Retail Analytics: Should we open new stores?
Data science now generates strategic solutions that help retailers identify optimal potential locations for expansion by assessing the market potential of areas of interest for new store openings.
Applying footfall analytics and location intelligence based on spatial data, retailers can perform analyses that identify areas or points of interest by analyzing the concentration of people, identifying the most and least crowded places, the times and days of peak pedestrian and vehicular traffic, and defining the shopping profiles of consumers in areas of interest.
This information helps to propose strategies for expansion plans and commercial routes, to maximize revenue and reduce costs in the supply chain.
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What variables are taken into account in the analysis?
The density of pedestrian and vehicular traffic, presence of other businesses in the vicinity, trends, tastes and preferences of those who travel and live in the area, behavioral and consumption patterns, sociodemographic characteristics of the floating and resident population, among others.
What are the phases of the analysis?
Phase 1 – Definition of the roadmap: Should we open new points in this city?
We start by evaluating specific zones or points of interest, which can be an area, a city, a state, or even an entire country, adding different layers of market data and sociodemographic information. With a 100% data-driven methodology, we first define whether or not a real market opportunity exists.
If the data shows that the market shows the potential we are looking for, we execute the second phase.
Also read: “How to increase customer dwell time“.
Phase 2 – Once it is validated that the area of interest has the required potential, we deepen the search for the best locations, starting by identifying affluent areas, main streets or avenues, competitors, risk areas, market potential and classifying consumers based on the type of business, helping to answer questions such as:
- What are the best locations for new stores?
- How many stores should we open?
- Where are my competitors’ stores?
- What are the expected revenues at each of the potential stores?
In order to maximize the efficiency of this analysis, layers of data are added to define consumer profiles, population characteristics, and preferences. This is divided into several steps, which you can learn about in this article. Business Expansion: Methodology for finding the best location.
At PREDIK Data-Driven we analyze our clients’ needs and implement all types of mobility intelligence to maximize their revenues, generate solutions and foresee future problems.
Need to implement mobility intelligence for future expansion plans? contact us!