SERIES: RETAIL TRENDS THAT ACCELERATED DURING THE PANDEMIC

The pandemic has forced restaurants and bars in Europe to close their doors for months on end. Only recently have they been allowed to serve customers again. The only way to keep cooking and serving during the lockdown was to deliver meals to people’s home. And this has indeed happened exponentially, driving the sales of Just Eat Takeaway.com, Delivery Hero, Grubhub and similar order and delivery services across the globe.

In this second article of our retail series we’ll have look at the meal delivery industry, which has propelled the existence of so-called ghost kitchens, or dark restaurants. These cater to people ordering online, have no seats, and often combine different types of cuisine under one roof.

In the first article we’ve discussed how convenience has become front and center for many consumers. This was already a big trend before the pandemic, but the coronavirus outbreak has accelerated it. People not only want to buy books and electronic goods online and have them delivered, but also food. For many during the pandemic, the only way to get to get a meal without cooking it yourself was to have it delivered. And they did in droves.

Figures from the big players proof the point: DeliveryHero, which operates in 50 countries around the globe, saw the number of orders jump by 96% to 1.3 billion orders in 2020 (this figure also includes orders for grocery and non-food items). The orders were worth €12.4 billion ($15 billion). Other delivery companies, such as Glovo, DoorDash and Uber Eats, have reported similar double-digit growth figures.

Exact figures about the global industry vary widely, but according to a study by Research and Markets worldwide sales are expected to reach $127 billion this year, up 10% from 2020, and grow further to $192 billion in 2025. Interestingly, the study says that “cost of supply chain and logistics will be the key restraint for the online food delivery services market.” Businesses could even “lose up to 26% of their profit if they fail to upgrade their logistics system to ensure on-time delivery”.

The boom of this meal delivery industry has created a new type of restaurant, so-called ghost kitchens. They’re also known as dark, cloud, or digital-only restaurants. These establishments usually only cook to deliver. They typically have no seats and no waiters. They take orders online (some perhaps also by phone). They may also combine different types of cuisine under one roof, for instance pizza and pasta in one part of the kitchen, and burgers in another part.

You usually can’t find ghost restaurants in shopping malls or Class A locations, and may not even recognize them from the outside. Instead, they are located in residential neighborhoods or on parking lots close to their customers. The proximity to customers is crucial: This helps the kitchens quickly bring the meals to the home or office from where the orders are placed.

Virtual restaurants typically only exist in the apps of meal delivery companies, such as FoodPanda, Deliveroo or Wolt. Some are owned and operated by real restaurants, while others are set up by delivery companies themselves. For example, Deliveroo operates three dozen sites, which house 220 ghost kitchens on four continents. Some of them are housed in shipping containers on parking lots, or in warehouses. Delivery Hero’s brand FoodPanda operates its own ghost kitchens in Asia and also plans to open them in Germany.

Some of these delivery companies rent out kitchen space to existing restaurants, which can then expand their reach into new neighborhoods. The establishments benefit from new orders, which their physical locations could not fulfill. There are also companies specialized in setting up these ghost kitchen sites and renting them out, such as Reef and Cloud Kitchen in the US.

There are three clear advantages in operating ghost kitchens, says Thomas Primus, CEO and Co-Founder of FoodNotify, which helps restaurants digitize operations, such as real-time supply management and digital recipe management.

“In many cases, there are additional cost savings to be had by sharing space and locations. Additionally, ghost kitchens don’t need to spend money on the interior, such as tables and seats, staff waiters and printed menus. Secondly, there are many kitchens whose utilization can be increased by serving customers online, for instance by offering lunches, or a completely new line of products, for example, wraps and burritos in addition to pizzas. Thirdly, ghost kitchens offer a low-cost option to expand into new neighborhoods or cities, and reach new customers,” explains Thomas.

He thinks that especially smaller restaurant owner could benefit from the concept, because they don’t have to invest heavily into a new, full-fledged establishment if they want to expand. They can simply set up a kitchen, or rent space in a ghost outlet to reach new customers. People seeking to launch a new restaurant could also benefit, because they can first test their idea as a virtual kitchen and see what runs well or what does not.

