Fig 1 - uploaded by Marina Kholod
Content may be subject to copyright.
Source publication
In this paper we analyze the new type of information, namely RFID (Radio Frequency Identification) data, collected from the
experiment in one of the supermarkets in Japan in 2009. This new type of data allows us to capture different aspects of actual
in-store behavior of a customer, e. g. the length of her shopping path. The purpose of this paper i...
Similar publications
Data about the shopping paths of customers in stores are now available due to developments in radio frequency identifica- tion technology. In this study, we conducted clustering of the shopping paths of customers gathered in a grocery store in Japan. We obtained nine typical movement patterns from the clustering results. In addition, we associated...
Unlikeonline shopping, it is difficult for the physical store to collect customer shopping data during the process of shopping and conduct in-depth data mining. The existing methods to solve this problem only considered how to collect and analyze the data, but they have not paid attention to the large computation amount, bulk data amount, and long...
Citations
... Distance between home and office is also critical because one who lives close to the office can buy more goods since the person frequently trips to the store (Kholod et al. 2010). Moreover, the personnel's marital status and partner's occupation are also important factors (Kim and Ju 2018). ...
Current descriptive studies have demonstrated both positive and negative impacts of Ramadan on consumption among Muslims. However, it is crucial to convey a deep understanding of the causal relationships between Ramadan and consumption behavior to inform policymakers and guide the development of efficient policy recommendations. In exploring the dynamic between Ramadan and consumer behavior, this study delves into the causal effects of the holy month on the purchasing patterns of Muslims. Utilizing a natural field experiment, the research examines data from 1837 observations involving 267 Muslim and non-Muslim personnel at the Police Headquarters in Bangladesh. The study employs a difference-in-differences method to isolate the impact of Ramadan and Eid festivities. Our findings reveal a substantial purchase increase among Muslims during these periods— 40.6% during Ramadan and 76.3% for Eid. These results underscore the importance of ensuring a preemptive ample supply of Ramadan- and Eid-related goods in the market to manage demand-pull inflation early in and during Ramadan. Moreover, the study accentuates the necessity for further research on the broader implications of Ramadan on Muslim spending habits across Bangladesh, aiming to inform and guide national economic policies.
... To account for variable store traffic intrinsic to the problem, layout optimization can be carried out by considering the shopper paths. As mentioned before, several researchers showed that product exposure, and eventually sales, increase with the increase in the length of shopping paths (Hui et al., 2013;Inman et al., 2009;Kholod et al., 2010). Supported by this finding, Boros et al. (2016) aimed to increase the path length for the average customer in a supermarket. ...
It is well-established that increased product visibility to shoppers leads to higher sales for retailers. In this study, we propose an optimization methodology which assigns product categories and subcategories to store locations and sublocations to maximize the overall visibility of products to shoppers. The methodology is hierarchically developed to meet strategic and tactical layout planning needs of brick-and-mortar retailers. Layouts in both levels of planning are optimized considering eligibility requirements and complete set of shopper paths, thus, they successfully capture the unique shopping behaviour of consumers in a store’s region. The resulting mathematical optimization problem is recognized as a special instance of the well-known Quadratic Assignment Problem, which is considered computationally as one of the hardest optimization problems. We adopt a linearization technique and demonstrate via a real-world numerical example that our linearized optimization models substantially improve the store layout, hence, can be used in practical applications as a vital decision support model for store layout planning.
... To account for variable store traffic intrinsic to the problem, layout optimization can be carried out considering the shopper paths. As mentioned before, several researchers showed that product exposure, and eventually sales, increase with the increase in the length of shopping paths (Inman et al., 2009;Kholod et al., 2010;Hui et al., 2013). Supported by this finding, Boros et al. (2016) aimed to increase the path length for the average customer in a supermarket. ...
It is well-established that increased product visibility to shoppers leads to higher sales for retailers. In this study, we propose an optimization methodology which assigns product categories and subcategories to store locations and sublocations to maximize the overall visibility of products to shoppers. The methodology is hierarchically developed to meet strategic and tactical layout planning needs of brick-and-mortar retailers. Layouts in both levels of planning are optimized considering eligibility requirements and complete set of shopper paths, thus, they successfully capture the unique shopping behavior of consumers in a store's region. The resulting mathematical optimization problem is recognized as a special instance of the well-known Quadratic Assignment Problem, which is considered computationally as one of the hardest optimization problems. We adopt a linearization technique and demonstrate via a real-world numerical example that our linearized optimization models substantially improve the store layout, hence, can be used in practical applications as a vital decision support model for store layout planning.
Published article available at: https://doi.org/10.1080/01605682.2022.2056532
... A further methodology used to track human trajectories is Radio Frequency Identification (RFID) technology where tags carrying a unique identifier attached to an object (e.g. shopping carts as in Hui, Fader, and Bradlow (2009) ;Kholod, Nakahara, Azuma, and Yada (2010) or conference badge as in Cattuto et al. (2010)) transmit signals captured by a system of pre-installed readers. While those monitoring techniques provide means for reducing expensive manual surveys (Bai, Ireson, Mazumdar, & Ciravegna, 2017), they still suffer from an inability to accurately identify distinct individuals (PIR), require bespoke infrastructure (RFID), are prone to measurement errors in outdoor environments (thermal cameras) or violate the privacy of the pedestrians (video cameras). ...
This paper discusses the opportunities afforded by novel population sensing technologies in the field of ‘smart’ urban management. In particular, it focuses on the application of these new sources of data in retail analysis.
