The location of a property is one of the most important criteria for apartment hunters. The distance to the next supermarket or the connection to public transport can decide whether someone decides for or against a property.

The German real estate portal Immowelt now offers a location check that generates ratings for every listing. The new feature is based on Targomo’s Location Scoring API and allows visitors to Immowelt to assess public transit quality and “daily needs” access.

“The Immowelt location check is a real and tangible added value for searchers on immowelt.de,” says Felix Kusch, Immowelt Country Managing Director. “Anyone who can assess the location of a property at a glance saves valuable time in the search for a suitable apartment or house. In the test phase, users were already enthusiastic about this practical function.”

The Immowelt Location Check is a benchmark for the attractiveness of a property’s location compared to all other property locations in the region. It is calculated based on the number and accessibility of relevant points. The “Daily Needs” score takes into account the extent to which grocery stores, drug stores, ATMs, pharmacies, etc. are reachable within the area. The score “Public Transit” takes into account the proximity and number of transit stops, the amount of transit lines and frequency of their services as well as the effectiveness of the transit network itself – how good is the network at connecting people across areas.

The result is presented on an easy-to-read, five-point scale: Super, Good, Okay, Moderate and Poor. For the future, Immowelt plans to expand the location check with two additional scores: Family-friendliness and leisure opportunities. These are intended to display information about kindergartens, playgrounds or sports facilities, among other things.

Targomo’s Location Scoring API enables the evaluation of locations by analyzing sociodemographic data and the accessibility of relevant places (points of interest) in the vicinity. The criteria according to which locations are evaluated can be set individually. “The high adaptability of the Location Scoring API was one reason, along with the speed and precision of the calculations, why we worked with Targomo to develop the Location Check,” says Felix Kusch.

“We enable real estate portals to provide their users with additional information that they would otherwise research on other websites,” says Henning Hollburg, Managing Director of Targomo. “This allows them to keep users on their own platform. They can customize the scores and tailor them to different countries, cultures or user types, for example. Even an individual weighting of the criteria by the user herself is theoretically possible – for example, a user could specify whether there should be many or few bars or restaurants in a neighborhood.”

About immowelt:

immowelt is part of AVIV Group, one of the largest digital real estate tech companies in the world.

immowelt’s mission is to digitize all steps of the real estate transaction in the future to make it as uncomplicated and easy as possible for all parties involved. The basis is provided by the wide-reaching immowelt portals, which are among the leading real estate platforms in Germany and Austria. They already successfully bring together owners, real estate professionals and seekers. immowelt supports the uncomplicated search for a rental property, the effective marketing of a property and customized financing of one’s home with data-supported services. Thanks to decades of experience and broad real estate expertise, immowelt thus creates the perfect success story for tenants and landlords, real estate professionals, property owners and buyers.

In addition to immowelt, other leading real estate online marketplaces in France, Belgium and Israel belong to the AVIV Group, which is part of Axel Springer SE.

With only a couple months into his new role as Business Developer, Dylann Joffard has already managed to make quite the impression at Targomo. Originally from the Parisian region of Seine-et-Marne, Dylann now lives in Berlin, Germany, where he’s brushing up on his German language skills. Currently, he’s reading a book on the topic of balanced working, which has only furthered his German comprehension.

With a BA in Geography and an MA in Urban Planning and Urban Policies, Dylann’s expertise in  the Geographic Information System (GIS) is undoubtedly a huge asset in terms of developing the French market for Targomo. Although he has yet to work on a larger-scale project, his career goals run the gamut—from identifying the markets who need GEO-AI location analytics to being able to forge solid relationships, he looks forward to helping successfully expand the company in France.

When asked about what advice he’d give to someone wanting to work in the field of business development, he says, “be curious and never be afraid of the ‘no.’” Understanding the why behind what problems someone is trying to solve is key, he explains. So if a prospective company ends up not being interested, it’s either because the company hasn’t identified a problem yet or you weren’t able to identify it. 