Thomas finds it difficult to give predictions for the ghost kitchen market, but he does believe it will continue to grow. In Europe, the market is still relatively small and considered a niche market, but in the US and China it is already reaching size: More than 1,500 ghost restaurants exist in the United States, and more than 7,500 in China. In her Food Report 2021, the Austrian food scientist and expert Hanni Rützler expects the trend of ghost kitchens to gather pace, even when the pandemic has been overcome.

The fact that the delivery companies themselves continue to set up new ghost kitchens underlines the market’s potential. Deliveroo itself plans to double the number of ghost kitchen sites to 64 this year, from which hundreds of different cuisines will operate. Supermarket chain Walmart has teamed up with the company Ghost Kitchen Brands to set up dozens of dark kitchens in Walmart’s stores in the US and Canada. Kroger, the biggest US grocery chain, is also expanding its ghost kitchen operations.

Phantom-like as they may sound, ghost restaurants will likely be as normal as buying cars or fashion online.

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The coronavirus outbreak is changing the roles of malls and inner city shopping areas. Samuel Vogel, owner of retail and real estate consultancy The Bird, has talked to Targomo and walks us through the changes affecting the retail market, from more local shopping to the diversification of a mall’s tenants.

In many European countries, shops have been allowed to reopen again, but lower footfall traffic is still very noticeable in top retail areas, such as malls and inner city areas. Samuel, who advices businesses on expansion and real estate strategies, sees this as the main challenge for retailers in top locations.

“When we don’t have reliable pedestrian data it is difficult to determine a location’s attractiveness. Rental prices have dropped considerably,” Samuel says during a video interview with Targomo. “I think in half a year we can truly see what the impact of the pandemic will be on inner city retailers. Which can survive, and which ones will throw in the towel?”

Footfall in inner city areas have suffered so much that in Germany even big chains such as drugstores DM and Rossmann and supermarkets like Rewe, Aldi or Alnatura have slowed or halted their expansion plans in these top locations, Samuel has noticed. Before the pandemic, there was a trend of these chains moving into the cities’ centers.

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.

On the positive side, he sees the current market as an ideal moment for companies to expand or move to top locations. “I think and I hope that we’ll get a bit more variation in inner city areas. Smaller players which previously were located in B or C areas now have a better opportunity to move into A locations, simply because they can afford it.”

He has seen that rental prices have dropped up to 35 percent in top areas, and that some retailers have decided to move to a next-door location to benefit from lower rents.

In addition to inner city areas, malls have suffered from the pandemic as consumers favored local, outdoor stores. Indoor shopping centers would probably benefit from new and different tenants to remain attractive, according to Samuel. “Some of them will have to repurpose retail space. Perhaps it would help if they house a big medical practice in a mall, or accommodate other use concepts to become attractive again or remain attractive.”

A third retail trend that the expansion manager finds noticeable is the arrival of instant-delivery companies, which operate micro-fulfillment centers in urban areas. Startups like grocery delivery firms Gorillas, Weezy or Flink are expanding rapidly.

“Flink, Gorillas and the like are companies that are not eying to rent top locations in inner cities. Instead, they want to locate their logistics hubs, of about 200 to 300 square meters in size (2,200 – 3,200 square foot), in the neighborhoods where people live. This allows them to reach their customers extremely fast. This is not immediately impacting inner city locations.”

Samuel Vogel founded consultancy The Bird in Berlin in 2020 after a decade-long career in retail. He has an extensive network in the retail and real estate industry in Germany and abroad. He supports retailers and other businesses with a B2C focus in finding the right location and right retail space. He advises or has advised a diverse group of clients, such as shopping mall group Unibail-Rodamco-Westfield, safe deposit box company Trisor, drugstore chain DM, VIU Eyewear and bakery Zeit für Brot. More info: the-bird.de

Targomo helps business and public organizations harvest the power of advanced spatial analysis. Targomo was founded in 2013 and is based in Berlin and Potsdam. The Location Intelligence company has customers in more than 20 countries and was selected as one of Europe’s top five Deep Tech companies at the EIT Digital Challenge in 2020.

