The science fiction author Arthur C. Clarke famously postulated a law of the universe in the late 1960s: "Any sufficiently advanced technology is indistinguishable from magic." Given the rapid technological progress, particularly through the advancement of artificial intelligence, this seems to be increasingly true every day. The implications for the commercial real estate industry are often such that they would have seemed like pure mysticism to CRE professionals at the time of Clarke's statement.
An example illustrates this: a restaurant chain with over 3,500 locations in the US is examining potential sites for additional branches in a particular part of Los Angeles. The chain has defined very specific parameters, including a cash-on-cash return of at least 20 percent, annual sales of at least $1.5 million, and a maximum cannibalisation factor of 10 percent for other company branches in the region. This information is entered into a computer program, a button is pressed, and within moments, the computer generates a detailed map of the neighbourhood with a series of irregular shapes that precisely represent the areas – down to specific streets and addresses – where a new branch would achieve these or better results.
As a constantly growing support for retailers, location intelligence has evolved to a level where platforms can predict retail success, including sales and return on investment, for a specific location. These forecasts are based on hundreds of demographic and psychographic factors, as well as information such as competitive analyses, complementary local businesses, local crime patterns, and the individual retailer's own history.
As an example, consider the location intelligence program Vantage by consulting firm Bain & Company, which evaluates current and potential physical locations for retailers. It is driven by global datasets and machine learning analytics, which present the results in a user-friendly location visualisation dashboard. Bain presented the aforementioned hypothetical example to Commercial Observer and offered further predictive details for the areas represented by the irregular shapes on the map.
A click on such an area showed that potential new branches for the franchise in that area could expect to achieve annual sales between $1.8 million and $1.9 million, as well as cash-on-cash returns of 25 percent, with the highest possible cannibalisation of an existing franchise branch being only 2.3 percent. For a franchise with high local saturation, it also precisely detailed which branches would be affected by cannibalisation and to what percentage extent.
The program also works in reverse, allowing retailers and brokers to place a marker at any nearby location and adjust the predictions according to the information already provided. Forecasts can also be based on additional details, which are as granular as whether there is a traffic light nearby or on which side of the street the location would be – all of which can influence footfall and sales figures.
Francois Vayleux, Vice President Global Retail Practice at Bain, explained that this is where the true strength lies, as potentially dozens or hundreds of areas could show high potential for a location. However, this technology allows one to select an area and precisely assess how much money can be generated based on the available information. Given the enormous amount of location intelligence data and analysis tools, including significant advancements in these categories in recent years alone, the ability to analyse locations down to the finest detail is quickly becoming a valuable tool and an essential skill for any retailer or retail broker.
Cassie Durand, Executive Vice President at CBRE and specialising in tenant representation for retail clients, recalled that in the post-COVID-19 pandemic period, all recently collected data quickly became irrelevant. The way people worked, shopped, and lived had changed faster than ever before. Durand noted that in her search for the best path for her retail clients, her first new hire – which she then described as unconventional – was not a broker, but a location intelligence specialist.
Durand emphasised that client confidence in company data, especially at a time when there was confusion about the most fundamental human behaviour patterns and interactions, was of utmost importance both for serving clients and as a competitive advantage. She further explained that a business originally based on brokerage activities has evolved into a consulting firm, which is also the ultimate goal. One wants the client to feel they are working with a consultant who genuinely cares about data-driven decision-making. This clarity and certainty regarding data and its best analysis are essential today, especially given the oversaturation of available information.
