What is Product Pricing Data? Examples, Datasets and Providers

Product Pricing Data Use Cases in Detail

Here are the main uses of pricing data:

1. Open pricing opportunities – Pricing data can sport opportunities for generating extra revenue and quick wins while also identifying errors in pricing policies.

2. Develop promotional effectiveness – Pricing data enables the research of market dynamics and customer data to predict chances of high profitability by rolling out promotions.

3. Redefining pricing strategy – Businesses and marketers use pricing data to redefine their pricing plan depending on market dynamics, product availability, customer preferences, revenue objectives, etc.

How Do Marketers Use Pricing Data to Develop Pricing Strategies?

Marketers for business entities can use of commercial pricing data for data analysis as far as determining when prices for their products should change. Market place data helps marketers to track down the changes in demand and supply for their given range of products. If the information from the data marketplace shows a significant drop in the sales of certain products, marketers can make use of this trend to lower the prices of the products or employ other marketing strategies, such as temporary promotional discount to encourage a positive shift in the demand pattern.

How is Product Pricing Data collected?

Product pricing data is collected from various historical and current consumer datasets, as well as from goods and production databases from across in the world. Product pricing data is also obtained from sources such as manufacturing industries, demand and supply reports, industrial authorities, economists, government regulatory, import and export reports, historical production reports of goods produced, end-of-day prices, the high and low prices, demand and supply reports for the past year etc.

What Are the Attributes of Product Pricing Data?

The main attributes of pricing data cover consumer products pricing data and industrial product pricing data. Here they are described in more detail:

Consumer products pricing data : This is the type of pricing data that covers pricing details of consumer products (products that a consumer buys for his/her personal needs) like toothpaste, groceries, textiles, computers, and other household products. Consumer products pricing data can be further categorized into the following types:

1. Convenience products pricing data.
2. Shopping products pricing data.
3. Specialty products pricing data.

Industrial products pricing data : This is the type of pricing data covers pricing details of industrial products (products bought for company use) like the raw materials, machines, tools etc. Industrial products pricing data is furthermore described in the following types:

1. Machine parts pricing data.
2. Capital items pricing data.
3. Business and supplies pricing data.

What is Pricing Data Analysis?

Pricing data analysis is a concept that is founded within the realms of big data analytics. Pricing data analysis, also referred to as pricing analytics, are the metrics and the related tools that are applied by pricing data analysts to comprehend how pricing activities have a direct bearing on the entire business by assessing the profitability of specific price points, and optimize a business’s pricing strategy for maximum revenue. Pricing analysis helps business proprietors make better decisions on pricing analytics from an informed point of view and build an accurate picture of the market situation. Pricing data analysis is a continuous process that ought to be undertaken by any business to excel in a given industry. It is against this backdrop that such businesses are encouraged to acquire pricing data from data providers either through payments for pricing data subscriptions.

How to Analyze Pricing Data?

Ecommerce has meant that modern day consumers are no longer your typical brick and mortar era consumers, because they know how to analyse prices of items before buying them and matching with the right value for the product. Marketers also have to keep up to date with the changes in pricing their products as they’re sold. Price data analysis is therefore a critical component of marketing that sellers should take into account.

Generally, pricing data analysis involves the following steps:

• Defining the competition - top-ranked competitors are most likely viewed as providers of the best deal. It is imperative that a business proprietor takes the time and analyse how their prices compare with the competition. A business proprietor can access competitor price data by deciding to buy pricing data from price data vendors, or buy pricing data online from internet-based providers of such data.

• Calculating price index - the purpose of determining price index is to find out the average market price of a given product. The involves using historical pricing data and real-time pricing data to determine trends and patterns in competitor price behavior.

What is a Pricing Data Model?

A pricing data model is a system that is designed to reveal in greater detail the pre-existing relationship between database tables that contain information about pricing. These database tables are made up of individual subunits of price models which are the basic structures and methods for the determination of prices. As such, when choosing which models best fits a given firm, factors such as the industry of operation, competitive position and economic strategy come into play. Firms can buy pricing datasets to help them better assess which pricing models are best for the specific industries in which they operate.

What Are Methods of Asset Pricing?

Asset pricing methods are largely comprised of two major components, general equilibrium asset pricing and the rational asset pricing. The general equilibrium method encompasses the determination of price based on market pricing that is driven by the forces of demand and supply. Guided by market clearing initiative, the equilibrium asset pricing method establishes prices and how they influence the requirements of the quantities of every asset and the quantities supplied. On the other hand, rational pricing is the presumption in financial economics that asset prices (hence asset pricing models) will reflect the arbitrage-free price of the assets as any change in this price will be “arbitraged away”. It is the most commonly used pricing model for fixed income securities such bonds, and is critical to the pricing of derivative instruments. In most cases, businesses would rather not waste a lot of time using these methods to determine asset pricing. It’s for this reason that commercial pricing datasets are available to offer pre-determined asset pricing for businesses. Thus, businesses can shop for pricing data from these online databases and use it when needed, an effort that saves time and resources.

How Can I Assess the Quality of Pricing Data?

High-quality pricing data refers to the datasets that allow your to carry out your strategies effectively. Low-quality data rarely leads to successful results. There are lots of good approaches that you can use to ensure the quality of your pricing data:

• Rate of Data to Errors: Check how many mistakes there are relative to the size of the data set.
• Check the number of Negative Values: Negative values show when there is information is missing from a data set.
• Amount of Dark Data: Check how much data is unusable due to data quality problems.
• Data Time-to-Value: Check how long does it take for you to get value from data, based on integration and analytics?

What is Evaluated Pricing?

Evaluated pricing refers to attempts made by businesses to acquire a fair valuation of individual securities as a result of available information combined with analytical approaches of varying degrees of sophistication. The information used for this approach can be obtained by businesses through purchasing pricing data from commercial providers. An evaluated price can vary greatly, depending on their sources from the providers of such data. The quality and consistency of evaluated pricing data are the core determinants of the price of pricing data that is determined by data providers.