Data Explained
How Trusted Tourism Analytics Data Improves Site Selection
Finding Locations That Win: How AmRest Expands in Germany with Targomo
AmRest, a leading multi-brand franchisee operator, uses Targomo’s location intelligence software for restaurant site selection, store network planning, and site evaluation in Germany.
By combining data-driven insights with prediction modelling, AmRest has improved its ability to estimate performance, align internal stakeholders, and expand with precision.
About AmRest
AmRest is one of Europe’s largest restaurant operators, managing an extensive portfolio of globally known food and coffee brands. With a presence across 22 countries worldwide, AmRest combines scale, expertise, and market knowledge to support growth across its brands. In Germany, the company acts as a franchise partner, running and expanding well-known brands like Starbucks and KFC, supporting franchise site selection in busy urban areas.
The Challenge: Expanding in Competitive Urban Environments
AmRest faces the complex challenge of selecting the best-performing locations across high-demand urban markets. Most locations are in the city centers and busy pedestrian zones, where even small differences in foot traffic patterns, tourism visits, and the surrounding environment can significantly impact a site’s outcome, making location quality a key driver of success.
“With some of our brands, like Starbucks you don’t plan your visit so long before… It is more of a spontaneous decision. Therefore, you have to be where the people are,” said Thorsten Eiber, who manages location strategy at AmRest Germany.
Thorsten Eiber
Senior Market Planner at AmRest
AmRest has always used innovative tools for data collection and continuously seeks the newest and most effective solutions on the market to successfully drive business growth, which led them to Targomo. “We’ve always done market drives. But relying on just what you see during a rainy Tuesday visit can be misleading. When you look at the data across the whole year, you get the full picture, and that’s something Targomo helps us prove,” said Thorsten.
The Solution: A Holistic Approach to Restaurant Site Selection
AmRest adopted TargomoLOOP as its primary location intelligence software for site evaluation in Germany. The company uses the platform as the first step to quickly assess a location and benchmark it against others, both for potential new sites and existing ones. TargomoLOOP provides structured insights into key drivers such as foot traffic data, footfall patterns, consumer demographics, the surrounding context of a location, and more.
“For our concepts, foot traffic matters. But we learned it’s not just the number of people. It’s who they are, when they’re there, and what else surrounds them,” said Thorsten.
In parallel, AmRest is working with Targomo to calibrate a GeoAI prediction model within the platform. By combining historic store performance data with location data, the model helps identify the drivers that best predict a restaurant’s performance. The model is tested and validated against existing locations first, helping the team check accuracy, analyse outliers, and improve reliability before applying it more broadly to future site decisions.
The prediction model is described as promising, though still being improved, especially because many restaurant sites differ significantly in size, layout, and context, making performance harder to predict than standardized restaurant formats.
Rather than treating Targomo’s outputs as a final answer, AmRest uses them as the starting point for a deeper assessment. The team compares the platform’s insights with internal site performance data and other sources, and then draws conclusions based on real-world context and experience.
“We don’t take the numbers black and white 100%… The tool is the first step for us to understand the location. And then, outside of TargomoLOOP we fine-tune our decision,” said Thorsten.
Results & Takeaways: A Smarter Expansion Strategy
While AmRest continues to refine its models, the benefits of Targomo’s tools are already clear:
- A stronger first step for evaluating and comparing locations, using one consistent framework across different cities;
- Better validation of on-site impressions, supported by reliable pedestrian and location context data;
- More structured benchmarking of high- and low-performing sites, helping identify what truly drives performance;
- Clearer internal discussions through live, visual analysis, improving team alignment during site evaluations;
- Earlier identification of unstable footfall patterns, such as locations driven by short peaks or seasons instead of consistent traffic;
- More confident decision-making by combining TargomoLOOP insights with internal performance data, rather than relying on a single source.
Among the reasons AmRest chose Targomo was the collaborative partnership: the platform continues evolving through shared learnings, improving both the data and the workflows that support expansion decisions.
“It’s not that we bought a tool and that’s it. We develop it further together. That was really what convinced us,” said Thorsten.
Today, Targomo is an integral part of AmRest’s location planning workflow in Germany. Whether evaluating high-street sites, understanding trade areas, or challenging assumptions with data, AmRest now has a more consistent way to assess opportunities and support site decisions with greater clarity.
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