Nimbus | EG Group Case Study

Background

EG Group is one of the UK’s fastest-growing and most recognisable forecourt operators, with an expanding portfolio of 341 freehold-owned sites throughout mainland UK.

Alongside an innovative approach to roadside retail, EG Group has forged high-profile relationships with globally recognised retail and convenience brands. It is now operating over 157 Starbucks drive-to and drive-thru restaurants, 138 Subway sub-stations, and 200 Greggs bakeries.

EG Group’s vision is to engage and work collaboratively with leading retail brand partners to deliver a world-class fuel, convenience, and food and drink offer that exceeds the expectations of the modern consumer.

Nimbus is light-years ahead. With its ease of use, constant feature development and comprehensive property data, we’re able to find and secure acquisitions quickly.

Neil Findlay

Development Director, EG Group

The challenge

EG Group grows through acquisitions and needs to keep buying sites at pace in line with ambitious growth goals. But to do this, they need to eliminate inefficiencies to enable them to target, identify, and complete the purchase of new opportunities at speed.

The challenge is information is disparate and takes a long time to consolidate:

→ Access to the key information to assess commercial sites can take a while to compile, such as plot size, planning history, flood history, traffic flow and local property values.

→ Speaking to agents is time-consuming and not scalable.

→ Data is readily available but with so many sources, reliability and accuracy is not always guaranteed.

The solution

To accelerate their team’s proactive site finding, Euro Garages turned to Nimbus. As soon as they had a trial of Nimbus, they realised it was the perfect tool to bring all the data they needed into one place.

Within just a few months of using Nimbus, the team is saving time, improving efficiency and identifying more opportunities than ever.

In fact, it’s a vital tool in their day-to-day work. It helps them to identify the right sites, make contact with landowners, and ultimately quickly make more accurate and data-driven decisions.