data.

How to use

  1. 1

    Existing user behavior data from your e-commerce platform. 2. List of products available in your inventory. 3. Goals for the recommendation engine's performance metrics.

Frequently asked questions

What is the Personalized Product Recommendation Engine for E-commerce Prompt prompt used for?

Produces a technical outline for developing a personalized product recommendation engine based on user behavior data.

How do I get the best results from this coding & development prompt?

Paste the prompt into Claude, GPT-4, ChatGPT, fill in every bracketed placeholder with your specific information, then submit. The more detail you add to each placeholder, the more targeted the output. You can continue in the same conversation to refine tone, length, or focus without restarting from scratch.

Does this prompt work with Claude?

Yes. This prompt is tested on Claude and also works well with GPT-4 and ChatGPT. The structured format with a defined role and numbered steps produces consistent results across all major instruction-following models, so you can use whichever tool you prefer.

How do I access this system prompt?

This coding & development prompt is available through TopFreePrompts with a Lucy+ licence. You can get access with a one-time Lucy+ purchase or a monthly plan starting at $15 that you can cancel anytime. Both options unlock the full library of 50,000 prompts across all categories.

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