Our goal is to integrate data derived through novel pedestrian counting and point-of-sale systems to build a statistical model that captures the relationship between retail turnover and footfall in the UK. The point-of-sales data are provided by two UK-based food & beverage retailers. To accurately measure the pedestrian activity around retail units, we make use of the data generated by the SmartStreetSensor project: a deployment of a large network of sensors installed across 105 towns and cities in the UK that collect Wi-Fi probe requests generated by mobile devices. We propose and implement novel methods for processing these raw signals into accurate estimates of pedestrian activity without compromising participants' privacy.
The resulting data is then integrated into seasonal ARIMA and dynamic regression models that can be used to predict future sales. Our results indicate that the dynamic regression model that accounts for fluctuations in footfall data outperforms seasonal ARIMA model that uses only past values and behaviours of transaction data to predict future sales. Thus, we conclude that footfall does have a strong impact on retail sales and therefore integrating footfall measures into sales forecasting can significantly improve the forecasting results. We also examine differences between the two retailers and observe a stronger correlation at the Fast Food Retailer locations compared to the correlation at Family Restaurant locations.
... As the experiment takes place in a shopping mall, there is also focus on the value of Bluetooth tracking in a marketing context. Prior research has already pointed at the relation between shopping path lenghts and sales volume for example (Kholod et al., 2010). The analysis is relevant for shopping malls in order to improve their store lay-out. ...
... Several researchers used Radio Frequency Identification (RFID) as a technology for tracking humans (Liao and Lin, 2007;Kanda et al., 2007;Hurjui et al., 2008;Takai and Yada, 2010;Kholod et al., 2010;Fujino et al., 2014;Kaneko and Yada, 2016). Due to its high positional accuracy and its applicability in indoor settings, RFID promises to be a valuable option for tracking customers in a marketing context. ...
... The essence of the matrix is that the position of the firm in economic space is determined, by marked quadrants and depending on this, one of the strategies is recommended. The minimum number of fields (quadrants) is 4, the maximum is theoretically unlimited, but in practice the big amount of them is not used [5]. ...
In this paper we investigate the subject of strategies development by Russian companies through the managerial decision modelling. In the traditional economic model it is assumed that the company exists in order to maximize profits in the long term. Profit determines the viability of a business, and protects the organization from the threat of bankruptcy. We develop strategy development matrix, based on the sales profitability metrics. Furthermore, we apply this methodology to the sample of leading companies of Russia in order to propose the necessary managerial decision in order to pursue the strategy of development of a company.
... Yada 11 developed the character string analysis technique EBONSAI, and showed that the techniques are effective in shopping path analysis. Kholod and Yada 12 considered the influence of the length of shopping path on purchase results, and pointed out that there is a positive correlation between shopping path length and sales. Kaneko and Yada 13,14 introduced the fractal dimension of shopping path as an indicator of the customers' in-store movements, and clarified that the fractal dimension has a positive effect for purchases in the product categories of vegetables, fish and meat. ...
Recent years have seen active research that utilizes information combining geographic data and sensor data, called geospatial information, in urban planning, medical care and marketing. In this study, we focus on RFID technology that records position information (i.e., spatial information) of shopping carts in a supermarket, and estimate the latent space-time structure of the store as observation data of customers’ visits. Then, we propose a dynamic Bayesian model for sales analysis, which extends the conventional state-space model to include the spatiotemporal structure. From the results of the model analysis, it is obvious that supermarkets have clear periodic structures in units of time periods and weekly structures, and they are dynamically related to the adjacency of each sales area. By utilizing the visualization of the space-time structure of the sales area, it is possible to easily inform the store manager about the influence of customers’ visits on sales outcomes.
... In addition, some studies have analyzed customer movement paths or performed customer behavior analysis based on collected sensor data. De Marco et al. 36 analyzed the store operations records of Italian apparel retailers using RFID technology, and Kholod et al. 37 examined the effects of shopping path length in grocery stores on purchase behavior using RFID data. Takai and Yada 30 used RFID data in a Japanese supermarket to derive the relationship between stay-time and purchase probability. ...
Indoor positioning systems have attracted considerable attention from practitioners and firms seeking to optimize the consumer shopping experience with the goal of attaining increased revenue and profitability. Acknowledging the importance of indoor positioning systems in store layout optimization, we conducted a field experiment for 11 months in order to develop algorithms for connecting indoor positioning data with customer transaction data. Using fingerprinting as a primary data collection technique, we compared positioning and transaction data before and after critical store layout optimization decisions in order to identify which customer movement patterns generated the highest sales. In contrast to previous works on indoor positioning systems, which focused solely on developing algorithms or techniques to increase accuracy rates, our algorithms in principle integrate computing and marketing perspectives. Our findings can be applied to store layout optimization and personalized marketing.
... In Kholod (2010), the researcher investigated how the relationship between the distance traveled in the route and the total purchase value. The author found a Pearson correlation coefficient (ρ of P earson) equal to 0.8457, which means that these two quantities have a strong linear dependence. ...
... Customers can also be categorized according to their movements: customers that know what they are looking for and result in straighter paths, compared to customers with more convoluted paths with loops. There are results showing that customers that tend to stay longer in the store are more likely to also buy something, and the basket size buying customers increases with the time spent in the store [9], [10]. Therefore, segmentation based on duration of a customer journey may give further insights. ...
... There are several approaches similar to ours, for instance [14], [10] and [9] use RFID-and Point of Sales-data to visualize the path of each customer on the respective shop layout. Furthermore, they have the advantage of exact location data (x and y coordinates). ...
