G-Star

G-Star is a major player in the global fashion industry, generating substantial revenue through both physical retail and a rapidly growing e-commerce business. Operating in a highly competitive market, the brand invests significant amounts in paid media to drive growth across markets and channels.

G-Star’s main challenge was the lack of a robust way to measure true media ROI across all channels. This made it difficult to understand the incremental impact of media investments and to distinguish between short-term performance effects and long-term brand growth.

Moreover, in a constantly evolving media landscape with new channels continuously being added to the marketing mix, G-Star required a solution that could deliver real-time, high-frequency ROI insights.

Based on a thorough briefing and explorative design phase, we helped G-Star develop granular MMM models across all 14 global markets.

An essential part of the initial phase of the project was focused on how to structure the media data in an optimal way, namely in relation to the split between channels and product categories. This is an important step in the design of an MMM setup, on the road towards succesful implementation.

Before implementation in the broader organization, we ensured a deep and aligned understanding of all business drivers in the models, with a specific focus on marketing channels, media ROIs and brand effects.

Furthermore, and in order to futureproof the setup, we helped G-Star establish data pipelines into the Alviss platform, to make data flow in an automated way to enable frequent updating of the ROI results.

With a global and dynamic MMM setup in place, G-Star can now allocate marketing spend more efficiently across markets, media channels and product groups. At the same time, decision-making is better balanced between tactical and brand-oriented communication, which is an essential capability for driving both short-term performance and long-term growth.