Retail store expansion strategies are one of the most fundamental issues for growing retailers. Opening a new store can be a game changer if you get the location right, or your new store could be doomed to failure if the location doesn’t attract enough customers.
In addition to geographical factors, such as transportation accessibility and real estate prices, demographic factors and mobility patterns in the areas of interest play a key role in decision making. These data on population, purchasing power and consumption habits are what generate an optimal expansion strategy.
Predictive location, and foot traffic analytics reveal valuable information that helps retailers to choose the right location when setting up geographic expansion strategies.
How are predictive analytics models used to determine the optimal location for a new facility?
Foot Traffic analytics can identify the characteristics of transit stops and routes, helping to determine and improve the overall coverage of any transit system.
When it comes to public transport, foot traffic analytics can be of great help to authorities, who are faced with various challenges such as road congestion and the diversity of modes of transport, among others. This poses difficulties for public transport managers and operators when it comes to planning.
The secret to site selection in such a competitive market is based on the ability to analyze the right data and be able to understand and interpret the site selection strategies of nearby locations to stay ahead of their expansion plans and gain a competitive advantage.
Where? This is the fundamental question that guides any site selection decision.
With advertising analytics based on big data techniques, marketers can quickly determine the effectiveness of each channel and thus adjust their strategies, enabling them to run hyper-targeted campaigns, choosing the right ad content for the appropriate ad networks.
What is it?
This type of analytics refers to the use of data and technology tools that help companies and marketers effectively monitor their marketing efforts to ensure that campaigns are targeted to the right audience and use the right channels for effective communication.
Delivery companies leverage location intelligence to have better market capture and maximize customer experience.
More and more businesses are getting into the product delivery business. This quest, in turn, has led them to need locationintelligence, as it allows them to measure and control various factors critical to the success of their business, or their processes, including real-time traffic updates, delivery address location, routes, among many other things.
Logistics managers need to implement location intelligence in supply chains in order to reduce delays, keep costs down, generate a competitive advantage, and thereby improve the global network of multiple carriers, service providers and physical locations from the constant threat of unexpected problems.
By leveraging location intelligence, decision makers gain deeper insight into market trends, consumer behaviors, foot traffic patterns, manufacturing activity, competitors’ logistics operations and much more.
Retailers need to use predictive modeling and combine it with business, customer, and market data in order to forecast sales or new businesses profitability.
Predictive modelingis a highly effective way to identify a suitable area for expansion strategies, as it has become a vital tool for narrowing down hundreds of potential sites or even a single site. When a potential site is identified, it’s combined with additional layers of data to determine if it meets the model’s requirements, sales performance targets, and other critical factors for any business requirements. Read the full article here
By incorporating location intelligence into urban planning, it becomes possible to develop infrastructure adapted to the needs of citizens, enhancing living conditions in any given city. In addition, spatial data helps to optimize costs and prioritize government administration projects.
What does location intelligence provide to urban planning?
The key to attracting potential customers to any new location is to determine its foot traffic potential, the use of geospatial data combined with footfall analytics makes the retail site selection process easier, faster, and more reliable.
At PREDIK Data-Driven we support corporations by optimizing their site selection strategies with 100% data-driven methodologies. One of our clients, a major regional footwear retail corporation, was able to determine in which shopping mall it was more convenient to open its first brick and mortar store, thus reducing investment risks and maximizing its revenues, having identified its potential customers and its target market in the malls.
In order to optimize advertising costs and maximize revenue, marketing leaders are using spatial data to create geofences in specific areas, allowing them to reach audiences that are more likely to become potential customers.
Micro-mobility analytics improve retailers’ expansion strategies by accurately identifying consumer demographics, understanding customer behavior, and understanding how their competitors are performing.
Micro-mobility is a methodology that combines geospatial data and foot-traffic analytics to solve several problems and improve site selection strategies by helping to understand how people move around specific brick n’ mortar locations, allowing companies to analyze movement patterns around specific locations, such as retail stores, to extract meaningful information.
Matching demand and supply is the basis of the business model of any company whose operations depend on micro-mobility, since for every unit of demand that is not satisfied, an order is lost, leading to loss of profits and customer loyalty.
All companies that rely on micro-mobility can better manage their assets by improving their algorithms with location intelligence and foot traffic analytics, identifying demand peaks or drops beyond the average value in order to foresee or solve any kind of unexpected problem and generate solutions based on Big Data. Mobile tracking helps to know what is happening over any terrain and teaches how to be proactive about it.
Supermarkets can apply location intelligence techniques and footfall analytics to understand consumer mobility patterns, generate efficient site selection strategies, understand the performance of their stores, and estimate competitor turnover.
The correlation between foot traffic visitation, sales, and the success of retail supermarkets have been studied and proven, so the development of this type of analysis has become a priority in the site selection process and expansion strategies.
Footfall analytics and POI characterization through Big Data are being used by different business sectors in order to make smarter business decisions and thereby maximize their revenues and optimize their costs.
Case Study: POI analysis of N1 City in Cape Town, South Africa
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