The AI-powered location analytics platform TargomoLOOP allows users in retail, hospitality, real estate, logistics and public services to optimize their location networks and services. Users obtain valuable insights to increase revenue, save costs and gain decisive competitive advantages. Everyone can sign up and start analyzing for free.

Deichmann Group, Europe’s biggest shoe retailer, has chosen Targomo’s technology to support its site selection in Germany. Deichmann will use Targomo’s location intelligence platform to predict the potential of new sites and further improve the performance of existing shops.

The German retailer, which operates in 30 countries with leading chains such as Deichmann, vanHaren and Rack Room Shoes, has selected location analytics platform TargomoLOOP for a pilot project to support its site selection in Germany, where Deichmann operates more than 1,400 stores.

TargomoLOOP is an AI-powered platform to analyze a network of locations with numerous location-related statistics. By combining locations with demographic data and precise travel time calculations, the platform allows companies to more quickly and easily identify sites that are best reachable for as many customers as possible.

The project with the Berlin-based tech company will give Deichmann additional insights into its branch network and the advantages of digitally provided location-based retail analytics. It will support Deichmann in keeping the right balance between the proximity to its customers and running its stores in changing market conditions.

Another objective is to support the forecasting of the revenue of potentially new locations and help analyze the profitability of existing sites. To make this possible, Targomo will analyze and bundle many of the variables that impact performance.

By using TargomoLOOP, Deichmann will obtain data-based indications for different performance levels. Combined with on-site expertise, the retailer can analyze realized performance and identify new locations. Ultimately, it hopes to support footfall and conversion rates in its stores, further increasing turnover and profitability of all its store locations.

Targomo helps business and public organizations harvest the power of advanced spatial analysis. Targomo was founded in 2013 and is based in Berlin and Potsdam. The Location Intelligence company has customers in more than 20 countries and was selected as one of Europe’s top five Deep Tech companies at the EIT Digital Challenge in 2020.

The AI-powered location analytics platform TargomoLOOP allows users in retail, hospitality, real estate and logistics to optimize their location networks. Users obtain valuable insights to increase revenue, save costs and gain decisive competitive advantages.

SERIES: RETAIL TRENDS THAT ACCELERATED DURING THE PANDEMIC

The pandemic has hit few other industries as hard as retail and out-of-home dining and drinking. Stores, restaurants and bars had to close virtually overnight and were only allowed to reopen, if at all, under tight restrictions. To cope with this situation, businesses have adapted and introduced new concepts and sales models. Consumers have also changed their shopping habits, reinforcing existing and breeding new retail trends. These developments appear to permanently alter the role of brick-and-mortar stores.

In this new series, we’ll discuss some of the retail trends, which are likely to be part of the “new normal”. The first big trend: Grocery delivery – when possible, within 10 minutes.

One of the New Retail’s hallmarks is convenience. Grocery delivery, long present before the pandemic erupted in 2020, has been one of the main beneficiaries of this need. Both new order & delivery services as well as classic supermarket chains have tailored to increased demand for at-home deliveries of grocery products.

Some people simply don’t want to wait in line, others dislike finding empty shelves. When the pandemic hit, some didn’t want to visit any stores because of infection risks. Ordering online and getting it brought to your home has been the easy, safe answer. A single figure shows how the service has skyrocketed the past twelve months: Globally, there were more than 550 million downloads for food and drink apps in Google’s Play Store between March 2020 and April 2021, a 33% percent year-on-year increase. Experts estimate that 10% to 15% of US grocery sales moved online at the height of the pandemic last year, as much as five times pre-covid levels.

