Selecting a new location is critical to the success of the new retail store, but it is hardly a straightforward endeavor. Considerations must include the needs of the business (space, storage, displays, deliveries, parking), customer demographics, census data, retail foot traffic, accessibility, visibility and more. Unfortunately, most retail locations are often selected by valuing emotions over information, and expectations over analytics. By enriching other data sets with location analytics, retailers can get the actionable insights to help them find the best locations for their new stores.

Reaching ideal customers means having a clear picture of who they are: age, gender, family status, etc. Location analytics can help businesses enrich current and potential customer demographics and improve strategic audience targeting, which can inform retail site selection decisions.

Location analytics can provide valuable insights into how people interact with brands. The customer journey often reflects consumer habits. Retailers might have some understanding of where customers shop and dine based on survey data, but this data alone doesn’t provide insight into the full customer journey. One type of data derived from enterprise location intelligence that can be used to understand consumer habits is foot traffic data. For instance, customers at a health food store might stop by on the way home from the gym. If the retailer decides to open a new location, then they might consider leasing a space near the gym.

Retailers can gain an even deeper understanding of customers with a further application of location intelligence – one that reveals consumer interests. With location analytics, a retailer can discover even more about their customers by learning their interests. Take for example, different events happening at a stadium within the same week. People who attend a concert at a stadium more than likely have different interests than those who go to the same stadium to watch a baseball game. Understanding the interests of customers adds the ‘why’, giving context to demographics and customer habits.

A 360-Degree customer profile can be created by combining first-level demographic data with second-level habits, then adding additional information describing their interests. This information can inform a site location decision by providing retailers with consumer insights for advanced market research.

Before a retailer selects a new location, it’s important for them to analyze competitor data. A saturated market may not be an ideal area for retail expansion. Retailers can combine traditional market share data with location analytics to understand competitor activity. With this information, a retailer can answer questions such as:

• In my area of interest, what are my competitors’ customers interested in?
• What are the busiest times of the day or week for competitors near my potential site?
• Which competitor stores have the most and least amount of foot traffic?

Interested in learning more about location analytics for retail expansion? Contact with our location intelligence experts today.