Every day, restaurants open, close, and relocate. They sometimes change names, or get acquired by other brands. At the same time, consumers are constantly changing the way they interact with restaurants based on their own personal financial situation, and the larger economy.
.png)
In such a dynamically changing world, it can be difficult to stay on top of these trends and truly understand what the restaurant market landscape looks like. With accurate and fresh points of interest (POI) data, data scientists can easily understand how many restaurants opened in a given month, at any level of geographic granularity. Enriching each of these restaurant locations with consumer behavior data provides the necessary context for understanding the full picture, enabling data scientists to measure how economic trends impact the restaurant market.
This infographic reflects US market changes and provides insight into how consumer behavior is impacted by economic trends. Check out the breakdown and then download a sample of SafeGraph data to get started building your own restaurant industry analytics.
The restaurant industry is extremely dynamic. Full service restaurants, quick service restaurants, drinking places, and snack bars all have unique target customers and ideal market conditions that determine whether they thrive or flounder. For example, during the COVID-19 pandemic, quick service restaurants (QSRs) had to adapt to changing consumer behaviors in order to stay afloat. Success or failure to do this can result in brands expanding to new areas of demand, or closing down underperforming restaurants.
In these infographics, we use the SafeGraph Places dataset to see how many restaurant and bar locations opened and any regional trends in store openings for the months of April and May of 2022. We specifically measure NAICS codes beginning with 722 so that we isolate our findings to categories in the food service industry. From those NAICS codes, we identify the top restaurant category in each state that has seen the largest number of location openings using the opened_on column in SafeGraph Places.
According to CNBC, 60% of restaurants close within one year of opening, and 80% close before their five year anniversary. Restaurants close every day in every type of economy, but the closure rate can fluctuate due to factors like the pandemic, stimulus checks, or recession.
Each month, SafeGraph measures how many restaurant and bar locations closed using our Places dataset. To understand the state of the food service industry and how that differs regionally, we specifically look at NAICS codes that begin with 722 for April and May 2022. We identify the top restaurant category in each state that has seen the largest number of store location closings during that time period using the closed_on column in SafeGraph Places.
Restaurant openings can be the result of many factors, such as an increase in demand in an area, or the success and expansion of a particular brand. For example, in times of recession consumers may choose to eat more at less expensive restaurants, resulting in a boom in demand for those brand locations. Analyzing restaurant store location openings by brand can reveal interesting insights related to consumer demand and economic health.
To see which restaurant brands experienced the most growth during April and May 2022, we measure the amount of restaurant location openings by brand. We then identify the five brands with the most POIs opened in the US, using the opened_on column in SafeGraph Places.
Restaurant closures can occur for a variety reasons, including increased competition in a particular area, or a decrease in consumer demand. As an example, during a recession consumers may choose to spend less money at expensive restaurants, resulting in a decrease in demand and a need for brands to close restaurant locations that are underperforming.
To understand which restaurant brands contracted the most in the US during April and May 2022, we measure the amount of restaurant location closings by brand. We then identify the five brands with the most POIs closed in the US, using the closed_on column in SafeGraph Places.
Consumer behavior fluctuates throughout the year based on factors like seasonality and popular trends, but also over time as a result of the larger economy. Looking at transaction data associated to specific points of interest (POIs) helps reveal these patterns in consumer spending and how it impacts different restaurant brands.
To see which restaurant brands saw the biggest decrease in transaction volume during this time period in the US, we use SafeGraph Spend data to compare the number of transactions month over month at brands with NAICS starting in 722. With these insights, data scientists can attribute a restaurant brand’s performance to larger economic or regional trends.
Consumers often change how they interact with restaurants based on what time of year it is, what is popular among their friends and family at the moment, and also how the economy is doing. Transaction data for individual places shows how consumer spending changes over time, and also across regions.
To see where else consumers shopped, we used SafeGraph Spend data to compare the number of transactions at POIs with NAICS starting in 722 during the given time period. Identifying the restaurant brands with the biggest increase in transaction volume month over month can help indicate how the economy is impacting consumer spending behavior and overall brand health.
Consumers spend money at multiple restaurant brands, and understanding these relationships is critical to profiling customers and building trade areas. While two restaurants may be competitors of each other, their customers may actually frequent different locations. These types of insights can help restaurants brands understand how best to serve their customers and better compete in the market.
Using cross-shopping columns in SafeGraph Spend, we chose two competitive restaurant brands and identified the top three other restaurant brands customers shop at. We did this by counting the number of times each restaurant brand’s POIs shows any spend with a related restaurant brand, reflecting the number of POIs where a customer had spent money at that specific location and the related brand.
