Retailer Uses Real Estate Intelligence to Back Risky $1M Per Store Expansion

With over 100 stores and outlets across the globe, this popular clothing and accessories retailer, has an active real estate team that is always looking for new and exciting opportunities for growth.

While CCG had already helped this clothing and accessories retailer implement a customer intelligence solution that helped them identify exactly who their best customers were, now they wanted the ability to identify where their next best customers were located, so they could confidently create new retail stores.

Still, selecting new locations is always a risk. Building out a new store can involve an investment of over $1 million, and it’s important to recoup that money within a year or two. Failure is not an option.

By understanding the customer base around existing locations and overlaying that with other internal and external data, this company was able to reduce the risk associated with real estate development and find store locations that were positioned to prosper. 


Geographical expansion for brick and mortar placement is essential to clothing and accessories retailer as their locations complement their online marketplace. In addition to generating the right foot traffic, clothing and accessories retailer stores fulfill online orders through their brick and mortar locations based on availability and proximity to the end customer.

When selecting a new location, the real estate team leveraged market research around demographics, neighboring landmarks (like universities), historical data, and property costs, amongst other elements.

The challenges that this team faced was that their processes to harvesting data were manual and did not provide the predictive intelligence needed to make investments with certainty. They also needed a more reliable and data-driven process that ensured technical and non-technical individuals could use the outputs for strategic decisions.

Considering the time, effort and cost involved with building new stores, this clothing and accessories retailer needed a more reliable, data-driven, and automated process. And that’s where CCG comes in.


CCG had previously implemented their CI for Retail product, an analytics platform for retailers who want to elevate the customer experience, for this clothing and accessories retailer. Now, they were tasked with further customizing that platform, extending the platform’s capabilities, and developing a system that first determined what factors were the keys to success at existing locations.

Then, using machine learning, the system could evaluate potential store sites using those criteria, and predict the likelihood of a specific location being successful. Essentially, CCG created a scoring algorithm for potential sites and then scored the list of locations under consideration by the real estate team.

Thus, the process that used to take hours of manual work and educated guessing could now be done automatically, in real-time, using reliable, clean data.

CCG’s new location tool delivered a wide range of metrics for assessing potential locations – in addition to predicted performance – making location comparisons easier for their decision-makers. In fact, the tool uncovered several promising locations that were not previously on their radar. Through better understanding of their customer demographics and features, teams are better able to understand the characteristics of the market around an existing store as well as future store locations. This understanding allows a broad cross-section of teams to make more informed merchandising decisions, driving improving the customer experience, and ultimately driving greater profitability in each market. Location demographics and information can be pulled independently of any list, matching up with key criteria in any area. This prevents great potential store sites from being overlooked.

“Deciding if and where we should invest in new retail stores can be a risky venture – especially if we aren’t able to base that decision on solid data. CCG’s location tool utilizes machine learning to help us make more accurate predictions about a potential site’s success, helping us make more confident and profitable real estate decisions.” --Vice President of Business Analytics & Strategy

This tool has excellent potential to scale, and could be used in a wide range of industries that have multiple locations and a plan for growth. Even though this organization had real estate experts on board, this system requires no real estate knowledge or expertise, and can quickly narrow down the field of potential store locations so decisions can be made with confidence. If your retail business could benefit from a tool that makes real estate decisions less risky and more profitable, CCG can help. Contact one of our Data and Analytics Experts today!

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Quick Facts

  • Industry -Retail
  • Solution -Real Estate Intelligence
  • Technology - Customer Intelligence for Retail, Alteryx, Python


Building out a new store location can cost up to $1 Million, needing to recoup funds is essential.

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