Average Retail Price: Clothing: Women's Tights data was reported at 184.250 RSD/Unit in 2016. This records an increase from the previous number of 181.260 RSD/Unit for 2015. Average Retail Price: Clothing: Women's Tights data is updated yearly, averaging 95.270 RSD/Unit from Dec 1996 (Median) to 2016, with 21 observations. The data reached an all-time high of 184.250 RSD/Unit in 2016 and a record low of 6.620 RSD/Unit in 1996. Average Retail Price: Clothing: Women's Tights data remains active status in CEIC and is reported by Statistical Office of the Republic of Serbia. The data is categorized under Global Database’s Serbia – Table RS.P001: Average Retail Prices.

Retail Price Index in Philippines increased to 1.40 percent in August from 0.80 percent in July of 2025. This dataset includes a chart with historical data for Philippines Retail Price Index YoY.

Average Retail Price: Cotton Fabrics: Printed Linen data was reported at 397.970 RSD/m in 2016. This records a decrease from the previous number of 399.330 RSD/m for 2015. Average Retail Price: Cotton Fabrics: Printed Linen data is updated yearly, averaging 231.290 RSD/m from Dec 1996 (Median) to 2016, with 21 observations. The data reached an all-time high of 399.330 RSD/m in 2015 and a record low of 23.910 RSD/m in 1996. Average Retail Price: Cotton Fabrics: Printed Linen data remains active status in CEIC and is reported by Statistical Office of the Republic of Serbia. The data is categorized under Global Database’s Serbia – Table RS.P001: Average Retail Prices.

China Retail Price Index: Urban: Food: Milk and Its Product data was reported at 101.000 Prev Year=100 in 2022. This records a decrease from the previous number of 102.100 Prev Year=100 for 2021. China Retail Price Index: Urban: Food: Milk and Its Product data is updated yearly, averaging 101.300 Prev Year=100 from Dec 1994 (Median) to 2022, with 29 observations. The data reached an all-time high of 134.300 Prev Year=100 in 1994 and a record low of 98.845 Prev Year=100 in 2015. China Retail Price Index: Urban: Food: Milk and Its Product data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Inflation – Table CN.IB: Retail Price Index: Urban: Annual.

This dataset contains data on annual average retail prices of food in Latvia in 1919-1939. Dataset "Annual Average Retail Prices of Food in Latvia, 1913-1939" was published implementing project "Historical Sociology of Modern Restorations: a Cross-Time Comparative Study of Post-Communist Transformation in the Baltic States" from 2018 to 2022. Project leader is prof. Zenonas Norkus. Project is funded by the European Social Fund according to the activity "Improvement of researchers' qualification by implementing world-class R&D projects' of Measure No. 09.3.3-LMT-K-712".

Monthly average retail prices for food, household supplies, personal care items, cigarettes and gasoline. Prices are presented for the current month and previous four months. Prices are in Canadian current dollars.

This dataset contains data on annual average retail prices of non-food goods in Lithuania in 1919-1939. Dataset "Annual Average Retail Prices of Non-Food Goods in Lithuania, 1913-1939" was published implementing project "Historical Sociology of Modern Restorations: a Cross-Time Comparative Study of Post-Communist Transformation in the Baltic States" from 2018 to 2022. Project leader is prof. Zenonas Norkus. Project is funded by the European Social Fund according to the activity "Improvement of researchers' qualification by implementing world-class R&D projects' of Measure No. 09.3.3-LMT-K-712".

U.S. gasoline prices decreased across all fuel grades in July 2025 when compared to the month before. Regular gasoline prices rose to an average of 3.17 U.S. dollars per gallon. In the period of consideration, gasoline prices reached their highest level in June 2022. Differences in fuel grades Fuel grades at U.S. gas stations are differentiated by octane level. Higher grade fuels have higher octane levels, meaning that the fuel can be compressed more in the engine. This enables high-performance engines to create more power. Fuel may also vary from state to state and pump to pump. Some cities also have regulations on gasoline in order to improve air quality. Bioethanol is added to gasoline in some cases to meet the renewable fuel standard. Gasoline-run engines are able to run on blends with a bioethanol percentage of up to 25 percent. Gasoline prices reach historic high Primarily a result of the Russia-Ukraine war and inflation, the annual retail price of gasoline reached a new historic high in 2022, climbing to nearly four U.S. dollars per gallon. By 2024, annual prices had decreased again slightly, reaching 2014 levels.