When he’s not busy growing the French market, you can find Dylann taking art photos. In fact, he had his first exhibition in Lyon, France, in early 2022. His goal? To express a message on a variety of topics (gender, racism, etc.) and work with inspiring people, no matter if they’re a professional or an amateur. 

As for his everyday motivation, it’s simple: for work, it’s about building trust with clients and meeting their needs. For his personal life, it’s being able to create and build relationships with people. 

Henning Hollburg, Targomo’s Founder and Managing Director, explains what predictive analytics is and how businesses with physical points of sales can benefit from it.

“Put simply, it’s the application of sophisticated machine learning algorithms to learn from the past and predict future scenarios.

We’ve been working on predictive analytics for years and now we can offer this innovative technology to all the businesses that need it. Enabling technologies have given the field a huge boost in recent years, from better hardware to more powerful models. In addition, the emergence of modern web technologies allows us to develop such solutions in a browser-based environment.”

“Location matters to all businesses that require physical interaction with their clients. It’s the reason why our models can predict as much as 80%-90% of the success of a retail chain branch. It also means that we can tell our clients, with this level of accuracy, what sales they can expect if they want to open a new store. This gives them tremendous planning certainty.

But the potential of the predictions goes beyond new openings. Changes in sales area, opening hours, store type, etc. can also be predicted. And not only for the changed store itself, but for the other stores in the network as well. For example, one customer of ours wants to know which location they should rebrand. Another is concerned with which products they should offer where.”

“At Targomo, it’s a three-stage process. First, the client provides us with their business data. We then train our model with that data, before integrating into TargomoLOOP a custom model for the client with predictions about their business expansion.

The clients’ business data comprises their store locations combined with a number of attributes, so called location-based data. It is typically store size and type, opening hours, last renovation and so on. Clients also provide us with their KPIs like overall revenue, revenue of a specific product, or number of visitors.

Then we analyse the surroundings of each store location to find patterns. Here mainly three types of data come into play: mobility related data like public transit schedules, road networks or movement data, socio-demographic data, and points of interest data. The patterns help us understand which factors cause success or failure. With these metrics/success factors we train a model. And this model allows us to forecast most KPI for given locations.”

“We integrate the model into TargomoLOOP, the intuitive browser-based tool we developed, and they can simply type in any address to see forecasts about revenues, number of visitors and other important considerations for store planning. Ultimately they will be able to understand if putting a store there will be successful or not. 

And the great thing is that our model isn’t just useful for retail expansion but also to understand if an existing store is over performing or underperforming. We simply check the business performance of existing stores against the predicted performance using our model. With these insights, the business can optimise its network. It can adapt pricing, product offering, store hours, to replicate success or avoid low performance.”

“Of course, the possibility stands and falls with the available data. For example, we sometimes saw that certain stores had lower sales due to renovation work and the resulting closures. They then first appeared in our analysis as underperformers because we had no information on the closures. The more internal data we receive from our client, the better.   

But, especially if only a few stores are available, it becomes difficult to identify patterns. Ideally, a network should consist of more than a few dozen stores to develop a meaningful model. In addition, there are also factors that influence performance for which we have no data or that have nothing to do with the location per se. For example, if the staff are particularly friendly and have built up a good customer relationship.”

Targomo has many years of experience in mobility and human movement analysis and have also done a lot of research in this direction. This expertise is incorporated into our analyses and predictions, as the success of stores depends crucially on human movement patterns: it’s all about people getting to businesses, and businesses getting to people. It’s the essential ingredient when looking at forecasting. 

Another advantage is that we integrate this prediction model, which is individually developed for the customer, into the analytics platform. This is quite easy to use, so all team members can access it without being a GIS expert or data scientist.

Thanks to Henning for the introduction to predictive analytics. Look out for more stories about this revolutionary technology on Targomo soon. 

