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1) Data Introduction • The Wholesale customers Data Set is a customer analytics dataset that tabulates annual spending by product category for wholesale distributor customers.
2) Data Utilization (1) Wholesale customers Data Set has characteristics that: • Each row contains annual expenditures for each of the customer's regions, channels (retail/hotel/restaurant/café, etc.), and fresh food, milk, grocers, frozen food, detergent, and deli. • The data reflects customer spending patterns in different industries and regions to suit customer segmentation, clustering, marketing analytics, and more. (2) Wholesale customers Data Set can be used to: • Customer segmentation and cluster analysis: Define different customer groups based on product-specific spending patterns and use them to establish targeted marketing strategies. • Sales Strategy and Demand Forecast: Use category-specific annual expenditure data to apply to product-specific demand forecasting, inventory management, and development of customized promotion strategies.
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Summary statistics of wholesale customers data.
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Analysis of ‘ Wholesale customers Data Set’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/binovi/wholesale-customers-data-set on 28 January 2022.
--- Dataset description provided by original source is as follows ---
The dataset refers to clients of a wholesale distributor. It includes the annual spending in monetary units (m.u.) on diverse product categories
Source: UCI Wholesale customers Data Set
--- Original source retains full ownership of the source dataset ---
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
The dataset refers to clients of a wholesale distributor. It includes the annual spending in monetary units (m.u.) on diverse product categories
Source: UCI Wholesale customers Data Set
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The data set refers to clients of a wholesale distributor. It includes the annual spending in monetary units (m.u.) on diverse product categories.
1) FRESH: annual spending (m.u.) on fresh products (Continuous); 2) MILK: annual spending (m.u.) on milk products (Continuous); 3) GROCERY: annual spending (m.u.)on grocery products (Continuous); 4) FROZEN: annual spending (m.u.)on frozen products (Continuous) 5) DETERGENTS_PAPER: annual spending (m.u.) on detergents and paper products (Continuous) 6) DELICATESSEN: annual spending (m.u.)on and delicatessen products (Continuous); 7) CHANNEL: customers’ Channel - Horeca (Hotel/Restaurant/Café) or Retail channel (Nominal) 8) REGION: customers’ Region – Lisnon, Oporto or Other (Nominal) Descriptive Statistics:
(Minimum, Maximum, Mean, Std. Deviation)
FRESH ( 3, 112151, 12000.30, 12647.329) MILK (55, 73498, 5796.27, 7380.377) GROCERY (3, 92780, 7951.28, 9503.163) FROZEN (25, 60869, 3071.93, 4854.673) DETERGENTS_PAPER (3, 40827, 2881.49, 4767.854) DELICATESSEN (3, 47943, 1524.87, 2820.106)
REGION Frequency Lisbon 77 Oporto 47 Other Region 316 Total 440
CHANNEL Frequency Horeca 298 Retail 142 Total 440
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Performance comparison of different model based clustering methods on wholesale customers data.
This dataset was created by kKamal_2003
During the period from February 24 to March 1, 2020, new customers accounted for 1.51 percent of BJ's Wholesale Clubs sales. This figure was up from 1.25 percent between January 1 and February 23, showing that established customers and not only new members of these stores are responsible for store traffic. The coronavirus pandemic has led to increased bulk purchasing of staple goods amongst consumers, which fits the business model of stores such as wholesale clubs.
For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.
This dataset was created by Kirollos Ashraf
This statistic shows the total number of Mobile Virtual Network Operator (MVNO) and M2M wholesale customers of T-Mobile US from the first quarter of 2011 to the fourth quarter of 2019. In the fourth quarter of 2019, T-Mobile USA had a total number of ***** million wholesale customers.
COS Water Service Areas and Wholesale Customers
The statistic shows the distribution of wholesale revenue in Brazil in 2018 and 2019, by business model and type of wholesale customer. The source analyzed wholesaling companies in four business models: B2B distribution, delivery wholesale, over-the-counter wholesale and self-service wholesale. In Brazil, the revenue generated by wholesale sales to small-sized supermarkets accounted for ** percent of the total wholesale revenue in the B2B distribution business model.
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France BS: Wholesale Trade: sa: Expected Selling Price to Customers data was reported at 11.200 % Point in Nov 2018. This records a decrease from the previous number of 12.500 % Point for Sep 2018. France BS: Wholesale Trade: sa: Expected Selling Price to Customers data is updated monthly, averaging 10.500 % Point from Jul 1979 (Median) to Nov 2018, with 237 observations. The data reached an all-time high of 79.900 % Point in Jul 1981 and a record low of -12.400 % Point in Mar 2009. France BS: Wholesale Trade: sa: Expected Selling Price to Customers data remains active status in CEIC and is reported by French National Institute for Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.S012: Business Survey: Wholesale Trade Sector.
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Retail Sales of Consumer Goods: Year to Date: Wholesale & Retail Trade: Shaanxi: Xianyang data was reported at 48.992 RMB bn in Dec 2015. This records an increase from the previous number of 12.187 RMB bn for Mar 2015. Retail Sales of Consumer Goods: Year to Date: Wholesale & Retail Trade: Shaanxi: Xianyang data is updated monthly, averaging 13.554 RMB bn from Feb 2008 (Median) to Dec 2015, with 44 observations. The data reached an all-time high of 48.992 RMB bn in Dec 2015 and a record low of 3.392 RMB bn in Feb 2008. Retail Sales of Consumer Goods: Year to Date: Wholesale & Retail Trade: Shaanxi: Xianyang data remains active status in CEIC and is reported by Xianyang Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HE: Retail Sales of Consumer Goods: Prefecture Level City: Wholesale & Retail Trade: Monthly.
