**Recipes are agentic workflows that automate the repetitive parts of your data work, turning messy, raw data into something you can actually use, without writing a single formula.**

![Recipes workflow](/images/recipe.gif)

## Think of Recipes like apps on your phone

> Your Android phone is powerful on its own, but **apps** are what make it useful for specific jobs. Chrome is just a browser until you add an **extension**. OrcaSheets works the same way: the sheet is the canvas, and **Recipes** are the purpose-built tools that plug into it to get a specific job done.

## What is a Recipe?

A Recipe is a small, agentic workflow built by the OrcaSheets team to take over one specific, recurring data chore on your behalf.

You just need to:

1. **Open** a Recipe from the toolbar.
2. **Point** it at your data or a connector.
3. **Set** a few options.
4. **Run** it.

From there, the Recipe takes over the repetitive work: pulling data in, cleaning it up, joining related sources, rolling it up into summaries, and handing you back a table that is ready to chart, pivot, or share. You stay in charge; the Recipe handles the busywork.

## Why use a Recipe?

Most data work is the same five steps, done over and over. Recipes automate those repetitive parts so you do not have to rebuild the same messy spreadsheet logic every month. Instead of stitching together imports, lookups, pivot tables, and cleanup steps by hand, you pick a Recipe that already knows how to handle a specific situation, and let it run.

For example:

- Reconciling Shopify orders against Stripe payouts.
- Turning Google Ads spend into a weekly ROAS report.
- Rolling up daily transactions into a monthly revenue summary.

## What a Recipe can do

A single Recipe can combine any of the following into one smooth workflow:

- **Connector integrations**: pull data directly from sources like Shopify, Stripe, Google Ads, Meta Ads, GA4, and more, so you do not have to export and re-import CSVs.
- **Data cleaning and standardisation**: fix column names, data types, date and timezone formats, currencies, and messy text values, so your data looks consistent every time.
- **Aggregations and rollups**: turn row-level data into daily, weekly, or monthly summaries, cohort tables, and KPI rollups that are ready to read at a glance.
- **Joins and enrichments**: stitch together related datasets such as orders, payments, customers, and ad spend, so you can see the full picture in one table.
- **Dashboard-ready outputs**: produce tables shaped specifically for charts, pivots, and reports, so the next step is just "plug it into a dashboard".

In short, each Recipe is like a small, trusted teammate that quietly takes care of one specific, repetitive data chore, so you do not have to.

## How to use Recipes

1. Click **Recipe** in the toolbar menu.
2. Browse Recipes by workflow category (examples):
   - E-commerce reconciliation (orders, payments, refunds, settlements)
   - Ad spend and ROAS analysis (cost, clicks, conversions, attribution rollups)
   - Churn / retention analysis (cohorts, repeat rate, reactivation)
   - Revenue and margin analysis (GMV, net revenue, discounts, COGS)
   - Data cleanup and standardisation (normalise columns, types, naming)
   - KPI rollups and dashboard-ready summaries (daily / weekly / monthly)
   - Connector-driven workflows (pull, clean, and model data from a source in one go)
3. Select a Recipe that matches your workflow and input data shape.
4. Configure parameters and apply the Recipe to transform your data.

## Notes

- Recipes are a **premium feature** and require an upgraded account.
- Your data must match the expected format for a Recipe to work correctly.
- Recipe development is currently done only by the OrcaSheets team. If you want a new Recipe built, reach out to `hello@orcasheets.io`.

## Video walkthrough

[Watch the Recipes + Presets feature video](https://www.youtube.com/watch?v=EBYu6ToL8WA#embed)

## Related pages

- [Importing Data](/docs/data-import)
- [Troubleshooting](/docs/troubleshooting)