Claude Prompting Guide [Coming Soon]

Claude is a capable AI on its own. But without the right context or when faced with too much raw data, it struggles.

That's where RetentionX comes in. RetentionX has already done the hard analytical work: modeling your customer cohorts, calculating lifetime value, segmenting your audience, and tracking repeat purchase behavior across every order in your store's history. That means Claude does not have to start from raw data. It can work with intelligence that has already been aggregated, modeled, and validated by RetentionX.

This matters because your store generates large volumes of data: thousands of orders, customers, and transactions. If Claude had to process all of that directly, the results could include approximations, gaps, or answers that sound plausible but are not grounded in your actual numbers.

By acting as a trusted analytical layer between your store data and Claude, RetentionX helps make the answers more reliable. Claude is not guessing from raw exports. It is working with clean, pre-computed RetentionX insights.

Selecting the Right Claude Model

Selecting the right model helps Claude deliver the best response for the task at hand. Available Claude models may vary depending on your plan. As a rule of thumb, choose the model based on the complexity of your task.

For most RetentionX analyses, use the model Claude recommends as the best balance of speed and reasoning. This is usually the right choice for day-to-day business questions, weekly performance reviews, customer analysis, product analysis, and strategic follow-ups.

For complex or high-impact questions, choose the most advanced reasoning model available to you, especially when investigating a major revenue drop, comparing multiple possible drivers, preparing an executive summary, or building a detailed strategic recommendation.

For quick, lightweight tasks, choose a faster model. This works well for summarizing a previous analysis, rewriting a recommendation, shortening an output, or checking a simple follow-up question.

Writing a Good Prompt

The best prompts give Claude three things: a clear time window, a business question, and any context Claude may not know.

Use this simple structure: [Time window], [Business question]. [Optional context.]

For example: “Last 30 days, why is repeat revenue down? We ran a flash sale the week before, so please check whether demand was pulled forward.”

If you have access to multiple stores, include the store name as well: [Time window] for [Store], [Business question]. [Optional context.]

For best results, use natural time windows like Yesterday, This week, Last 30 days, This quarter, or Last 12 months. Ask the business question instead of naming specific metrics or tools, and add helpful context such as campaigns, product launches, inventory issues, price changes, or seasonality.

RetentionX Skills for Claude

To help you get started, we’ve prepared a set of ready-to-use Claude skills for common RetentionX analyses.

Skills are reusable prompt templates that include the instructions Claude needs to run a structured analysis on your RetentionX data. Download the skills below, add them to your Claude settings, and start a new conversation.


 

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