Explainer translates complex SQL into plain business language. Share with product managers, analysts, and executives — no SQL knowledge required to understand the output.
Input: a CTE with window functions. Output: a plain-English report your product manager can read without asking a single question.
## What This Query Does — Plain English **In one sentence:** This report finds your top 10 most valuable customers by ranking them based on how much they've spent on completed orders. --- ## Business Context This query answers the question: *"Who are our best customers, and how much have they spent?"* It's the kind of analysis used for: - **Customer segmentation** — identifying VIP customers for loyalty programmes - **Sales reporting** — showing account managers which clients to prioritise - **Revenue analysis** — understanding what percentage of revenue comes from top customers --- ## How It Works (No SQL Required) 1. **First, it looks at all completed orders** — it ignores cancelled or pending orders, only counting transactions that actually happened. 2. **For each customer, it adds up their total spending** — if a customer placed 5 orders worth €200, €150, €300, €80, and €120, their total is €850. 3. **It ranks all customers from highest to lowest spending** — the customer who spent the most gets rank #1. 4. **Finally, it shows only the top 10** — the 10 customers with the highest total spending, along with their name and rank. --- ## Key Numbers to Know | Term in the Report | What It Means | |--------------------|---------------| | total_revenue | Total amount this customer has spent on completed orders | | order_count | Number of completed orders this customer has placed | | rank | Their position in the spending leaderboard (1 = highest spender) | --- ## What This Report Does NOT Include - Pending or cancelled orders - Customers with no completed orders - Customers ranked 11th or lower
Stop spending 30 minutes explaining what a query does. Explainer does it in seconds.
Translates SQL logic into business language — no jargon, no technical terms. Written for product managers, analysts, and executives.
Explains not just what the query does, but why it matters — what business question it answers and how the results would be used.
Formatted for non-technical readers. Share directly in Slack, email, or Confluence without editing. No SQL knowledge required to understand it.
Output is clean Markdown that renders beautifully in any modern tool — Notion, Confluence, GitHub, or email.
Every column name and technical term is explained in a table. Stakeholders understand exactly what they're looking at.
Explicitly states what the query does NOT include — filters, excluded statuses, date ranges — so stakeholders don't draw wrong conclusions.
Run Explainer before your next stakeholder meeting. Share the plain-English summary so everyone understands what the numbers represent.
When a business analyst asks about a query in your BI tool, paste it into Explainer and share the output instead of writing a manual explanation.
Create a business-language glossary for every report in your data warehouse. Attach the Explainer output to each report in Confluence.
Help new product managers or analysts understand the data model by explaining the key queries that power their dashboards.
Explainer currently generates output in English. Multi-language support is on the roadmap.
Yes. Explainer is designed for enterprise-complexity SQL. The more complex the query, the more value Explainer provides — it breaks down each CTE and explains how they connect.
Yes. Explainer output is written at a level appropriate for non-technical executives — clear, concise, and free of SQL terminology.
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