---
title: How Tirlán planned the Cream category for 2026
seo_title: Tirlán case study | Pricing, promotions and switching in Cream | Advise
description: Tirlán used Advise to understand competitor growth in Cream, set RSP strategy around a price increase, and build a 2026 promo plan that avoids cannibalisation.
slug: /customers/tirlan
template: case-study
date: 2025-12-16
category: Customer story
client: Tirlán
logo: tirlan
glance:
  - [Client, "Tirlán, the farmer-owned Irish dairy and nutrition co-operative"]
  - [Category, Cream]
  - [Challenge, Competitor growth ahead of an October 2025 price increase]
  - [Advise modules, "Category Intelligence, Revenue Growth Management"]
  - [Customer since, "2024"]
cta_primary: { label: Book a demo, href: "/demo" }
cta_secondary: { label: See Core, href: "/core" }
schema: Article
tags: [customers, core, rgm]
---

# How Tirlán planned the Cream category for 2026

**Pricing, promotions and switching, answered from one view instead of weeks of Excel models.**

Tirlán's category team needed to understand why competitors were growing in Cream, and to get a price increase and a full year of promotions right. With Advise, they answered each of those questions from the same harmonised data, across every retailer.

## The challenge

Competitors were growing in the Cream category, and Tirlán had a price increase planned for October 2025. The team needed to know three things before committing to it:

- where retail selling prices were heading, and how the increase would land against competitors
- which promotion mechanics were working, and which were only moving volume between Tirlán's own products
- where shoppers would switch if prices moved, and where availability gaps were costing sales

Answering those questions the usual way means pulling EPOS files from each retailer, recoding them, and building a separate Excel model for each question. That takes weeks, and by then the plan is already late.

## What Tirlán did in Advise

- **Retail selling prices:** RSP trends by retailer and competitor, to set the pricing strategy on performance data rather than assumptions
- **Promotion mechanics:** which mechanics drove incremental sales across retailers, and where promotions were cannibalising Tirlán's own range
- **Switching:** switching patterns between brands and pack sizes, to see where share was at risk and how to protect it
- **Availability:** gaps in distribution across retailers, so lost sales could be found and recovered

Every analysis ran on the same coded, harmonised data, so the pricing, promotion and switching answers all agreed with each other.

## The results

- **An RSP strategy informed by performance data**, going into the October 2025 price increase
- **A 2026 promotion calendar optimised to avoid cannibalisation** across Tirlán's own range
- **Market share protected** with detailed switching models, so the team knew where shoppers would go and how to hold them

> "To produce that detail with third-party EPOS data, you'd be looking at around an hour. With Advise, it's literally a few clicks and you're there."
> Category Manager, Tirlán

## Plan your category the same way

See Advise in its full glory in a 30-minute demo.

[Book a demo](/demo) · [Read more customer stories](/customers)