> For the complete documentation index, see [llms.txt](https://learn.moselle.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://learn.moselle.io/planning-and-execution/forecasting/phase-1-understand-forecasting/sell-in-vs-sell-through.md).

# Sell-In vs. Sell-Through

Learn why Moselle forecasts from sell-in, how Mo folds your retailer sell-through data into that forecast, and the two steps you need to set it up today.

{% hint style="info" %}
**Quick Answer:** Moselle forecasts from **sell-in** because it best predicts when retailer orders arrive and when revenue lands. Mo then folds your **sell-through** data on top of that forecast, following your forecast guidelines. To turn this on, make your sell-through data readable by Moselle and tell Mo where to find it in your Forecast Guidelines.
{% endhint %}

## What Is the Difference?

When brands sell through retail partners, there are two distinct points at which a "sale" is recorded:

**Sell-In** : When the brand ships product to the retailer. This reflects purchase orders (POs) placed by the retailer and is owned by the brand.

**Sell-Through** : When the retailer sells that product to the end consumer. This reflects actual point-of-sale (POS) transactions and is owned by the retailer (e.g., Sephora, Ulta Beauty).

These two numbers are often very different. Sell-through shows true consumer demand. Sell-in shows when retailers actually buy from you — and that is what drives your shipments, your revenue, and your cash.

|                                   | Sell-In                                                                                              | Sell-Through                                                                                                                           |
| --------------------------------- | ---------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------- |
| **Measures**                      | Brand shipments to retailer                                                                          | Consumer purchases at retail                                                                                                           |
| **Data Owner**                    | Brand                                                                                                | Retailer                                                                                                                               |
| **Timing**                        | Matches when retailer buys and revenue happen                                                        | Reflects real-time consumer demand                                                                                                     |
| **Common Source**                 | ERP sales orders, wholesale order log, wholesale ordering platforms, EDI (e.g., SPS Commerce, Crstl) | Retailer analytics, usually emailed as a spreadsheet or downloaded from a vendor portal (e.g., Sephora Brand Portal, Ulta Partner Hub) |
| **Role in Your Moselle Forecast** | The foundation the forecast is built on                                                              | A demand signal Mo folds in on top                                                                                                     |

***

## Why Does Moselle Forecast from Sell-In?

**Sell-in is the more accurate basis for a forecast** because it lines up with the events you actually plan around:

* **When buys come in** — Retailers place orders on their own replenishment cycles. Sell-in captures that timing; sell-through does not.
* **When revenue happens** — You recognize revenue when the retailer's PO ships, not when a shopper checks out.
* **What's final** — Retailers don't return unsold inventory. Once product ships, the sale is booked.
* **What you need to produce and ship** — Replenishment, production, and cash plans all depend on when product leaves your warehouse, so a sell-in forecast keeps supply planning accurate.

### Example: Why a Sell-Through Forecast Can Mislead You

Say consumers buy **1,000 units a month** of your product at two retailers through Q4. On a sell-through basis, Q4 looks strong.

But both retailers went into Q4 already holding plenty of stock, so they don't reorder. You book **almost no revenue in Q4**. Then, in February, their shelves run low and they place one **large, lumpy reorder**.

A sell-through forecast would have shown Q4 revenue and cash that never arrived, and missed the February spike your supply plan needed to cover. A sell-in forecast shows both correctly.

Sell-through still matters. It tells you whether retailer inventory is moving, so you can see a reorder coming (or slowing down) before it shows up in sell-in. That's why Moselle starts with sell-in and then uses sell-through to adjust.

## How Does Mo Fold Sell-Through Into Your Forecast?

Your forecast is built in two layers:

{% stepper %}
{% step %}

### Moselle builds a sell-in forecast

Moselle's forecasting engine reads your sell-in history and produces a **directional forecast** — a baseline projection of what retailers will order and when.
{% endstep %}

{% step %}

### Mo reads your Forecast Guidelines

Every time a forecast is created or refined — top-down or bottom-up — Mo reads your saved [Forecast Guidelines](/planning-and-execution/forecasting/phase-3-refine-and-maintain/setting-up-forecast-guidelines.md). Your guidelines tell Mo where to find your sell-through (a dashboard or the raw data) and how you want it used.
{% endstep %}

{% step %}

### Mo adjusts the forecast with sell-through

Mo looks up your sell-through data and folds it in on top of the sell-in forecast — for example, raising projections for SKUs that are selling through faster than retailers are reordering, or lowering them where retailer stock is building up.