Clearly, quick grocery delivery offered by new retail entrants Gorillas, Gopuff, Weezy and others have seen a stellar rise during the pandemic. They are rapidly expanding across cities in Europe, the US and elsewhere. Early May, US-based Gopuff announced the acquisition of British peer Fancy. Some of them have already reached unicorn status ($1+ billion valuation) and set new records. Berlin-based Gorillas attained the much coveted valuation level in March, only ten months after its founding. It was the shortest time for any German startup to become a unicorn, and possibly in Europe. And that’s not all: Gorillas is currently in talks for a $500 million funding round, valuing the company at more than $6 billion, Bloomberg has reported.

The high valuations and the intense interest in these new startups comes with a simple, but bold promise: Grocery deliveries in as little as 10 minutes. It is a radical break with 1- or 2-day delivery, the old norm of traditional supermarkets.

To keep their pledge of instant shipments, the startups are building up a novel network fulfillment and delivery centers. The new retailers operate so-called dark stores located in areas with a high population density. Dark stores are relatively small, local warehouses and are not open to visitors. They are also known as micro-fulfillment centers, from which orders are immediately processed and dispatched to the consumer as soon as orders come in. Contrary to large logistics centers on the outskirts of town, these dark stores are located in the neighborhoods where people live, guaranteeing ultra-short delivery times.

Consumer’s demand for convenience and instant delivery has also pushed the incumbents to offer quick commerce services. In the UK, discounter Aldi and upmarket supermarket chain Waitrose have picked meal delivery company Deliveroo to offer delivery of groceries in 20 or 30 minutes. In the US, online order & delivery apps like Instacart and Shipt allow consumers to order from dozens of shops such as Whole Foods, Target and CSV, and get them shipped in as little as an hour.

The rise of instant delivery has even prompted sformer players to return to the German home market with meal and grocery deliveries. Delivery Hero, the world’s biggest meal delivery company, had sold all of its German operations in 2018 to focus on emerging markets. But last week, the Berlin-based company announced it would launch its quick commerce service Foodpanda in Berlin and other German cities.Delivery Hero has also stepped up its game, promising delivery of food and non-food items in as fast as 7 minutes. It will partner with local restaurants and stores, as well as operate its own dark stores, which Delivery Hero calls Dmarts, or “dark markets”.

The move will further intensify competition in a nascent market. Experts think that eventually less than a handful of local players will survive. The winners need to corner the market with an optimal fulfillment network, a superfast delivery service and the right product mix.

All these developments, from young startups like Gorillas to decades-old family businesses like Aldi, imply that instant grocery delivery and the rise of micro-fulfillment centers will continue to spread – even when the pandemic has passed.

Location intelligence enables retailers to identify the best locations for micro-fulfillment centers and reach the optimal market penetration for entire networks. Book a demo to learn more.

We’ve released a major update of our location analytics platform TargomoLOOP: Businesses can now examine whether a new branch would cannibalize the catchment areas of existing locations. They can also see how rival locations could affect the potential customer base of own branches in the same area.

In the retail industry, for example, branches of the same chain sometimes compete against one another when they are located close to each other and catchment areas overlap. This effect is known as cannibalization, but the same principle also applies to the impact of competitors nearby.

All these surrounding locations have an effect on the number of people that is expected to visit a store. Calculating the impact of these locations is now possible in location analytics platform TargomoLOOP with a new feature called – surprise, surprise – cannibalization.

Although reality is more complex, the assumption behind cannibalization analysis is that a person only visits one location and is not counted twice or more when catchment areas overlap. Cannibalization analysis is especially relevant for the uses case where a consumer only buys products in either shop A or shop B. It also applies to the business of micro fulfillment centers, for example, when online grocery shops instantly deliver goods to the buyer’s home, or when restaurants bring their meals to people living in the immediate vicinity.

In all these cases, a business does not want catchment areas of shops, delivery centers or restaurants to overlap, because that would lead to an oversupply of locations and higher operational costs. Or it would lead to a significant loss of potential customers when rival chains are located in the same area, but customers only care for visiting a single chain, for example, Do-It-Yourself Center A or B.