The statistic shows the year-over-year growth rate of jewelry retail prices in the United States from 2008 to 2018. In 2018, retail prices of jewelry in the United States declined by *** percent compared to the previous year.

Coal retail prices can vary depending on factors such as coal type, location, market demand, and transportation costs. This article explains how the grade of coal, location, market demand, and transportation costs can affect the retail price of coal. It also highlights the importance of considering local market reports and consulting with coal suppliers for accurate pricing information.

Retail Price: Tokyo: Education: PTA Membership Fee: Elementary data was reported at 3,070.000 JPY/Year in Oct 2018. This stayed constant from the previous number of 3,070.000 JPY/Year for Sep 2018. Retail Price: Tokyo: Education: PTA Membership Fee: Elementary data is updated monthly, averaging 3,300.000 JPY/Year from Jan 1999 (Median) to Oct 2018, with 238 observations. The data reached an all-time high of 3,450.000 JPY/Year in Mar 2015 and a record low of 273.000 JPY/Year in Mar 1999. Retail Price: Tokyo: Education: PTA Membership Fee: Elementary data remains active status in CEIC and is reported by Statistical Bureau. The data is categorized under Global Database’s Japan – Table JP.P002: Retail Price: Tokyo.

The global retail pricing software market was valued at USD 12.28 Billion in 2022 and is projected to reach USD 21.89 Billion by 2030, registering a CAGR of 7.5% for the forecast period 2023-2030. Factors Affecting Retail Pricing Software Market Growth

Benefits of Retail pricing software; 

Retail pricing software offers several benefits to businesses, helping them make more informed pricing decisions and ultimately improving their competitiveness, profitability, and customer satisfaction. For instance, retail pricing software leverages vast amounts of data, including historical sales data, customer behavior data, and market trends. In addition, pricing software uses advanced algorithms to calculate optimal prices for products or services. This optimization takes into account factors such as production costs, demand elasticity, competitor pricing, and desired profit margins.

Restraining Factor:

Cost and Complexity of software;

Retail pricing software often involves significant initial costs for implementation, customization, and training. Smaller retailers with limited budgets might find it challenging to invest in such solutions. Additionally, the complexity of these systems might deter some businesses, especially those without dedicated IT resources.

Market Opportunity:

The growing trend of omnichannel retailing;

Omnichannel retailing refers to providing a seamless and integrated shopping experience across various channels, both online and offline. This includes brick-and-mortar stores, e-commerce websites, mobile apps, social media platforms, and more. The goal is to create a consistent and convenient shopping experience for customers regardless of how they choose to interact with the retailer. The rise of omnichannel retailing presents several challenges and opportunities when it comes to pricing strategies. Retailers need to maintain consistent pricing across all channels to avoid customer confusion and frustration.

The COVID-19 impact on Retail Pricing Software Market;

The COVID-19 pandemic had a significant impact on various industries, including the retail pricing software market. The pandemic led to changes in consumer behaviour, with increased online shopping and a shift away from physical stores. The sudden change in consumer behaviour has increased demand for pricing software that could quickly adapt to these shifts. With more consumers turning to online shopping, retailers needed pricing software that could handle the complexities of pricing across multiple online platforms, marketplaces, and channels. Many retailers had to offer promotions and discounts to attract customers during economic uncertainty. Pricing software was crucial for planning and executing these strategies effectively. Introduction of Retail Pricing Software

Retail pricing software is a specialized type of software designed to help businesses, particularly retailers, determine the optimal prices for their products or services. It leverages various data points, algorithms, and analytical tools to assist in setting prices that align with the business's goals, market conditions, customer preferences, and competitive landscape. Retail pricing software gathers a wide range of data from both internal and external sources. his can include historical sales data, customer behaviour data, competitor pricing information, economic indicators, and more. Integration with the business's point-of-sale systems, e-commerce platforms, and other relevant software helps ensure that the data is up-to-date and accurate.