Gustoso Group, one of the fastest growing branded restaurant operators in Germany, is supporting the expansion of business with new location intelligence technology from specialist Targomo. This is helping the company to efficiently identify the best locations for each of its restaurant brands Cotidiano, Ciao Bella, Ruff’s Burger and Otto’s Burger. With the help of the TargomoLOOP platform, the gastronomy specialists are able to quickly analyse the potential of a possible new location to assess whether it is suited to the target audiences of its various brands.

“We were immediately won over by Targomo. The interactive tool allows us to assess potential locations much more quickly and efficiently,” explains Andreas Reitz, Director Development & Expansion of Gustoso Group. Following a successful trial period, the restaurant professionals are now using TargomoLOOP in their day to day work. In addition to efficient data analysis of a location’s potential, based on its competitive situation, demographics, purchasing power and footfall, the platform also enables the structured evaluation of points of interest. These provide information about the area’s characteristics and visitor attractions, which makes it easier to assess the value of footfall for the company’s own business.

Andreas Reitz’s team uses TargomoLOOP to assess every possible new location and understand its respective potential for the various restaurant brands operated by the group. For example, a location that proves unsuitable for better burger player Ruff’s Burger might well be a good fit for Italian concept Ciao Bella. The varied requirement profiles of the group’s individual restaurant brands, along with key performance metrics from existing locations, have been stored in TargomoLOOP in a way that makes it easy for the gastronomy experts to work interactively with the platform. This allows them to assess the locations’ potential in real time via the user interface without the need to create reports.

With Targomo, the Gustoso Group can now drive efficiency into its processes. “Previously, we entered all relevant data into a huge Excel spreadsheet,” reports Stefanie Langhans, Senior Finance Manager at Gustoso Group, “but over time it became so complex that detailed analyses for each potential location became too time-consuming.” With TargomoLOOP, Gustoso Group can now carry out much more detailed analyses and ensure that it only visits properties whose locations are economically viable for one or more of its restaurant brands. “Leveraging the platform, we can minimise existing uncertainties when making location decisions,” Stefanie Langhans is pleased to say.

The fact that TargomoLOOP also allows to very precisely forecast possible cannibalisation effects of potential new locations on existing restaurants is highlighted by the managers of Gustoso Group as a particular advantage. But the gastronomy professionals have even more plans for the platform: In the future, TargomoLOOP will also actively suggest locations that are likely to replicate the success of strongly performing existing restaurants.

The managers of Gustoso Group are quick to praise the cooperation with the Targomo team: “These are smart people who bring great competence to the table. The strong cooperation is very valuable for us,” says Andreas Reitz. For example, joint workshops between the companies highlighted the roles of competition and points of interest, allowing the location search criteria to be optimised. For the Gustoso Group team, Targomo has provided great support in finding the best locations for the 14 new restaurants planned for this year and thus in pursuing its expansion strategy.

About Gustoso Group

The Gustoso Group is an innovative and fast-growing gastronomy company based in Munich. Since its founding in 2015, the group has grown through organic and inorganic growth to around 75 locations across Germany. The group includes the brands Ciao Bella, Cotidiano, Ruff’s Burger and Otto’s Burger. The company’s declared goal is to become one of the leading multi-brand restaurant platforms for the most innovative and successful gastronomic concepts in Europe.

With the rise in rapid grocery delivery, dark stores have emerged as fulfilment centres placed close to large populations for ultra-quick orders. But how are they different from supermarkets, how do you plan a dark store, and what does the future hold?

By 2023, e-commerce sales are expected to hit $6.5 trillion. That’s more than the GDP of Germany and India combined. In fact, in the five years between 2021 and 2026, e-commerce is expected to grow by 55% globally.

The world was always going this way, but the Covid pandemic certainly helped accelerate the change. According to Capgemini research, online sales in the UK surged 61.8% year-on-year during Covid, with Amazon sales in the UK up 81% in 2020 compared to the year before.

With such unprecedented change comes new opportunities and infrastructure to service these growing demands for near-instant delivery. One of those is the concept of the “dark store”, a term probably unfamiliar to most but which anyone who has ordered online will have had some touchpoint with.