By considering cannibalization, a manager gets a more accurate picture of a location’s true catchment area. If a shop owner wishes to open a new branch, she can immediately see whether that new store would “steal” potential customers from existing shops in the same area and how many. She can also see how many customers she potentially could win from competing shops nearby. Or, conversely, how a competitor’s new location might impact the catchment area of her branches in the same area.

The new feature will help businesses and organizations to make better analyses of their locations and, ultimately, make better decisions about opening a new branch, relocating an existing one, and responding to competitors.

All types of data can be used to calculate a location’s catchment area, and therefore, the impact of cannibalization. TargomoLOOP offers demographic data, such as total population, household size and age groups, people categorized by spending power, and visitors data, for example.

Let’s take the example of two supermarket chains, which each have 3 shops in Stuttgart. Their customers typically travel a maximum 10-minute car ride to the store. In the analysis below, when cannibalization is not considered, the shop that attracts the most people is My Location C. However, when the feature is turned on, Competitor Location B comes out first.

In TargomoLOOP, making the analysis is as easy as turning on the light: You only need to switch the cannibalization toggle to ON in the top-center of the table. Your results are calculated on the fly and shown in the table. For more information about how to use the feature and interpret the data, check our help pages.

For consumers, the travel time to a location and the attractiveness of that location – defined by, for example, the products on offer, opening hours, and the presence of other shops – determine whether they visit that place or a different one.

TargomoLOOP’s cannibalization feature uses travel time to calculate whether a person visits shop A or B, as shown in the picture 2 above. A person is expected to visit the location that he can reach in the shortest amount of travel time, given the selected travel mode. In the future, we also plan to introduce the option to take the attractiveness of a location into account.

The cannibalization analysis is based on a scientific method to predict the likelihood that a person visits a certain location. Newton’s law of gravity, which states, among others, that the gravitational force between two bodies is inversely proportional to the squared distance between the two bodies, is taken as the basis of the calculations. But instead of taking distance, travel time is taken as the variable determining whether a person “gravitates” to location A or B. Anyone interested in the methodology can check our whitepaper Selecting the Ideal Branch Location with Gravitational Models.

Many businesses and organizations, from retailers to restaurants and bakeries, from real estate to mobility services, can benefit from TargomoLOOP and its features. They can make detailed analyses of locations, catchment areas, and neighborhood characteristics.

The German capital has placed its vaccination centers at central sites in the city. We wanted to know how easily people aged 65 and up would be able to reach these locations. It turns out that around 95 percent of Berlin’s seniors can reach a center in 30 minutes by car.

Since the end of December, Germany has been vaccinating its citizens aged 65 and older. People over 70 years are entitled to a return trip by taxi, paid for by the local government. Many people who live in elderly homes can also get a vaccination at home thanks to mobile teams, who inoculate seniors where they live.

Because there is no data about how many seniors are eligible to receive vaccination at home, we have assumed that all people need to visit one of the six centers. We wanted to know how much time it would take for all Berlin seniors of 65 and older – 700,000 in total – to reach one of the vaccination locations. We used the locations of Berlin’s six vaccination centers, demographic data and a reachability calculations available in location intelligence platform TargomoLOOP.

We’ve found that the majority of people can reach an inoculation center in a maximum 30-minute car drive. Only a few hundred in pockets in the west, east, and south-east would need up to 40 minutes by car to reach the nearest vaccination location. These are the highlighted areas in the picture at the top.

The table below shows the result for different age groups. The total for the age group 65 and up is 683,393, but this figure also includes seniors who do not live in Berlin. Based on Berlin’s total senior population of 699,564 at the end of 2018 it means that 97.7 percent of them can reach a vaccination center within 30 minutes by car. The actual percentage will be a bit lower, because of the non-Berliners included in the 683,393 figure.

We’ve also looked at public transportation as the travel mode, and then the travel time increases for many senior citizens. Most of them could reach a center within an hour. Only a couple of dozen people in the south-east (Müggelheim, Rauchfangswerder, Altes Fischerdorf) would need a little longer. Obviously, many seniors will likely not take public transportation because of the infection risk, and the option to take a free taxi ride for people aged 71 or older.