**Expected Result:** A forecast that keeps the timing accuracy of sell-in and reflects real consumer demand from sell-through. Once it's in your guidelines, this step runs automatically on every forecast.
{% endstep %}
{% endstepper %}

{% hint style="warning" %}
**Mo only folds in sell-through when your guidelines tell it to.** Without the two steps below, your forecast is based on sell-in alone.
{% endhint %}

***

## How Do I Get Sell-Through Folded Into My Forecast?

**Time Required:** 15–30 minutes (one-time setup) **Difficulty:** Beginner

### Required Steps

{% stepper %}
{% step %}

### Make your sell-through data readable by Moselle

Mo can only use sell-through data that Moselle can read. Pick whichever option matches where your data lives today:

| Where Your Sell-Through Data Lives        | How to Connect It                                                                                                                                                             |
| ----------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **A spreadsheet you maintain**            | Connect it with the [Google Sheets integration](/getting-started/onboarding/setup-integrations/google-sheets.md)                                                              |
| **Your BI tool, data warehouse, or ERP**  | Connect the source through [Integrations](/getting-started/onboarding/setup-integrations.md), or ask your Customer Success Manager to set up the connection                   |
| **Spreadsheets your retailers email you** | Forward them to your Moselle data address and Moselle handles the ingestion (see [How to Submit Sell-Through Data by Email](#how-to-submit-sell-through-data-by-email) below) |
| **A retailer vendor portal**              | Download the reports and consolidate them in one place, such as a single Google Sheet, so Mo reads from one source                                                            |

{% hint style="info" %}
Not sure which option fits? Tell your Customer Success Manager where your sell-through data lives — that's all we need to know to get it connected.
{% endhint %}

**Expected Result:** You can ask Mo "Show me my sell-through by retailer for the last 4 weeks" and it returns your data.
{% endstep %}

{% step %}

### Add sell-through instructions to your Forecast Guidelines

Open Mo, click the three-dot menu **(⋮)**, choose **Settings**, and add a sell-through section to the **Forecast Guidelines** field. Tell Mo:

1. **Where to find your sell-through data** — your sell-in vs. sell-through dashboard if you've built one, otherwise the raw data source (sheet, report, or connected system)
2. **Which retailers or SKUs it covers**
3. **How to fold it in** — for example, how much weight to give it and over what time window

{% hint style="info" %}
**Dashboard or raw data?** A dashboard gives Mo a consistent, pre-built view of sell-in next to sell-through, but you need to create it first (see [Recommended Steps](#recommended-optional-steps) below). Until you do, point Mo at the raw sell-through data.
{% endhint %}

**Example guideline (raw data):**

> Sell-through: Our weekly retailer POS data is in the "Retail Sell-Through" Google Sheet (tabs: Retailer A, Retailer B). After the sell-in forecast is generated, compare the last 8 weeks of sell-through to sell-in for each SKU at each retailer. Where sell-through is running ahead of sell-in, raise the next 3 months of sell-in forecast to close the gap. Where sell-through is running behind, lower it. Flag any SKU where the adjustment is more than 25%.

**Example guideline (dashboard):**

> Sell-through: Use the "Sell-In vs. Sell-Through" report to compare sell-in and sell-through by SKU and retailer. Apply the same adjustment rules as above.

Because guidelines are saved, Mo applies this automatically every time a forecast is created, top-down or bottom-up — you don't need to repeat it in each chat.

{% content-ref url="/pages/a4VaHeybGOn75f976xpb" %}
[Setting Up Forecast Guidelines](/planning-and-execution/forecasting/phase-3-refine-and-maintain/setting-up-forecast-guidelines.md)
{% endcontent-ref %}
{% endstep %}
{% endstepper %}

### Recommended (Optional) Steps

These aren't required, but they make it much easier to trust and review how sell-through shapes your forecast.

{% tabs %}
{% tab title="Sell-In vs. Sell-Through Dashboard" %}
Build a dashboard in **Explore** that puts sell-in and sell-through side by side. Once it exists, you can point your Forecast Guidelines at it instead of the raw data.

1. Click **Explore** in the left sidebar (or **Explore & Build** on the Reports page)
2. Describe what you want, for example: *"Weekly sell-in vs. sell-through by retailer and SKU for the last 26 weeks, with a gap column"*
3. Refine the charts and tables, then save it to your Reports

Use it to spot where retailer stock is building up or running low before it affects reorders. Give it a clear name (e.g., "Sell-In vs. Sell-Through") so your guidelines can reference it.

{% content-ref url="/pages/2fZ00LMDTKttlNbQLGFs" %}
[Explore](/analytics/explore.md)
{% endcontent-ref %}
{% endtab %}

{% tab title="Weekly Forecast Audit Workflow" %}
Set up a Mo workflow that audits your forecast every week.

1. Open **Workflows** from the Mo section
2. Ask Mo to build a workflow, for example: *"Every Monday, audit the forecast. Compare last week's forecast to actuals and flag misses. For retail channels, compare sell-in to sell-through by retailer and SKU. Explain how you folded sell-through into the sell-in forecast — which SKUs changed, by how much, and why — and confirm sell-in was booked correctly."*
3. Review the draft, then save and schedule it to run **weekly**

Each run gives planners one clear view: whether targets were hit, whether sell-through was factored in, and whether sell-in was booked correctly.

