How Earls Court Development Company use data to help inform a new neighbourhood

Background

The Earls Court Development Company (ECDC) has a vision to bring the wonder back to Earls Court. Their latest proposals demonstrate how Earls Court will be put back on the map, re-emerging as a destination to discover wonder, an ecosystem for creative talent and a showcase for one of the fastest growing industries in the world – clean and climate tech. The masterplan includes 4,000 new homes, 12,000 jobs, culture, community, retail, dining and leisure. 60% of the land is unbuilt, maximising open spaces and opportunities for nature to thrive. The site will have a series of cultural venues, alongside a commercial campus creating a global destination for clean and climate tech research and skills. Sustainability will be the green thread, with one of the largest zero-carbon energy loops in the UK powering the site. A hybrid planning application will be submitted this summer and the first phase will commence in 2026.

The Challenge

• Understanding how current plans would impact the local market, what retail opportunities should be created and how to create a robust masterplan that would address these factors, despite London’s complex market and a high amount of local competition.
• Gauging customers and audience — who is already here, what they do, what they need and where they go — in relation to other large-scale central London developments and regeneration master plans in King’s Cross and Battersea.
• Prior to partnering with CACI, the company solely relied on qualitative data to understand peoples’ perceptions and inform their decision making, such as speaking to people within the community and stakeholders.

The Solution

ECDC was keen to ensure that an optimised neighbourhood would be created for residents both within and outside of the development along with workers and users of the space. To achieve this, CACI interpreted and analysed raw data and numbers for the company, bringing them to life and narrating the results through comparable’s and benchmarks.

It’s very clear in the presentations that we’re given — whether it’s for local authorities or internally — that the evidence base is robust and ultimately indisputable. That was helpful in providing that context and equips us with a robust way to create and define the master plan moving forwards.

Tom Branton, Development Director at ECDC

The CACI data sources included as part of this study were:

• Mobile App Data: Mobile location data generated a precise view into the location’s catchment and visitor profiles, ensuring ECDC would innately understand how visitor profiles and their respective behaviours varied over time. This helped the company assess who users are along with their demographic and spending power, along with insights into how visits changed over a day and week.
• Acorn: CACI’s consumer segmentation model, Acorn, enabled ECDC’s understanding of who new residents would be and their needs, and who would shop at the development.
• Location Dynamics: Location Dynamics is CACI’s spatial interaction model, creating a digital mirror of the UK retail landscape replicating consumer flows. The engine of the model is a machine learning algorithm that provides future forecast catchments. For ECDC, CACI used Location Dynamics to understand the expected current catchment and spend, as well as leakage to nearby destinations, to provide a detailed understanding of the local retail landscape.

The Results

• Newfound understanding of the ‘size of the prize’ of wider London and tourist demographics and audiences. ECDC historically relied on gut instinct when it came to decision making, but working with CACI ensured they were backed with concrete evidence. For example, CACI’s data showed that one-third of the total potential spend in the development area could come from out of catchment.
• Enhanced decision-making through evidence-based data on the community. With the development situated across both the London Borough of Hammersmith and Fulham and the Royal Borough of Kensington and Chelsea, their perceptions of the surrounding community to inform decision-making — while strong — are now rooted in evidential data. This has served to alter their perceptions to ensure that a comprehensive understanding of residents and borough dwellers can be met and their audience narrative can be shaped accordingly.

The Future

In the coming years, CACI will continue to support ECDC in the data-backed planning and construction of residential units, retail landscape and office space development.

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