Greggs is one of the UK’s leading bakery chains, famous for its sausage rolls, sandwiches, and affordable coffee. With thousands of locations across England, Greggs caters to commuters, students, and professionals, balancing affordability with convenience.
However, as consumer habits evolve, factors such as foot traffic, pricing, and customer sentiment play an essential role in determining how well Greggs is performing across different locations. This article analyzes key data points, including traffic trends, pricing structures, and customer ratings, to provide insights into the performance of Greggs.
Greggs' performance across England is strongly influenced by foot traffic and visitation trends. Understanding these patterns helps identify high-performing locations, areas with potential for growth, and underperforming sites in need of optimization.
Greggs has 151 highly visited locations across England. These stores are typically found in city centers and busy shopping areas, where daily foot traffic is consistently high.
A significant portion of Greggs stores—1,294 locations—experience above-average visitation. These sites form the backbone of Greggs' network, serving busy suburban neighborhoods, high-street retail areas, and secondary urban centers. Many of these locations are strategically placed near schools, office districts, and roadside service areas, ensuring steady customer inflow throughout the day.
Only 41 Greggs stores report average visitation levels. These locations may be in developing neighborhoods, low-footfall shopping areas, or smaller towns where customer traffic is moderate. Factors like local competition, accessibility, and surrounding business density likely influence these numbers.
Interestingly, 282 Greggs stores lack recorded traffic data. This gap may be due to recent store openings, limitations in tracking, or locations in lower-surveyed regions. These stores represent an opportunity for further analysis and strategic adjustments.
By analyzing traffic data, Greggs can enhance performance at underperforming locations, strengthen high-traffic stores, and refine its expansion strategy to align with customer demand.
While Greggs has numerous locations across England, some districts stand out due to higher-than-average foot traffic. Among them, Castle, Five Village, Blacon, and Muskham each have two highly visited Greggs stores, making them key hotspots for customer activity. These areas likely benefit from prime retail positioning, strong commuter traffic, or high local demand.
Below is a list of the districts with the highest concentration of highly visited Greggs locations:
By analyzing factors such as surrounding businesses, customer demographics, and accessibility, Greggs can further optimize its site selection and expansion strategy.
Customer feedback is a key performance indicator for Greggs locations. Ratings reveal consumer sentiment regarding food quality, service speed, and overall experience. Here is the rating data breakdown:
A significant portion of Greggs locations (1,723 stores) do not have available customer rating data. This lack of insights presents a challenge in assessing overall brand perception. AI-driven sentiment analysis and customer feedback tracking could help fill these gap.
While Greggs has thousands of locations across England, only a handful have achieved a perfect 5-star rating, highlighting exceptional service, product quality, and customer satisfaction. These standout locations are spread across St Leonard’s, Meriden, Harold Wood, High Legh, and Goldenhill & Sandyford districts, often benefiting from strong local demand, well-managed operations, and strategic site selection.
Greggs is known for its affordable pricing, positioning itself as a budget-friendly alternative to coffee shops and bakeries like Costa Coffee and Pret A Manger. 1,711 of Greggs locations across England fall into the inexpensive pricing category, making it a go-to option for cost-conscious customers.
Certain districts in England have a high concentration of Greggs locations categorized as inexpensive. These areas tend to be urban centers, commercial zones, and districts with a high volume of students and commuters, where affordability is a key factor for daily customers.
Below is a table highlighting the districts with the most inexpensive Greggs pricing:
Online reviews from customers provide deeper insights into customer satisfaction, service experiences, and product expectations.
From our UK restaurant and cafe dataset, there are no Greggs locations with up to 1,000 reviews compared to brands like Costa Coffee with reviews reaching and exceeding 1,000 from customers. The highest volume of reviews is from 700 to 942 and they are located in Devonshire, St Pauls, Martlesham, Greenlands, Ketley & Overdale, Whickham North, Hexthorpe & Balby North, Rawcliffe & Clifton districts.
For more details on the reviews of all Costa Coffee locations in the United Kingdom, sign up for xMap Studio.
The ability of bakeries like Greggs to expand strategically relies on geospatial intelligence and AI-powered site selection.
Bakeries can use geospatial analytics to assess:
By integrating predictive analytics, bakeries can:
Bakey brands are increasingly investing in AI-powered decision-making to optimize store performance. This includes:
Greggs continues to dominate the UK’s bakery sector, benefiting from strong brand loyalty, competitive pricing, and strategic location planning. By leveraging geospatial data and AI, Greggs ensures that it remains a leader in the quick-service food industry.
In conclusion, As customer expectations evolve, bakeries must continue adapting to traffic trends, pricing dynamics, and customer feedback to maintain its market dominance in England.
Contact xMap to make inquiries about our datasets across countries and industries.
Whatever your goal or project size, we will handle it.
We will ensure you 100% satisfication.
"We focus on delivering quality data tailored to businesses needs from all around the world. Whether you are a restaurant, a hotel, or even a gym, you can empower your operations' decisions with geo-data.”