Similar in layout to a supermarket, dark stores are brick-and-mortar warehouses laid out in aisles and stocked to the rafters with goods. But that’s where the similarities between the two ends.

Generally not open to the public, though some do act as click-and-collect centres, dark stores have emerged out of consumers’ unprecedented appetite for convenience and online shopping. Put in a quick commerce order, and the chances are it will be fulfilled at a dark store, and sent to you quite possibly the same day.

Another key difference between a supermarket, in the traditional sense, and a dark store are their catchment areas, and how that is defined. With a supermarket, its catchment area is estimated, because its customers can ebb and flow. In other words, the buyer goes to the seller, and they use many different forms of transport to get there, so accessible multi-modal transport routes have to be taken into consideration when defining the catchment area. Supermarkets are also situated to take advantage of passing trade, often near complementary businesses where customers can visit multiple shops from one area.

With dark stores, the opposite is true. The seller goes to the buyer, mostly fulfilled by a delivery agent who will bring the purchase to your home or business address. Because of this, the dark store can accurately determine what its catchment area is. This is defined by three elements: the dark store location (within the proximity of a wide range of potential customers), the type of transport used (mostly vehicles or e-bikes), and the promised delivery time.

Like supermarkets, location is crucial for dark stores. But while supermarkets have to take into consideration multi-modal transport and high foot traffic, for dark stores the data foundation when it comes to a decision for or against a location is different. It’s much more important to be placed strategically and geographically in order to service areas with high population densities and the right demographic profile, quickly. 

Space requirements can also be different.  Dark stores don’t have to lay out stores based on customer psychology. In a supermarket, for instance, fresh produce is placed near the front, and promotional items on the end of aisles. Instead, dark stores can maximise the space to their full advantage. For example, prioritising items that are frequently ordered by making them easier to reach and closer to the front of the store for even more efficient delivery.

As we know, close proximity to the customer base is key to fulfilling promises of speedy delivery. But with many micro-fulfilment zones placed in close proximity, there’s a danger of cannibalisation through overlapping delivery or fulfilment zones.

This is where location technology can help. With tools such as TargomoLoop you can really drill into the detail of your chosen area, from catchment size, to demographic data, allowing you to accurately pinpoint your potential market, creating zones that work in harmony with each other, and potentially avoid cannibalisation. 

A great example of this is Yababa, a grocery company that specialises in Turkish and Middle Eastern products. Using our powerful demographic location data, it was able to determine the optimum sites from which to service its unique customer base in Berlin, Cologne and Düsseldorf, Germany.

Our software can also allow you to optimise based on other demographic criteria, such as household size, purchasing power and consumer profiles. For instance, if you are targeting younger customers with higher incomes, you can find out where these people are in relation to your store, and how many you can deliver to within an allotted time.

In the restaurant industry, the concept of ‘Ghost kitchens’ has been around for a few years now. They allow restaurants or fast food outlets that don’t have a physical location with guest space, to service customers from kitchens with delivery-only or kerbside pick-up locations. The same principle is now appearing in other industries. Supermarket chain Kroger and tech platform Ocado have partnered to help Kroger expand into territories where it currently doesn’t have a presence, and without the need to create expensive public-friendly brick-and-mortar stores.

Then there’s the hybrid model, where online and offline sales merge under one roof. Alibaba has been trialling this concept in China with its smart supermarket Hema. Here, customers can browse physical products, scan them to purchase, have them delivered while they shop and even order food to be cooked and be ready for the end of their shopping trip.

Gorillas, an app-based delivery company with presence in Europe and the United States, uses Targomo to plan delivery zones and map fulfilment areas. Recently it added in-store pick-up as an option, reports the New York Post. At its 18 locations in New York, customers can now order online and pick-up in store at a time that suits them.

In Germany, supermarket chain REWE is doing something similar, introducing collection stations that are open 24/7 and allow people to pick up groceries that they have previously ordered on the app.

