Right Locations = Success For Retailers
About 53% of retail shops operate no longer than 4 years, while 20% of them fail just after a year in operation. One of the most important reasons of such failure is the selection of the sub-optimal locations which have low potential fort he desired customer base.
The right site selection is a complicated problem; there are many factors affecting the performance such as visibility, popularity, accessibility, and density of the target customer segment.
All factors should be analyzed separately and together for optimal location selection. Many retail companies invest in software and data for better analyses but mostly to no good-end.
Greatest return on investment requires a 5 step approach:
1. Target Identification
It includes demographic and geographic characteristics, as well as buying patterns and purchase history. Retailers should define proprietary customer profiles such as ‘women, 15-25 year olds, and singles. Demographic structure which combines geography, may be clustered into identifiable groups for target sales.
2. Data Selection
Data are the main component for the location analysis. There are so many data to choose from and most of them irrelevant at the end of the day. The correct group of data should be selected initially for the analysis to be successful.
3. Analytical Approach
Analytical approach consists evaluations of analysis of plausible relationships among both geo-demographic and customer data. After selection of the right data set, appropriate analytical methods should be applied.
4. Site Evaluations
Site evaluations determine the characteristics of the places and sales effect areas. Site evaluation should provide enough information about the location such as customer forecast, foot traffic forecast, and revenue forecast.
5. Market Optimization
Market optimization is the process of improving the marketing efforts of retail shops to maximize the desired business outcomes. After applying analytical methods on defined dataset and site evaluation via location analysis, locations and markets can be optimized.
Considering an example, world’s large coffee house, which has 4,000 stores throughout the world, increased operating income %32 percent by using location analysis. In retail sector there are always lots of risks like cannibalization of sales through existing stores, stores on low potential areas. That company was forced to close hundreds of stores because of having negative efficiencies that are related to choosing wrong locations in 2007 and 2008. After location analysis the store opening classes of 2011 and 2012 had produced some of the best unit economics of the company, very strong growth.
Location analysis and GIS on retail sector is the most effective method for reaching maxi¬mum benefit in terms of site selection. Optimum decisions for new locations should be presented based on the location dynamics, geographic conditions, viewing angles. But putting data together is not enough by itself; the weight of the data should be assessed utilizing domain knowledge of the retailers.