The analysis above has been done with analytics platform TargomoLOOP. The basic version is free of charge and allows users to quickly gain insights into their locations. Curious to see the platform in action? Simply sign up and start analyzing.

Location analytics platform TargomoLOOP supports managers in retail, food service, real estate, public services and logistics to analyze locations and quickly see their potential in terms of catchment area, customer base and reachability. AI-powered predictive analytics allows retailers to identify the success factors of a network of stores and predict the revenue potential of new locations. These insights help managers to plan and optimize their branch network.

The platform’s basic version offers essential features to analyze locations with maps, demographics, and reachable places (also known as Points of Interest). Users can easily rank locations by category and weight. They can correlate location variables with performance. Users can analyze an unlimited number of locations and download reports of their findings. No set-up is required: Simply register, type in an address, and get results within seconds. Everyone can start analyzing for free.

+++ Update +++

Most of the services are up and running again, including TargomoLOOP, the dashboard and developer documentation.

For detailed information and continuous updates, please check here: https://status.targomo.com/

+++Update +++

A fire early Wednesday morning destroyed parts of Europe’s largest data center. Also some of Targomo’s services are affected by this incident and are currently unavailable.

Details:

The location analytics platform TargomoLOOP is currently offline.

The majority of Targomo’s API services are not affected. However, there are some effects as we implement our fallback infrastructure. Currently affected resources for API users:

We are working hard to get the services back online as soon as possible. Currently, we cannot yet estimate how much time it will take to get our services online again. We apologize for any inconvenience the disruption may cause.

For further information and current updates, please check our status page.

Detailed information about the incident you can find here: https://status.us.ovhcloud.com/

Please don’t hesitate to email support@targomo.com if you are experiencing any other issues we should be aware of.

Businesses looking for the best locations can now very quickly identify which sites best match their specific requirements. In location analytics platform TargomoLOOP they can rank locations by assigning weights to criteria most relevant to them.

Each business needs a specific area to thrive. For some stores, households with children are crucial, while the presence of offices has a negative impact on revenue. For restaurants the presence of high footfall is important, while the vicinity of supermarkets could be detrimental to business.

Finding the locations that match these individual location parameters is now easier with a new weighting feature in Targomo’s location analytics platform TargomoLOOP. In the example with the stores above, the feature allows a retailer to add a high weight to the variable households with children and a low or negative weight to the presence of offices.

Of a list of potential locations, TargomoLOOP can now easily rank all these sites and give an individual scoring to every location, using the weights. Locations in areas with more households with kids will get a higher score, while those with many offices in their vicinity get a lower score. The result is a ranking list of locations customized to the specific needs of the business, in this example a certain retailer.

Noel Carbo, Product Manager with Targomo, says: “Many location questions require a customized analysis of location variables. By adding weights to each demographic variable and reachable places category, our customers can precisely find the locations that best suit their business. Weighting greatly improves the value of our scoring and ranking analysis, resulting in better location recommendations.”

Many businesses and organizations, from retailers to restaurants and bakeries, from real estate to mobility services, can benefit from TargomoLOOP and the new weighting feature. They can make detailed analyses of locations, catchment areas, and neighborhood characteristics.

The basic version of TargomoLOOP is free of charge and allows users to quickly gain insights into their locations. Curious to see the platform in action? Simply sign up and start analyzing.

Location analytics platform TargomoLOOP supports managers in retail, food service, real estate, public services and logistics to analyze locations and quickly see their potential in terms of catchment area, customer base and reachability. AI-powered predictive analytics allows retailers to identify the success factors of a network of stores and predict the revenue potential of new locations. These insights help managers to plan and optimize their branch network.

The platform’s basic version offers essential features to analyze locations with maps, demographics, and reachable places (also known as Points of Interest). Users can easily rank locations by category and weight. They can correlate location variables with performance. Users can analyze an unlimited number of locations and download reports of their findings. No set-up is required: Simply register, type in an address, and get results within seconds. Everyone can start analyzing for free.