While e-commerce sales are booming, consumer demand for instant shopping gratification and the chance to connect more physically with their purchases means a hybrid model where we see the supermarket and dark store merge could be the next big revolution in the world of retail.

Discover how the power of location intelligence could help you plan your next retail location.

Location decisions are far-reaching and are rarely made alone. Various parties and hierarchies are usually involved. Therefore, a crucial part of the decision-making process is to share facts and insights about potential new locations with the relevant stakeholders.  That’s when location reports come into the game.

Our location analytics platform TargomoLOOP lets you create reports on locations and download them as PDFs. The location reports present the essential facts and analysis results about a site. They help share the analysis results with colleagues, supervisors and partners, and can be used for archiving purposes. 

We have now improved the functions and layout of the reports to make it more relevant and more pleasant to read so that you can communicate your findings even better. 

The first page provides an overview of the core information about the location. This includes the address, the rating within the location network and an overview of the selected catchment areas, which are also visualized in a map.

Targomo offers the possibility to make multimodal catchment analyses. This means that the analysis covers several catchment areas, each determined by a different mode of transport. TargomoLOOP offers, in addition to the modes of car, walking, cycling or public transport, the possibility to set the speeds individually, which is why additional modes of transport such as e-bike can also be mapped. 

On additional pages, the report contains the analysis results broken down for each individual catchment area. Here you will find details on the points of interest, the demographic and socio-economic characteristics of the area and other data points that were added to the analysis. 

Also customer specific data can be integrated. This can include past or estimated guest counts, orders, the size of the location or the number of employees.  

Would you like to see the analytics platform TargomoLOOP in action? Book your demo here.  

The old adage “by failing to prepare, you are preparing to fail” has never been more apt than when choosing your next retail location. With so many factors to consider, as well as the pandemic creating shifts in how people shop, and a host of other trends to take into consideration, doing your research is vital.

Start your research journey here, with the help of this list of mistakes to avoid when choosing a new retail location.

While it makes great economic sense to expand your bricks-and-mortar business into multiple locations, it’s important you watch out for ‘retail cannibalisation’.

In the first quarter of 2018, Starbucks – the popular coffee chain with a store on every corner – was suffering from market saturation. With so many stores available, and a burgeoning competitor market, its stock plummeted 11.38% at a time when the overall market was up 4.1%. As a result, it started shutting stores in the United States.

Of course, healthy competition is great for any business, but in the retail industry, cannibalisation occurs when branches of the same chain that are near each other end up competing with one another for the same business.

The same is also true of competitor businesses. If too many similar businesses are located in the same catchment area, customer loyalty and preference is going to favour one business over another. An oversupply of locations also leads to higher operational costs, as Starbucks found to its chagrin.

So before you decide for a location, check how your branches influence each other. A good technology solution lets users immediately see whether the new store would “steal” potential customers from existing shops in the same area and how many. They can also see how many customers they could potentially win from competing shops nearby, and how a competitor’s new location might impact the catchment area of their retail stores.

In 1920, American mathematician Harold Hotelling came up with a theory called Hotelling’s Model of Spatial Competition. His model shows that when competing for locations, every business wants the “central point” as it is the most strategic spot to be as close to as many customers as possible. But because every business has ultimately the same intention, stores become clustered around the same location and end up competing with one another.

Putting that theory into practice, Marc Smookler, a United States retail expert, conducted a study in Austin Texas in 2015. He concluded that CVS and Walgreens pharmacies were, on average, only 1.5kms apart, and Walmart and HEB (a grocery chain) were 1km apart.

So sometimes you’re drawn to an area because that’s where the market is. But you should also know who your competitors are, what they specialise in, what their USPs are and how your business is similar or different. And most of all: where they are located. Because this gives you the chance to identify “whitespots” with the highest market potential.  

We’re all familiar with the concept of the strip mall (in Germany they’re also known as Fachmarktzentren): an out-of-town shopping area characterised by a centralised parking area and a parade of shops or big box stores clustered together. Over time, and even during the pandemic, these areas have out-performed city centre locations.

