Location Analysis of Your Store, Shop is Now Asked from Artificial Intelligence with NEXTGEO
The concept of artificial intelligence (AI) is increasingly appearing in many areas of our lives every day. Designed to mimic human intelligence and developed with systems such as machine learning, deep learning and natural language processing, AI applications help solve complex problems by analyzing large data sets.
In many fields from education to health, from design to security, almost every day a new artificial intelligence technology and applications are being introduced into the daily lives of individuals and companies. In parallel, the world's leading companies are investing billions of dollars in artificial intelligence technologies to strengthen their position in the competition in this field.
One of the issues touched by artificial intelligence is one of the most important stages of the investment and leasing process, when companies decide on the location.
The location decision process, which requires the simultaneous evaluation of many different data, is of critical importance in terms of determining the most suitable location for the company's investment strategies. Because a wrong decision to be taken at this stage causes the company to suffer financial (turnover) and moral (prestige) damage.
Next Geo, which develops location analytics with artificial intelligence technology, also provides advanced çözümümümümümürü>determination for retail sector örü companies.
The location selection algorithm developed by Next Geo data science teams statistically associates the company's store-based performance data with the global data in the Next Geo data pool to determine the factors that positively or negatively affect store turnover and the coefficients of these factors.
Demographic data (population, age, gender, lifestyle, etc.) Economic data (household income, sector-based household expenditure and socio-economic status) Each data in the Next Geo data pool, which consists of tens of thousands of current environmental criteria collected under the main headings of Competition (store locations of the company's own stores and competing brands), Environmental factors (other environmental factors such as schools, hospitals, public institutions) and Pedestrian traffic, is calculated for each store phase and included in the algorithm.
The location selection algorithm identifies the universal factors affecting store turnover from a large pool of data and accordingly identifies the common location criteria of successful stores.
In the last stage, nearly 200th000 retail street sections throughout Turkey are analyzed in the detail of the departure-division of the street and the similarity with the locations of successful stores is scored. By using the street scores, which are created completely according to the company's location selection criteria, it is possible to find out to what extent any location in Turkey is suitable for the company's location selection criteria.
Developing a similar model for shopping centers, Next Geo incorporates data such as the number of stores, brand mix and leasable area size of shopping malls into the location selection model within the scope of the algorithm and achieves similar results for shopping malls.
With this technology, Next Geo, which provides unique çözüm;s in determining the most suitable locations for the investment criteria of companies, has already provided nearly 70 companies operating in banking, retail, fmcg, açThe company provides location analytics çözüs developed with artificial intelligence technology to nearly 70 companies operating in the outdoor advertising, automotive and electric charging station sectors.
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