In the United States, consumer spending in wholesale clubs increased by ***** percent in the week ending on ************* compared to the same week in 2020. However, consumer spending registered a significant growth (** percent) when compared to pre-pandemic levels, in the same week in 2019.
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Retail Sales of Consumer Goods: Wholesale Retail Trade: Yunnan: Honghe data was reported at 24.425 RMB bn in 2014. This records an increase from the previous number of 20.737 RMB bn for 2013. Retail Sales of Consumer Goods: Wholesale Retail Trade: Yunnan: Honghe data is updated yearly, averaging 9.447 RMB bn from Dec 2005 (Median) to 2014, with 9 observations. The data reached an all-time high of 24.425 RMB bn in 2014 and a record low of 4.475 RMB bn in 2005. Retail Sales of Consumer Goods: Wholesale Retail Trade: Yunnan: Honghe data remains active status in CEIC and is reported by Honghe Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HI: Retail Sales of Consumer Goods: Wholesale & Retail Trade: Prefecture Level Region.
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License information was derived automatically
Retail Sales of Consumer Goods: Wholesale Retail Trade: Yunnan: Dali data was reported at 23.546 RMB bn in 2014. This records an increase from the previous number of 20.424 RMB bn for 2013. Retail Sales of Consumer Goods: Wholesale Retail Trade: Yunnan: Dali data is updated yearly, averaging 9.641 RMB bn from Dec 2005 (Median) to 2014, with 9 observations. The data reached an all-time high of 23.546 RMB bn in 2014 and a record low of 5.344 RMB bn in 2005. Retail Sales of Consumer Goods: Wholesale Retail Trade: Yunnan: Dali data remains active status in CEIC and is reported by Dali Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HI: Retail Sales of Consumer Goods: Wholesale & Retail Trade: Prefecture Level Region.
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Graph and download economic data for Index of Wholesale Prices of Finished Goods, Consumer Durables for United States (M04212USM350NNBR) from Jan 1947 to Dec 1966 about finished, wholesale, durable goods, consumer, goods, price index, indexes, price, and USA.
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Graph and download economic data for Index of the Wholesale Prices of Finished Goods, Consumer, Other Nondurables for United States (M04215USM350NNBR) from Jan 1947 to Dec 1966 about finished, wholesale, nondurable goods, consumer, goods, price index, indexes, price, and USA.
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The size of the Wholesale Telecom Carrier Market was valued at USD 19942.01 million in 2023 and is projected to reach USD 42833.49 million by 2032, with an expected CAGR of 11.54% during the forecast period. A wholesale telecom carrier is a telecommunications company that provides network services, infrastructure, and bandwidth to other telecom providers, enterprises, or resellers rather than directly to end-users. These carriers operate extensive networks, often encompassing international or regional fiber-optic systems, satellite connections, and other critical telecommunications infrastructure. Their primary role is to serve as intermediaries, enabling retail telecom providers and businesses to deliver voice, data, and internet services to their customers. The wholesale telecom carrier market provides essential services such as voice termination, SMS messaging, VoIP solutions, data roaming, and international call services to other telecom operators, mobile network operators, and internet service providers. Recent developments include: In July 2023, Wholesale provider Deutsche Telekom Global Carrier has announced the launch of a new Point-of-Presence (PoP) in Miami, Florida, hosted within Equinix's data center. The PoP, hosted within the renowned Equinix data centre, offers bandwidths of 1/10/100 gigabits per second (n x 1, n x 10, n x 100 Gbps). According to the official statement, this expansion aims to strengthen Deutsche Telekom's global IPX and IP network footprint. In November 2023, LotusFlare has recently announced that it has in strategic technology relationship with T-Mobile to deliver additional business and technical capabilities to T-Mobile wholesale customers using LotusFlare Digital Network Operator® Cloud (DNO™ Cloud). In May 2023, UK broadband provider Onestream has announced that it has signed a strategic agreement with BT Wholesale, under which it will be able to offer customers connections through BT's FTTP and single SoGEA network. . Key drivers for this market are: INCREASING DEMAND FOR DATA, CLOUD AND DIGITAL SERVICES 40, AFFORDABLE TARIFFS, WIDER AVAILABILITY, AND COST OF COMMUNICATION 40. Potential restraints include: DECLINE IN INTERNATIONAL VOICE TRAFFIC 41, THE WHOLESALE BUSINESS IS OVERLY MATURE 42; INFLATION-DRIVEN THREATS LEAD THE LIST OF EVOLVING EXTERNAL PRESSURES 42; CHANGING REGULATORY LANDSCAPE 43.
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1) Data Introduction • The Wholesale customers Data Set is a customer analytics dataset that tabulates annual spending by product category for wholesale distributor customers.
2) Data Utilization (1) Wholesale customers Data Set has characteristics that: • Each row contains annual expenditures for each of the customer's regions, channels (retail/hotel/restaurant/café, etc.), and fresh food, milk, grocers, frozen food, detergent, and deli. • The data reflects customer spending patterns in different industries and regions to suit customer segmentation, clustering, marketing analytics, and more. (2) Wholesale customers Data Set can be used to: • Customer segmentation and cluster analysis: Define different customer groups based on product-specific spending patterns and use them to establish targeted marketing strategies. • Sales Strategy and Demand Forecast: Use category-specific annual expenditure data to apply to product-specific demand forecasting, inventory management, and development of customized promotion strategies.