According to JPMorgan, “The pandemic had a major impact on retailers in city centres heavily reliant on office workers and tourism. But service-oriented strip mall retailers in densely populated urban and suburban neighbourhoods performed well throughout 2020 and 2021. These properties have consistently performed well regardless of market conditions.”

This successful recipe stems from considering other nearby businesses not as potential competitors, but as opportunities to draw the right target market to the location.

Complementary businesses offer products that relate to or complement yours:  a pharmacy near a doctor’s office, a bar near a restaurant near a hotel, a sports shop near a gym, a pet supply store near a veterinarian, a cafe next to a bakery.

We recently interviewed a retail expansion manager who said “for my client who rents out deposit boxes to store people’s valuables, I analyzed how many banks are located around a potential new site”.

So if you are looking for the ideal location for your business, you should also analyse which other shops in the area complement your offer and are beneficial to your business.

Understanding how people travel to your store is vital. Are you in the middle of a city where parking is at a premium? Are you out of town and far away from public transport? Do customers have to pay to park near your store? Do you sell large, bulky items that require a car?

It’s important not to overestimate how many people will travel to your store by car, and consequently underestimate how many will use public transport or other forms of mobility.

A recent study in Berlin, Germany, discovered that retailers often make the mistake of overestimating the amount of people who travel by car when they go shopping.

The report, which surveyed 145 traders about how they thought customers got to their shops, and interviewed 2,019 shoppers on two shopping streets in Berlin, discovered that shop owners overestimated how far customers travel to visit their businesses.

“Over half (51.2%) of shoppers lived less than 1 kilometre from the shopping street. In contrast, traders on average estimated that only 12.6% of customers live within this distance.” The results appear to show a big discrepancy between the perception of traders about customers’ mobility patterns and the actual reality.

Furthermore, the study appeared to show that traders often misjudged how customers travelled to their shops, underestimating public transport and overestimating car use.

“While only 6.6% of shoppers travelled to the streets by car, on average traders estimated 21.6% of their customers use this mode; a discrepancy of 15%,” says the report. “Further they underestimate transit, pedestrian, and bicycle travel by 8.1%, 6.2% and 3% respectively.”

Before deciding on a location, analyse it for accessibility, considering different modes of transportation such as walking, biking, driving, and public transportation.

Foot traffic is one of the hallmarks of retail. At its most basic, it means the number of people walking past. It’s one of the key metrics for retailers, as the pedestrian activity near a shop influences sales volumes and increases the chance of spontaneous buying or “impulse purchases”.

So if you’re deciding on a location for your new business and benefit from spontaneous purchases or visits, you should take a closer look at this figure. But be careful: often a general figure is not enough. You should also consider whether there are fluctuations throughout the day and how foot traffic behaves on weekends compared to weekdays.

Furthermore, you should also check what causes the traffic. Are vehicle data included, or are only pedestrians counted? Just because a location has high frequency doesn’t mean that people have the time for a spontaneous visit to your store. Therefore, Foot Traffic should only count visitors who spend at least a certain amount of time in the area, not just passing through.

But while foot traffic is important, it’s not the only consideration. During the pandemic lockdowns, foot traffic in some areas went down significantly as people preferred to shop close to their homes because of travel restrictions. Suddenly, hyper-local shopping became popular.

Because of this, it’s crucial to understand the demographics nearby, what the average household size is and how many children live there children, for instance. If you really understand the catchment area, you’ll discover how many potential customers can reach your location. This can give you a good understanding of whether the site is attractive or not and whether it will appeal to your target customers.

As a business owner, you probably have a fair understanding of who your target customer is. But defining who they are and locating them is not so easy. What problem is your business trying to solve for them? What is the benefit of your product? Do you serve a particular niche market, and do you have enough potential customers in your catchment area? What other companies nearby offer the same or a similar product or service as you? According to Marketing Donut, “successful marketing relies on understanding your target market. Who are you selling to? Why should they buy your product? What do they stand to gain?”

