Automated price adjustment system

Project Abstract

Automated price adjustment systems have become increasingly prevalent in the retail industry as a way to dynamically respond to market conditions and consumer behaviors. These systems leverage advanced algorithms and data analytics to continuously monitor factors such as competitor pricing, inventory levels, and customer demand to make real-time pricing decisions. By automating this process, retailers can optimize their pricing strategies, increase competitiveness, and maximize profits. This research project aims to develop a comprehensive automated price adjustment system for a large e-commerce platform. The system will be designed to handle a vast amount of data and make pricing decisions at scale while taking into account various factors that influence pricing dynamics. The system will utilize machine learning algorithms to analyze historical sales data, competitor pricing, and market trends to predict optimal price points for products. Real-time data streams will be integrated to ensure that the system can quickly respond to changes in the market environment. One of the key challenges in developing an automated price adjustment system is ensuring its accuracy and reliability. This research project will focus on validating the system through extensive testing and simulations to evaluate its performance under different scenarios. By analyzing the system's output against actual market outcomes, we aim to fine-tune the algorithms and parameters to improve the system's accuracy and effectiveness. Another important aspect of the research project is to ensure that the automated price adjustment system is user-friendly and transparent for retailers. The system will provide clear insights into the pricing decisions it makes, allowing retailers to understand the rationale behind the recommended price adjustments. Additionally, the system will offer customization options for retailers to set constraints and preferences based on their business goals and strategies. Overall, the development of an automated price adjustment system has the potential to revolutionize the way retailers manage pricing strategies. By harnessing the power of data analytics and machine learning, retailers can make more informed pricing decisions, react quickly to market changes, and stay ahead of the competition. This research project aims to contribute to the advancement of automated pricing systems and provide valuable insights for retailers looking to implement these technologies in their operations.

Project Overview

<p> </p><div><p><strong>INTRODUCTION</strong></p><p><strong>1.0 Introduction</strong></p><p>The phenomenon of price adjustment is central in economics for several reasons. First, at the microeconomic level, since price adjustment is considered the main market clearing mechanism, whether prices adjust or not can have important implications for the efficiency of resulting allocations. Therefore, having a better understanding of the price change process can provide insights on issues like: how rigid are prices of individual products; how fast are costs passed-through onto prices; how long it takes prices to adjust to changes in market conditions such as changes in supply and demand, etc. Second, at the managerial level of an individual business, pricing and price adjustment play a critical role as it determines the bottom line profitability. For example, questions such as: how to adjust prices of individual products in response to temporary cost increases, how to adjust prices to competitors’ price changes, how to adjust prices of sale and non-sale items, how frequently to change prices, etc., are all questions pricing managers and retail sellers face on a daily basis. Third, there are variety of markets (e.g. different types of auction markets, non-auction markets such as markets with posted prices, etc.), and understanding the specific characteristics of these institutions may help us better understand and predict the outcomes observed at these markets. Given the importance of the price adjustment mechanism, it is not surprising that the issue has received considerable theoretical as well as empirical attention.</p><p><strong>1.1 Theoretical Background</strong></p><p>The introduction of computerized technology into the retail environment over the past two decades has resulted in new opportunities for retailer managers. For example, demand based management uses statistical models to predict consumer price response using historical information. The most prevalent type of information in retail markets is transaction data collected using optical bar code scanners which track every item purchased by a consumer at the point-of-sale. This data could potentially contain a wealth of information about how consumers respond to price and promotions. A price adjustment management system is a computerized system that aids in adjusting the price of products based on different variables such as cost price, transportation, taxes and commissions on products and competitors prices. This is done such that an optimal price is ascertained that still brings about a certain percentage of profit.</p><p>Most supermarket chains carry thousands of items in different categories, operate scores of stores, constantly adjust prices on a weekly basis due to changes in demand, supply, and competition, and may manage wholesale and retail operations. Price adjustment systems are meant to help managers make decisions, but they also serve to help automate decision making. Pricing specialists agree that businesses should price products based on value. Yet, many companies set prices based on the cost of their product (Ulaga, 2001; Hinterhuber, 2008). Alternatively, they set prices based on the prices of competing products, without fully accounting for the worth of performance differences between their product and the reference products.</p><p></p><p>In a research study aimed at identifying specific obstacles that prevent companies from implementing value-based pricing strategies Hinterhuber (2008) found that the number one obstacle was the ability to conduct an accurate value assessment. One respondent commented that his business team just did not have the tools to attach a financial value to their differentiated product.</p><p><strong>1.2 Statement of Problem</strong></p><p>Many supermarket owners do not have an effective method of adjusting price tags such that they increase their revenue and attract customers. There are many competitors in the market place and this influences the level of patronage especially if they are good in managing prices. In addition, the situation of charging higher than normal may also reduce demand and consequently bring about loss. This situation brings about the need for a price adjustment software system that can enable the adjustment of price of each product such that there is no loss or excess profit and also to provide avenue for updating price of items.</p><ul><li><strong>Aim And Objectives of the Study</strong></li></ul><p>The aim of the study is to develop an automated price adjustment system for supermarket. The following are the specific objectives:</p><ul><li>To develop an automated price adjustment system that can aid in the adjustment of prices of products.</li><li>To develop a system that will allow the easy storage, retrieval and updating of prices of each registered product.</li><li>To develop a system that will replace the manual way of managing prices of products</li><li>To implement a system that the database can be queried easily.</li><li></li></ul></div><div><p>1<strong>.4 Scope of the Study</strong></p><p>This study covers automated price adjustment system for supermarket, a case study of NTEPS supermarket.</p><p><strong>1.5 Significance of the Study</strong></p><p>The significance of the study is that it will provide solution to the problem of adjusting price of products in NTEPS supermarket, it will serve as a management information system for super market owners. The study will also serve as a useful reference material to other researchers seeking information on the subject.</p><p><strong>1.6 Organization of the Research</strong></p><p>This research work is organized into five chapters. Chapter one is concerned with the introduction of the research study and it presents the preliminaries, theoretical background, statement of the problem, aim and objectives of the study, significance of the study, scope of the study, organization of the research and definition of terms.</p><p>Chapter two focuses on the literature review, the contributions of other scholars on the subject matter is discussed.</p><p>Chapter three is concerned with the system analysis and design. It analyzes the present system to identify the problems and provides information on the advantages and disadvantages of the proposed system. The system design is also presented in this chapter.</p><p>Chapter four presents the system implementation and documentation. The choice of programming language, analysis of modules, choice of programming language and system requirements for implementation.</p><p>Chapter five focuses on the summary, conclusion and recommendations are provided in this chapter based on the study carried out.</p><p><strong>1.7 Definition of Terms</strong></p><p><strong>Adjust: </strong>To make slight changes in something to make it fit or function better</p><p><strong>Management:</strong>&nbsp;the organizing and controlling of the affairs of a business or a sector of a business</p><p><strong>Price:</strong>&nbsp;The amount, usually of money, that is offered or asked for when something is bought or sold.</p></div> <br><p></p>