Price optimization

Last updated

Price optimization is the use of mathematical analysis by a company to determine how customers will respond to different prices for its products and services through different channels. [1] It is also used to determine the prices that the company determines will best meet its objectives such as maximizing operating profit. [1] The data used in price optimization can include survey data, operating costs, inventories, and historic prices & sales. [2] Price optimization practice has been implemented in industries including retail, banking, airlines, casinos, hotels, car rental, cruise lines and insurance industries. [3] [4] [5] [6]

Overview

Price optimization utilizes data analysis to predict the behavior of potential buyers to different prices of a product or service. Depending on the type of methodology being implemented, the analysis may leverage survey data (e.g. such as in a conjoint pricing analysis [7] ) or raw data (e.g. such as in a behavioral analysis leveraging 'big data' [8] [9] ). Companies use price optimization models to determine pricing structures for initial pricing, promotional pricing and discount pricing. [10]

Market simulators are often used to simulate the choices people make to predict how demand varies at different price points. [11] This data can be combined with cost and inventory levels to develop a profitable price point for that product or service. [12] This model is also used to evaluate pricing for different customer segments by simulating how targeted customers will respond to price changes with data-driven scenarios. [10]

Price optimization starts with a segmentation of customers. A seller then estimates how customers in different segments will respond to different prices offered through different channels. [13] Given this information, determining the prices that best meet corporate goals can be formulated and solved as a constrained optimization process. [1] [14] The form of the optimization is determined by the underlying structure of the pricing problem. [1] [14]

If capacity is constrained and perishable and customer willingness-to-pay increases over time, then the underlying problem is classified as a yield management or revenue management problem. [1] [14] If capacity is constrained and perishable and customer willingness-to-pay decreases over time, then the underlying problem is one of markdown management. If capacity is not constrained and prices cannot be tailored to the characteristics of a particular customer, then the problem is one of list-pricing. If prices can be tailored to the characteristics of an arriving customer then the underlying problem is sometimes called customized pricing. [1] [14]

Related Research Articles

<span class="mw-page-title-main">Marketing</span> Study and process of exploring, creating, and delivering value to customers

Marketing is the process of exploring, creating, and delivering value to meet the needs of a target market in terms of goods and services; potentially including selection of a target audience; selection of certain attributes or themes to emphasize in advertising; operation of advertising campaigns; attendance at trade shows and public events; design of products and packaging attractive to buyers; defining the terms of sale, such as price, discounts, warranty, and return policy; product placement in media or with people believed to influence the buying habits of others; agreements with retailers, wholesale distributors, or resellers; and attempts to create awareness of, loyalty to, and positive feelings about a brand. Marketing is typically done by the seller, typically a retailer or manufacturer. Sometimes tasks are contracted to a dedicated marketing firm or advertising agency. More rarely, a trade association or government agency advertises on behalf of an entire industry or locality, often a specific type of food, food from a specific area, or a city or region as a tourism destination.

<span class="mw-page-title-main">Supply chain</span> System involved in supplying a product or service to a consumer

In commerce, a supply chain is a network of facilities that procure raw materials, transform them into intermediate goods and then final products to customers through a distribution system. It refers to the network of organizations, people, activities, information, and resources involved in delivering a product or service to a consumer. Supply chain activities involve the transformation of natural resources, raw materials, and components into a finished product and delivering the same to the end customer. In sophisticated supply chain systems, used products may re-enter the supply chain at any point where residual value is recyclable. Supply chains link value chains. Suppliers in a supply chain are often ranked by "tier", with first-tier suppliers supplying directly to the client, second-tier suppliers supplying to the first tier, and so on.

Brand equity, in marketing, is the worth of a brand in and of itself – i.e., the social value of a well-known brand name. The owner of a well-known brand name can generate more revenue simply from brand recognition, as consumers perceive the products of well-known brands as better than those of lesser-known brands.

Multichannel marketing is the blending of different distribution and promotional channels for the purpose of marketing. Distribution channels include a retail storefront, a website, or a mail-order catalogue.

<span class="mw-page-title-main">Conjoint analysis</span>

Conjoint analysis is a survey-based statistical technique used in market research that helps determine how people value different attributes that make up an individual product or service.

<span class="mw-page-title-main">Service economy</span>

Service economy can refer to one or both of two recent economic developments:

Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns toward effective decision-making. It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance.

Managerial economics is a branch of economics involving the application of economic methods in the managerial decision-making process. Economics is the study of the production, distribution and consumption of goods and services. Managerial economics involves the use of economic theories and principles to make decisions regarding the allocation of scarce resources.