In a blog on WordStream, the writer Dan Shewan, said: “If you run a small business, maybe you have an idea of your target market. However, a vague idea is not enough to compete in today’s ruthless business environment. Without detailed knowledge of your target market, you could be losing business to your competitors or missing out on opportunities to increase sales.”

Ultimately, the right location is the place where your target customer visits or lives. With powerful location intelligence, you can unlock the door to compelling insights that could be the difference between business success or failure. With TargomoLOOP, you can analyse data such as population age groups, household size, spending power and lots more to help you understand how you can find and reach your target group.

A graduate of China University of Geosciences, Yue Luo sits within our data sciences team, where she is responsible for analyzing data to generate detailed, actionable insights and predictions that ultimately help influence decisions for Targomo customers. 

Yue’s road to Targomo was quite linear. A background in Geographical Information Science (GIS) and merging spatial statistics with machine learning methods led Yue to further her studies at the State University of New York at Buffalo. There she obtained a PhD in Geography, before leaving academia behind to relocate to Germany and join Targomo. “My passion for GIS was strong from the very beginning, and I’m lucky to have found the perfect opportunity at Targomo that allows me to pursue it professionally while continuously enhancing my skills and knowledge. As one of the leading locational intelligence companies, I love that Targomo acknowledges the importance of utilizing spatial statistical methods to find solutions for a variety of industries.”

In other words, Targomo is the perfect professional fit for her particular skill set. “It’s my first full time role, and as expected, it’s quite different from academia. Professionally, the pace is much faster, and the deliverables are of course results-oriented. In the academic world, it’s the exact opposite. It’s more about taking the time to research topics, and thoroughly understanding and articulating the process to derive results. With that said, while my role at Targomo is challenging, it’s equally as rewarding, thanks to my supportive, approachable, and inclusive colleagues that constantly motivate me.”

Aside from preparing data to continuously explore models and implementing new ideas to optimize methodology performance, Yue spends her days on everything from routing and location selection to revenue prediction and driver analysis. “I like that Targomo offers me the luxury to be creative, and the freedom to try and experiment with ideas.” The one aspect of her role she loves the most? “Receiving customer feedback in real time. I’m able to see how beneficial my work is to their business, and how I was able to help improve solutions based on their specific needs.”

Lastly, data isn’t her only passion. Outside of the office, Yue starts each morning moving through a vinyasa flow to set her intentions and prepare for the day. After hours, Yue loves to explore international great food. “I love sharing good food with friends and coworkers!”

Expansion needs to be well planned, and that’s exactly what McDonald’s Germany will be doing in the future with Targomo as its new partner. The location intelligence startup was able to convince the burger giant of its technology and the expertise it has gathered, and signed the global fast-food chain as a new customer. McDonald’s uses the platform TargomoLOOP to plan new restaurant locations in Germany.

“In the future, TargomoLOOP will make it much easier for us to evaluate new restaurant locations in terms of the relevant catchment area,” says Andreas Weber, Head of Real Estate at McDonald’s Germany. “The sound data basis and the intuitive interface were decisive factors in favor of a decision for TargomoLOOP.”

“We are proud to support McDonald’s in their German expansion,” said Niklas Gossel, Head of Enterprise Sales at Targomo. “Our analytics platform is designed to provide brands of large branch networks with a reliable data-driven decision-making basis. Locations contribute decisively to value creation but are also associated with high investments. We can use our technology to significantly reduce risks of bad decisions and strengthen the value creation of physical locations.”

McDonald’s serves around 1.6 million guests a day in around 1,450 restaurants in Germany, making it the market leader and largest employer in the system catering sector.

Interested people can register here to test TargomoLOOP for free.

Finding the right retail location doesn’t happen by chance. With so many factors to consider, from location scouting to customer analysis, an expansion manager can be the driving force to find the perfect place.

As retail experts, expansion managers have the industry contacts, the expertise and the technology to help store owners make an informed decision about where to put their business, whether it’s their first shop or your next. They can also take care of all the contract negotiations, providing retailers with a seamless turn-key solution that works around their business’ needs.

