# Retail: Connect what was sold to what was promoted.

Retail knows what was sold. Marketing knows what was promoted. Random Truffle connects the two, by SKU, category, brand and customer.

## What matters

Retail decisions happen at the level of the SKU and the category, while campaigns are planned by brand and season. The value is in seeing both together.

- SKU, category and brand
- Affinity and repeat purchase
- Margin, when it exists
- Sales related to campaigns

## Questions you can ask

- Which campaigns are associated with sales for this brand?
- Which customers stopped buying this category?
- Which audience is most relevant for this SKU?
- Which creative performs best by product category?

## Data that becomes useful

- POS and ecommerce transactions
- Catalog, SKUs and categories
- Customer and identity, where available
- Promotions, campaigns and assets

Store purchases only link to a customer when there is a loyalty or account identifier. The rest is analyzed in aggregate.

## What the agents can do

1. **Understand (Nexus):** Analyze sales and campaigns by category and SKU, and find where repeat buying fell.
2. **Define (Aura):** Select the segment with affinity for the category and the criteria that justify it.
3. **Create (Prism):** Adapt pieces per SKU from the catalog and brand rules, for review.
4. **Activate (Radian):** Prepare distribution across paid and owned channels.
5. **Learn (Shared system):** Compare sales, and margin where it exists, against the plan.

## How learning closes the loop

Sales associated with a campaign are not the same as incremental sales. When the question is incrementality, the plan includes a measurement design (a holdout or a comparable control) before launch.

- Sales by SKU and category
- Repeat purchase in the segment
- Margin, when available
- Creative response by category

## An example conversation

> **You:** Which categories lost repeat buyers this month?
>
> **Nexus:** The decline is concentrated in two categories: running footwear and accessories. I can compare purchase frequency and recent promotions before treating either as a cause.

*Illustrative conversation with a fictional brand. Not a transcript or a client result.*

## Start with the category that changed.

Explore the evidence behind a drop in repeat buying.

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Source: https://randomtruffle.com/solutions/retail