As of December 31, 2020, prices of consumer goods in Belgian supermarket chains registered a significant change compared to March 2020. Collect&Go reported the highest growth, as prices increased by **** percent, followed by Colruyt at **** percent. Conversely, the prices of the retail chain Cora had the biggest decrease, dropping at less **** percent.

Overview \r This report examines Australian and international experience in monitoring farmgate and retail prices for food products. It also outlines a simple methodology to monitor farm shares and farm-to-retail price spreads for food products, and investigates the potential to apply the methodology to Australian data. \r \r Key Points \r • The food retail sector in Australia is highly concentrated while there is increasing consolidation in the food processing sector. There is some concern that this could lead to farmers receiving lower prices and consumers paying higher prices than would be the case in a perfectly competitive market. \r • The paper reviews local and international research in monitoring movements in farm and retail prices for food products, outlines a simple methodology to monitor farm shares and farm-to-retail price spreads for food products, and investigates the potential to apply the methodology to Australian data. \r • The review of international research found significant variation across countries in the importance they place on food price monitoring and analysis. Research has consistently found that the more processed food products are, the lower the farm share, and that farm shares have generally been declining over time. \r • The review also found that the United States Department of Agriculture Economic Research Service (USDA ERS) is a world leader in analysing prices in food supply chains. The paper outlines a relatively simple methodology used by the USDA ERS to monitor changes in farm shares and farm-to-retail price spreads for food products. \r • While there are limitations with the USDA ERS approach, an increase in farm-to-retail price spread or a decrease in farm share of the retail price could be a useful early indicator that competition issues are emerging within a supply chain. However, additional analysis will always be required to confirm whether the cause was an increase in market power because these changes can occur for a number of reasons, including differences in productivity in different sectors or input prices increasing at a faster rate in the retail sector than in the farm sector. Unfortunately, there is generally a lack of data that will allow a breakdown in marketing costs to facilitate this analysis. \r • One option for additional research is to replicate another methodology developed by the USDA ERS, which uses input-output data to decompose costs and profits between different sectors within a supply chain and to estimate returns to primary factors, including capital and labour. This type of analysis would be more expensive than the high-level analysis described in this paper but it would also be more informative than the farm share/price spread analysis in identifying the range of factors influencing prices, and lead to a more informed debate about the various factors influencing prices, including market power. \r

Sugar retail prices can vary widely depending on various factors such as the country, brand, type of sugar, and market demand. Factors affecting sugar retail prices include country and region, brand, type of sugar, market demand and supply, and global market trends. This article provides examples of sugar retail prices in different countries, emphasizing the need to check local stores or online retailers for current prices.

The statistic shows the average domestic retail price of regular gasoline in Shizuoka prefecture, Japan in 2017 and 2018. As of December 2018, the average gasoline retail price stood at around ***** Japanese yen per liter in Shizuoka prefecture, up from around ***** yen in December 2017.

Explore how recent global economic changes, supply chain constraints, and shifts in demand have influenced lumber retail prices, impacting the construction and home improvement sectors. Understand the factors behind the price fluctuations since the COVID-19 pandemic and discover future projections for the lumber market as it adapts to new supply chain norms and sustainable forestry practices.

View weekly updates and historical trends for US Retail Diesel Price. from United States. Source: Energy Information Administration. Track economic data w…

China Retail Price: MoM: Rural Market Fair: Beef data was reported at 1.300 % in Nov 2013. This records an increase from the previous number of 1.200 % for Oct 2013. China Retail Price: MoM: Rural Market Fair: Beef data is updated monthly, averaging 1.100 % from Jan 2009 (Median) to Nov 2013, with 57 observations. The data reached an all-time high of 5.700 % in Jan 2013 and a record low of -1.900 % in Mar 2010. China Retail Price: MoM: Rural Market Fair: Beef data remains active status in CEIC and is reported by Ministry of Agriculture and Rural Affairs. The data is categorized under China Premium Database’s Price – Table CN.PA: Ministry of Agriculture and Rural Affairs: Retail Price: Agricultural Product.

View monthly updates and historical trends for US Consumer Price Index. from United States. Source: Bureau of Labor Statistics. Track economic data with Y…