{% content-ref url="/pages/7FLZX0v9oQDFklfnHl1b" %}
[Mo Workflows & Templates](/mo/key-capabilities/mo-workflows.md)
{% endcontent-ref %}
{% endtab %}
{% endtabs %}

***

## Updating Sell-In Data

Sell-in usually comes from your ERP's sales orders. Smaller brands often keep a wholesale order log instead, and some brands receive retailer orders through a wholesale ordering platform or an EDI provider such as SPS Commerce or Crstl. If your source is connected through [Integrations](/getting-started/onboarding/setup-integrations.md), sell-in updates automatically. Otherwise, update it through the **Data Room**.

{% content-ref url="/pages/LbJu5JdXTAddmFeLGbt2" %}
[How do I Upload Sales Data to Moselle?](/getting-started/onboarding/manual-data-uploads/how-to-upload-sales-data.md)
{% endcontent-ref %}

***

## How to Submit Sell-Through Data by Email

If your sell-through data comes as weekly retailer POS reports, you can email them directly to Moselle. Once processed, Mo can answer questions about your sell-through performance and fold it into your forecast (as long as your Forecast Guidelines tell it to).

**Time Required:** 2 minutes per submission **Processing Time:** Up to 1 business day

{% stepper %}
{% step %}

### Download Your Weekly Report

Log into your retailer's vendor portal and download your weekly POS or sell-through report.

* **Sephora** — Available via the Sephora Brand Portal
* **Ulta Beauty** — Available via Ulta Partner Hub
* Other retailers — Download from your assigned vendor portal

Accepted formats: Excel (.xlsx) or CSV
{% endstep %}

{% step %}

### Email the File to Moselle

Send the report as an attachment to your Moselle data email address. This address is unique to your account and follows the format:

**\[your-company].mail.moselle.io**

{% hint style="info" %}
Not sure what your address is? Contact your Customer Success Manager — they can confirm the exact email for your account.
{% endhint %}

{% hint style="warning" %}
**Do not leave the subject line blank.** A clear subject line is required for the system to route and process your file correctly.
{% endhint %}
{% endstep %}

{% step %}

### Use a Clear Subject Line

Your subject line must include:

1. **The retailer name**
2. **What the data represents** (report type, week, region, or other identifier)

**Examples:**

* `Sephora Best Seller Week 30`
* `Ulta USA Weekly Sales`
* `Nordstrom POS Data June`

The more specific your subject line, the faster and more accurately the system can process your file.
{% endstep %}

{% step %}

### Wait for Processing

Moselle will process your file within **1 business day**. You do not need to take any action during this time.
{% endstep %}

{% step %}

### Ask Mo for Your Sell-Through Data

Once your file has been processed, open Mo and ask about your sell-through performance. Mo will have access to the updated data and can answer questions like:

* "What are my top-selling SKUs at Ulta this week?"
* "Show me my sell-through rate at Sephora for the last 4 weeks"
* "Which stores are underperforming on \[product]?"

{% hint style="success" %}
Mo will let you know if it cannot find data — in that case, check that your email was sent with a clear subject line and allow up to 1 business day for processing.
{% endhint %}
{% endstep %}
{% endstepper %}

***

## Frequently Asked Questions

<details>

<summary>Why doesn't Moselle forecast directly from sell-through?</summary>

Sell-through shows true consumer demand, but it doesn't tell you when retailers will place orders or when you'll book revenue. Forecasting from sell-in keeps those dates accurate; Mo then uses sell-through to adjust the volumes.

</details>

<details>

<summary>My forecast doesn't seem to reflect sell-through. What should I check?</summary>

1. Ask Mo to show your recent sell-through data. If it can't find it, the data isn't readable yet — revisit Step 1.
2. Open Mo > ⋮ > **Settings** and confirm your **Forecast Guidelines** say where your sell-through data lives and how to use it.
3. Ask Mo to explain how it applied sell-through to a specific SKU.

</details>

<details>

<summary>What happens if my subject line isn't clear enough?</summary>

The system uses the subject line to identify the retailer and data type. A vague or missing subject line may cause processing delays or errors. If your data doesn't appear within 1 business day, re-send the email with a clearer subject line (e.g., "Ulta USA Weekly Sales Week 32").

</details>

<details>

<summary>How often should I submit Sell-Through data?</summary>

Most retail partners (Sephora, Ulta) provide POS data on a weekly basis. We recommend a weekly cadence so Mo has the most recent demand signal available when it adjusts your forecast.

</details>

<details>

<summary>My retailer uses different SKU codes than my internal system. Will Moselle handle that?</summary>

Yes. Moselle supports SKU mapping between retailer item numbers and your internal SKUs/UPCs. This is configured during onboarding. Reach out to your Customer Success Manager if you need to update or add mappings.

</details>

<details>

<summary>What is a healthy sell-through rate?</summary>

This varies by category, channel, and product lifecycle stage. As a general benchmark, a sell-through rate of 80% or above is considered healthy in most beauty and personal care categories. Your Customer Success Manager can help you interpret your sell-through data in context.

</details>