> For the complete documentation index, see [llms.txt](https://help.modelreef.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.modelreef.io/use-cases/consumer-goods-fmcg-and-cpg-manufacturers/retailer-channel-margin-modelling.md).

# Retailer/Channel Margin Modelling

{% hint style="info" %}
Model Reef is not a CRM or TPM platform. It models the commercial economics of retailers and channels using structured drivers and variables.
{% endhint %}

## Retailer and Channel Margin Modelling

This guide explains how to model retailer, channel and customer margins for consumer goods, FMCG and CPG manufacturers in Model Reef.

You will:

* Represent retailers, channels and key customers in the branch structure.
* Combine SKU level cost and price with channel specific terms.
* Model discounts, rebates, logistics and trade spend by channel.
* Produce margin views by retailer, channel, region and portfolio.
* Use scenarios to test commercial strategies and mix shifts.

***

### When to use this pattern

Use this pattern when:

* You sell to multiple retailers, channels or regions with different terms.
* You need margin visibility beyond aggregate COGS.
* You want to understand which channels and customers create or destroy value.
* You need scenario driven commercial strategy tools.

It builds on:

* SKU Manufacturing Cost Model
* Promotional Lift and Discount Impact
* Multi Channel Revenue Forecasting style patterns
* New Product Launch Forecast

***

### Architecture overview

{% stepper %}
{% step %}

### Structure

* Branches for retailers, channels and key customers.
* Sub branches for categories and SKU groups.
  {% endstep %}

{% step %}

### Commercial terms

* List prices and net prices.
* Discounts, rebates and trade spend.
* Logistics costs, freight and handling.
* Service level and support costs.
  {% endstep %}

{% step %}

### Margin outputs

* Net revenue per channel, retailer and SKU.
* Fully loaded margin after COGS, logistics and trade spend.
* Contribution by channel and portfolio.
  {% endstep %}
  {% endstepper %}

***

{% stepper %}
{% step %}

### Define retailer, channel and customer branches

In the branch tree, structure commercial branches such as:

* Commercial Group
  * Channel - Grocery
    * Retailer - Retailer A
    * Retailer - Retailer B
  * Channel - Convenience
  * Channel - Online Direct
  * Channel - Foodservice

Under each retailer or channel, you can create SKU group or category branches, or simply use variable naming and categories to distinguish SKUs.

Ensure this structure can be reconciled with your internal sales and margin reporting.
{% endstep %}

{% step %}

### Attach prices and commercial terms

In the Data Library, create drivers for each SKU, retailer and channel such as:

* List Price per Unit or per case.
* Off Invoice Discount Percentage.
* Invoice Price per Unit.
* Promotional Discount patterns where you combine this with promotional modelling.
* Volume Based Rebates and Year End Bonuses.
* Scan or activity based allowances where applicable.

Create Revenue variables at the appropriate level, for example:

* Revenue - SKU X - Retailer A.
* Revenue - Category Y - Online Direct.

Use formulas such as:

* Gross List Revenue = Volume × List Price.
* Invoice Revenue = Volume × Invoice Price.
* Rebates and Allowances = Volume × Rebate per Unit plus fixed amounts.
* Net Revenue = Invoice Revenue minus Rebates and Allowances.

This gives you a gross to net waterfall at retailer and channel level.
{% endstep %}

{% step %}

### Model logistics, freight and service costs

Create Opex and COGS variables for channel specific costs, for example:

* COGS - Logistics - Grocery Channel.
* Opex - Merchandising and Field Sales - Retailer A.
* Opex - E Commerce Fulfilment - Online Direct.

Attach drivers such as:

* Cost per Case or per Unit moved.
* Cost per Delivery or per Order.
* Merchandising hours and wage rates.
* Field sales team size and travel costs allocated by retailer or channel.

Compute these costs using the same volume drivers used for revenue so that:

* Logistics cost reflects actual and forecast throughput.
* Service cost reflects actual effort required per channel or retailer.
  {% endstep %}

{% step %}

### Link SKU cost, trade spend and channels for full margin

Combine this pattern with SKU Manufacturing Cost Model and Promotional Lift and Discount Impact by ensuring that:

* SKU cost per unit is available for every SKU in each channel.
* Trade spend and promotional costs are allocated to the relevant retailer and channel.
* Logistics and service costs are included to derive fully loaded margin.

Use custom reports and dashboards to show margin by:

* Retailer and channel.
* Category and SKU group.
* Region and territory.
* Portfolio and customer segment.

You can then answer questions such as:

* Which retailers and channels generate the highest contribution per unit?
* Which product and channel combinations are margin dilutive?
* What is the impact of mix shifts across retailers and channels?
  {% endstep %}

{% step %}

### Use scenarios for commercial strategy and mix shifts

Clone the base model into scenario models to test:

* Price increases or decreases by retailer and channel.
* Changing trade spend and promotional intensity.
* Shifts in mix across retailers, channels and regions.
* Logistics network and service model changes.
* Customer rationalisation or portfolio focus strategies.

In each scenario, adjust:

* Price and trade term drivers.
* Promotional calendars and depth.
* Volume and mix drivers.
* Logistics and service cost drivers.

Compare scenarios using:

* Net revenue and fully loaded margin by retailer and channel.
* Contribution margin at category and portfolio level.
* Cashflow and working capital implications including receivables and inventory.
* Valuation impact where channel strategy materially changes future cashflows.
  {% endstep %}
  {% endstepper %}

***

### Check your work

* Commercial terms match actual contracts or current trading conditions.
* Logistics and service cost drivers reflect how cost is actually incurred.
* Gross to net waterfalls reconcile to historic margin analysis.
* Scenario outcomes are realistic and actionable for sales and finance teams.

***

### Troubleshooting

<details>

<summary><strong>Margin appears inconsistent with historical reports</strong></summary>

Check that all trade spend, logistics and service costs have been captured and that they are allocated at the same level of granularity used in your reporting.

</details>

<details>

<summary><strong>Difficult to manage many SKUs and customers</strong></summary>

Aggregate SKUs into families and group smaller customers where appropriate, focusing detail on key customers and channels.

</details>

<details>

<summary><strong>Complexity makes scenario comparison hard</strong></summary>

Use a small set of key scenarios and rely on dashboards and charts that summarise contribution at retailer, channel and portfolio level.

</details>

***

### Related guides

* [Build a Rolling Forecast](/how-tos/scenarios-and-planning/build-a-rolling-forecast.md)
* [Build a Seasonality Adjusted Forecast](/how-tos/scenarios-and-planning/build-a-seasonality-adjusted-forecast.md)
* [Updating API Based Data](/help/importing-from-google-finance-and-yahoo-apis/updating-api-based-data.md)
* [Overriding Variables](/syntax/scenario-syntax/overriding-variables.md)


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