Driving Retail Efficiency: Leveraging Data In Site Planning

/ septiembre 20th, 2018 / 0 Comment

Technology has replaced location as the most important factor in the success of retail. The National Retail Federation reported on a study from WD Partners that a majority of consumers (53%) want to buy online and pick up in-store in order to enjoy the best of both worlds. A full 60% of shoppers under 30 love the concept of showroom stores with no inventory, like Nordstrom Local, and even traditional shoppers over 45 like the concept.

How Data Resolves Key Questions For Retailers

Many players in the retail space are facing existential questions such as, “Which store should I shut down?” or “Where do I open my next store?”

The old “four corners” location logic, which made it profitable to open competitive stores in high-traffic areas or choose a location as close as possible to the center point of consumer residence areas, has now found its way into the history books.

Here are three factors retailers need to consider to make more intelligent decisions in site planning and internal store design:

Factor No. 1: Macro-Indicators Of Market Growth Potential

Retailers need to research whether consumer activity (e.g., foot traffic) is increasing or decreasing in the areas of potential site locations. This will certainly be affected by the influx (or outflux) of population movements, but they need to look deeper into the data to break out income levels of potential shoppers and the incoming/outgoing population. Generating personas and normalized consumer profile reports that analyze the population by lifestyle choices, the affordability of your brand, the progress of gentrification in various neighborhoods, etc., will help retailers analyze the area. Furthermore, they need to examine how well other industries are doing in the area and benchmark their success factors.

Another critical element is financing options for real estate in the neighborhoods. Retailers need to consider how real estate prices are moving and new sources of financial backing for prospective homebuyers. Based on the above data points (as well as any others specific to their market position), they can map various areas as growth or decline zones.

Factor No. 2: Analysis of Extant Competition

Using data, retailers can have a detailed analysis of their competitor’s strategy versus their own strategy. They can find answers to questions such as which retailers are their primary competitors in a specific region and the audience for these competitors. By taking a granular look at the activity at competitor stores, including time spent and distance traveled to get there, they can determine how quickly their competitors are growing, how engaged customers are at the stores and the primary drivers of their sales revenues.

Just as retailers would with their own performance, they can push out projections in the quarterly, six-month and annual categories for their competitors. By analyzing how often customers physically visit their competitors’ stores, they can identify if their engagement or purchase journey has changed recently. Finally, they can rank their competitors in terms of footfalls and sales in specific zones to benchmark those numbers against their own.

Factor No. 3: Analysis Of Existing Sites

All the evidence points to the fact that consumers still want both online and brick-and-mortar options. To better triangulate the best physical location for their next store, retailers need to consider how close they want to be to up-and-coming residential areas. In addition to thinking about ease of accessibility and spillover effects from close competitors, they need to map out places where off-price retail is filling in “white spaces” in their territory and strategize how to better serve this market. Then, they need to weigh the cost of putting stores in neighborhoods where competitors are established.

The next step is to lay out route plans of where consumers shop based on their commute patterns between home and work. There will be natural bottlenecks and nexus points where routes coincide. Retailers can develop a time chart of the regions they identify and rank it by performance growth vs. static numbers. Data sources of consumer movement can be very valuable in analyzing traffic in and around their store location.

Finally, they need to break down how far their best customers have to travel to visit their stores and analyze the performance of all store locations within a certain proximity compared to outside those areas. This will require them to analyze the ROI of store-specific marketing vs. operational spend. Then it is much easier to see the stores that have inherent capabilities to perform better and the ones they are better off closing.

Use Recent, Real-World Data

There are many other points to consider, but the most important takeaway is that retail analytics are foundational today for intelligent planning and more reliable revenue in a time of ongoing volatility. Retailers need to be sure their data is drawn from detailed, recent and reliable data sources.

Author: Anil Mathews. Anil is the Founder and CEO of Near. Anil built Near with a technology-centric approach into a global ambient intelligence platform.

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