Accelerating Store Network Expansion – 6 Benefits of Geomarketing

Analyze and optimize network coverage

By calculating trade areas around each point of sale in a retail network while factoring in competitor locations, geomarketing makes it possible to quickly identify white zones (also known as expansion areas) as well as cannibalization zones. This makes it easy to achieve expansion, optimization, or network consolidation objectives.

Trade areas can be calculated based on various parameters specific to each industry: driving time, walking time, distance, and more. These theoretical trade areas can then be refined with additional parameters such as revenue or market potential, to obtain real-world trade areas.

Discover the best locations for your future openings

By correlating real estate opportunities with geolocated contextual data, geomarketing enables upstream evaluation of a future site's potential. Modern tools such as Galigeo's Predictive Geomarketing Platform allow unlimited simulations to be run, eliminating unsuitable locations upfront based on defined criteria. This avoids having to conduct costly, time-consuming traditional studies that are often outdated before they are even completed.

Taking it a step further, applying predictive models that factor in data such as median household income or foot traffic within the future point of sale's trade area provides a reliable estimate of market share or revenue potential, accurate to over 85%.

Determine the local potential of your existing stores

Geomarketing provides a comprehensive view of a point of sale's local environment, helping to understand the reasons behind its strong or weak performance. Using contextual data — for example, the recent arrival of a competitor in its trade area — within relevant performance analyses enables swift, well-informed decisions to optimize each store's performance.

Cross-referencing with digital channel data also makes it possible to measure the impact a physical store has on online sales, evaluate drive-to-store performance, and assess the omnichannel strategy.

Leverage mobility data to get a concrete picture of potential foot traffic at a future retail location

Using pedestrian or road traffic data, depending on your needs, in your site selection studies provides a refined view of potential in-store traffic. The precision of current technologies then makes it possible to segment this traffic by type of passerby: age, gender, origin, whether they work or live in the area, and more.

For example, it becomes possible to calculate the average daily traffic of a future location, or to compute ratios between people passing by the storefront, people entering the store, and people making a purchase inside.

Predict the future revenue of an upcoming location

After all, why leave the opening of a new store to chance? Current predictive models, which take into account numerous parameters — such as the type of business to be established, the average age of the surrounding population, or daily traffic — provide a reliable revenue forecast for a retail location.

For instance, the estimated revenue the retail brand will generate once established can be included in site feasibility studies or business plans, reassuring all stakeholders: franchisees, investors, and retail brands alike.

Segment consumers based on relevant criteria to launch effective advertising campaigns

By selecting a set of relevant parameters, retail marketing teams can precisely target ideal audiences for their campaigns: place of residence, workplace, age, gender, and more. Leveraging geomarketing thus reduces campaign costs and improves ROI.

For example, it becomes possible to send promotional materials only to the right audience, or even to identify the 100 loyalty cardholders most likely to purchase specific products in the coming weeks, by combining business data with artificial intelligence.