Magnum drives 30% incremental sales after blending weather and retail data

BUSINESS OBJECTIVE 

Generating demand in Germany’s competitive ice cream market

The Magnum Ice Cream Company’s premium brand, Magnum, has been delighting German consumers for more than 35 years. In today’s seasonal and competitive ice cream market, the challenge is no longer just about visibility — it’s about ensuring that marketing investment drives incremental demand and efficiency. 

Even during warm weather, ice cream sales were lagging in certain regions, highlighting the need for a more precise marketing approach. Building on a previous successful U.K.-based campaign pilot for ice cream brand, Cornetto, the media buying team knew that combining retail data with weather signals could deliver similar outcomes for the German market. 

For its summer campaign, the brand worked with media agency PHD Germany and Omnicom Media Germany’s data division, Annalect, to sharpen its media strategy. Rather than simply advertising more during summer months, Magnum wanted to spark demand in regions with favourable weather but where ice cream sales remained low. 

This objective called for a highly customised strategy built around three key elements: retail data, weather forecasts, and a custom performance metric. The media buying team turned to The Trade Desk for our technical ability to support and optimise a bespoke strategy at scale.

SOLUTION 

Blending retail and weather data to gain predictive sales insights

The media buying team partnered with REWE, one of Germany’s largest supermarket chains. The retailer provided indexed product-level sales data by region for targeting. This level of detail is rarely available to brands in Germany and represented a breakthrough in retail collaboration. 

The customised strategy was built around three key components: 

• Retail data: REWE and Annalect indexed REWE’s data, using its average Magnum sales as the baseline. Then, each zip/postcode’s sales were calculated relative to that baseline, creating a demand index for each geo-segment. Each week, REWE shared updated indexed zip/​postcode lists with Annalect, enabling dynamic prioritisation across 434 geo-segments. 

• Weather data: Annalect integrated temperature and precipitation forecasts with the indexed retail data and used the combined inputs to model ice cream demand for each region. Higher temperatures would hopefully make consumers more prone to shop for the sweet treat. 

• Custom metric: Annalect created a custom key performance indicator (KPI) that combined weather forecasts, retail demand, and media efficiency. The KPI favoured cost-efficient inventory while ensuring media spend targeted areas with favourable weather and strong sales potential. 

Annalect translated the indexed zip/​postcode data and weather forecasts into bid lists. The lists were ingested via an existing application programming interface (API) integration that automatically recalculated regional KPIs and reallocated media budget to high-priority areas. The KPI and demand index were recalculated weekly, ensuring that prioritisation adapted to changing sales patterns and weather conditions. Our platform optimised performance by controlling volume and enhancing bid factors, automating data‑driven adjustments and removing the need for manual inventory changes. 

The team also used our platform to continuously track and optimise the campaign’s cost per thousand impressions (CPMs). The ads were primarily served across connected TV (CTV), online video (OLV), and digital out-of-home (DOOH) within REWE stores. They dynamically delivered across regions where the sun was shining, but demand was low — prioritising consumers when the conditions were just right. 

RESULTS 

Delivering efficiency and sales growth in prioritised regions

By continuously reallocating budget on our platform, the algorithm directed 65% more investment into prioritised regions. The impact was strongest in these geo-segments, confirming that the model successfully stimulated demand in regions where the potential was highest. 

The dynamic budget allocation also proved to be well-balanced, delivering cost-effective results for Magnum and other brands of The Magnum Ice Cream Company available in REWE stores across Germany. This approach helped ensure that bid adjustments were data-driven and automated. 

Results included: 

• 30% incremental sales in prioritised geo-segments, with 65% improved cost-efficiency compared to non-optimised campaigns 

• 19% lift in overall demand for ice cream across all regions 

• 8% uplift in Magnum sales across all stores 

• 9% increase in all company ice cream brand sales in Germany during the campaign 

Beyond the numbers, the campaign highlighted how retail insights, when combined with other real-world elements like weather forecasts, can transform fast-moving CPG advertising. 

Learn how you can leverage brand and regional data to optimise campaigns in real time. Contact us or reach out to your account manager at The Trade Desk today.