> For the complete documentation index, see [llms.txt](https://docs.chord.co/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.chord.co/model-your-data/model-amplifications/planned-forecasts.md).

# Planned forecasts

## Planned forecasts

{% hint style="info" %}
Note: Our Model Amplifications feature **only accepts files in CSV format at this time.** Please make sure the files you upload are CSV files.
{% endhint %}

## Overview

Chord Performance brands can now upload their daily planned forecasts of gross and net revenue along with number of orders and number of customers. With this, brands can now track their store performance comparing their forecasts with actuals.

## How it works

This amplification enables the input of data at varying levels of detail.

1. The fields `Date` and `Forecast Version Name` are **required** and cannot be left blank.
2. The fields `Is New Customer,` `Variant Product Category`, and `Variant Product Subcategory` can be left blank to forecast different level of details:
   1. When `Is New Customer` is left blank it will be considered as ***All type of customers***, meaning both new and returning customers.
   2. When `Variant Product Category` is left blank it will be considered as ***All product categories**.*
   3. When `Variant Product Subcategory` is left blank it will be considered as ***All product subcategories.***
3. Fill the rest of the fields with the forecasted value. Take into account the definition of each metric:
   1. **Gross Revenue:** Gross revenue of the orders calculated as **item\_total + fulfillment\_total**
   2. **Net Revenue:** Net revenue of the orders calculated as **item\_total + fulfillment\_total - promo\_total - refund\_total**
   3. **Fulfillment Total:** The total shipping revenue
   4. **Promo Total:** The total discounts applied to the price of the order
   5. **Refund Total:** The total refund transactions applied to the order

Based on the above, there are six (6) possible levels of detail in this amplification (with each level's required attribute(s)):

* **Total Daily Forecast**
  * *No fields required*
* **Customer Type Daily Forecast**
  * `Is New Customer`
* **Subcategory Daily Forecast**
  * `Variant Product Subcategory`
  * NOTE: If the `Variant Product Subcategory` is filled, the corresponding `Variant Product Category` must be filled as well, otherwise it will appear as **NOT-PROVIDED**.
* **Category Daily Forecast**
  * `Variant Product Category`
* **Customer Type by Category Forecast**
  * `Is New Customer`
  * `Variant Product Category`
* **Full Detail Forecast**
  * `Is New Customer`
  * `Variant Product Category`
  * `Variant Product Subcategory`

## Planned forecasts variances explore

![](https://2938842758-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5Oy2IAsu7IvAGAlWgC36%2Fuploads%2Fgit-blob-5dd829ee46a8f89a0307e561a75c77228ecc8f43%2Fplanned-forecasts-1.png?alt=media)

With this amplification, Performance brands now have the ability to log forecasts at different levels of detail and can have several different forecast versions (tracked via the `Forecast Version Name` in the amplification).

To correctly visualize the data and the variance metrics, you must first filter the explore by selecting one value for **Level Of Detail** and one for **Forecast Version Name** (both of these fields are under the group **Forecast Parameters**).

Once the filters are set, you can drag and drop the desired dimensions and metrics.


---

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