To bring more light to the work of an expansion manager and find out how they discover the best retail locations for their clients, we spoke to Samuel Vogel, owner of retail and real estate consultancy The Bird.

“I work in the field of real estate search,” explains Samuel. “I’m scouting for the right retail objects. Additionally, I examine a building’s technical specifications. I make a full location analysis. I also take care of branch network expansion. Everything really, up until the handover of the keys.”

Samuel Vogel advises clients such as shopping mall manager Unibail-Rodamco-Westfield and safe deposit box company Trisor. He has worked for several other retailers, including VIU Eyewear and bakery chain Zeit für Brot.

For Samuel, knowing his client’s customers is key to helping them achieve their retail goals. “My first question is always ‘who is your customer’,” he says. To give us an example, Samuel mentions one of his clients, Trisor, who rents out deposit boxes to people who want to secure their valuables away from home.

“This service is about the feeling of security, because the service is deposit boxes. Therefore, locations should be reachable 24 hours a day and have good parking. Furthermore, you want to know where there is a high density of potential customers, what their incomes are and what kind of products they buy. This helps me to find the optimal locations,” says Samuel. “The more questions you ask about customers, the closer you get to identifying the optimal locations, and the more you map their needs, the easier it is to find the right location.”

What the retailer sells and how it sells it is another important factor, whether that’s a product or a service. Some companies, like jewellers, benefit from a premium façade to convey the feeling of luxury, whereas a fitness chain would benefit from a solid structure that can handle heavy gym equipment, while a restaurant would seek an acceptable level of sound insulation and air ventilation. In the case of Trisor, its security deposit boxes are very heavy, so Samuel needed a building that could handle this weight. Again, with Trisor, the front of the building has to convey a feeling of security if a customer is to trust placing gold bars or other valuables in there.

“A visit to the places is a decisive factor,” explains Samuel. “I have to see the building and develop a feeling for the place. An image in a brochure can be perfect, but if something near the place doesn’t match the brand and product, that building could go off the list.”

The customers’ needs and the brand’s image determine the requirements that a location should meet. Samuel uses this list to request real estate options from his network of property brokers, and make a preselection of suitable locations. When retail space could be a good match, he will always have a visit in person.

“One of the important tasks of an expansion manager is to clearly explain to the agency or owner who might not be familiar with the product, what we are looking for,” says Samuel. “The landlord wants a reliable tenant with long-term plans. It is therefore vital to give the landlord a good introduction to the retailer’s business. If they don’t understand the product, they won’t accept me as a tenant.”

Once Samuel receives the real estate offers, he will rank them in terms of best fit for the retailer based on their needs and of course their customers’.

Knowledge is power, and when it comes to retail, accurate geo-referenced information and location data is crucial, from demographics of potential customers to footfall, as Samuel explains. “Firstly, I take a macro perspective: I look at the whole country and cities that could be suitable for my client. If it is a new business setting up locations, I still have an ‘empty’ map, so to speak. The logical step is to look at urban areas and big cities and see where the biggest potential is. Secondly, after I have identified specific locations, I examine these places with location data to see whether that site truly is a good match for the retailer.

“With Trisor, for example, I analyzed how many banks are located around a potential new site, and more specifically, how many deposit boxes are likely to be on offer there. We can’t get exact figures about the number, but I can make an analysis to estimate supply and demand. To do this, I used Targomo’s technology.”

With Targomo, Samuel was able to see how many banks and gold shops were located in this area so that he could make a supply and demand analysis to see if there is a need for this service. “The exciting thing about Targomo’s analytics platform is that it allows me to combine external data with internal data,” he says. “The more location-referenced data I have in the platform, TargomoLOOP the more accurate the analysis becomes. The more I know about my business, the better I can position myself in the market. TargomoLOOP allows you to scientifically compare different locations based on data and evidence.”

FREE TRIAL: Learn how technology supports retailers with site selection and expansion in TargomoLOOP.