Yield management is a variable pricing strategy, based on understanding, anticipating and influencing consumer behavior in order to maximize revenue or profits from a fixed, time-limited resource. As a specific, inventory-focused branch of revenue management, yield management involves strategic control of inventory to sell the right product to the right customer at the right time for the right price. This process can result in price discrimination, in which customers consuming identical goods or services are charged different prices. Yield management is a large revenue generator for several major industries; Robert Crandall, former Chairman and CEO of American Airlines, gave yield management its name and has called it "the single most important technical development in transportation management since we entered deregulation."

Dynamic pricing, also referred to as surge pricing, demand pricing, or time-based pricing, is a pricing strategy in which businesses set flexible prices for products or services based on current market demands. Businesses are able to change prices based on algorithms that take into account competitor pricing, supply and demand, and other external factors in the market. Dynamic pricing is a common practice in several industries such as hospitality, tourism, entertainment, retail, electricity, and public transport. Each industry takes a slightly different approach to dynamic pricing based on its individual needs and the demand for the product.

Revenue management is the application of disciplined analytics that predict consumer behaviour at the micro-market levels and optimize product availability, leveraging price elasticity to maximize revenue growth and thereby, profit. The primary aim of revenue management is selling the right product to the right customer at the right time for the right price and with the right pack. The essence of this discipline is in understanding customers' perception of product value and accurately aligning product prices, placement and availability with each customer segment.

The following outline is provided as an overview of and topical guide to marketing:

Marketing mix modeling (MMM) is statistical analysis such as multivariate regressions on sales and marketing time series data to estimate the impact of various marketing tactics on sales and then forecast the impact of future sets of tactics. It is often used to optimize advertising mix and promotional tactics with respect to sales revenue or profit.

Rule-developing experimentation or RDE is a systematized solution-oriented business process of experimentation that designs, tests, and modifies alternative ideas, packages, products, or services in a disciplined way using experimental design, so that the developer and marketer discover what appeals to the customer, even if the customer can't articulate the need, much less the solution.

Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. Marketing provides services in order to satisfy customers. With that in mind, the productive system is considered from its beginning at the production level, to the end of the cycle at the consumer. Customer analytics plays an important role in the prediction of customer behavior.

<span class="mw-page-title-main">Customer experience</span> Interaction between an organization and a customer

Customer experience (CX) is a totality of cognitive, affective, sensory, and behavioral consumer responses during all stages of the consumption process including pre-purchase, consumption, and post-purchase stages. Pine and Gilmore described the experience economy as the next level after commodities, goods, and services with memorable events as the final business product. Four realms of experience include esthetic, escapist, entertainment, and educational components.

Demand forecasting is known as the process of making future estimations in relation to customer demand over a specific period. Generally, demand forecasting will consider historical data and other analytical information to produce the most accurate predictions. More specifically, the methods of demand forecasting entails using predictive analytics of historical data to understand and predict customer demand in order to understand key economic conditions and assist in making crucial supply decisions to optimise business profitability. Demand forecasting methods are divided into two major categories, qualitative and quantitative methods. Qualitative methods are based on expert opinion and information gathered from the field. It is mostly used in situations when there is minimal data available to analyse. For example, when a business or product is newly being introduced to the market. Quantitative methods however, use data, and analytical tools in order to create predictions. Demand forecasting may be used in production planning, inventory management, and at times in assessing future capacity requirements, or in making decisions on whether to enter a new market.

Pricing science is the application of social and business science methods to the problem of setting prices. Methods include economic modeling, statistics, econometrics, mathematical programming. This discipline had its origins in the development of yield management in the airline industry in the 1980s, and has since spread to many other sectors and pricing contexts, including yield management in other travel industry sectors, media, retail, manufacturing and distribution.

Operations management for services has the functional responsibility for producing the services of an organization and providing them directly to its customers. It specifically deals with decisions required by operations managers for simultaneous production and consumption of an intangible product. These decisions concern the process, people, information and the system that produces and delivers the service. It differs from operations management in general, since the processes of service organizations differ from those of manufacturing organizations.

SIMALTO – SImultaneous Multi-Attribute Trade Off – is a survey based statistical technique used in market research that helps determine how people prioritise and value alternative product and/or service options of the attributes that make up individual products or services.

References

  1. 1 2 3 4 5 6 Phillips, Robert L. (2005). Pricing and Revenue Optimization. Stanford, CA: Stanford University Press. p. 35. ISBN   9780804746984.
  2. ↑ Alina Tugend (April 8, 2014). "As data about drivers proliferates, auto insurers look to adjust rates". The New York Times. Retrieved July 7, 2015.
  3. ↑ Alex Dietz (September 6, 2012). "Revenue management vs. price optimization:part two". SAS. Retrieved July 7, 2015.
  4. ↑ Bob Tedeschi (September 2, 2002). "Scientifically priced retail goods". The New York Times. Retrieved July 7, 2015.
  5. ↑ Anne Kadet (May 2008). "Price profiling" (PDF). The Wall Street Journal Magazine. Archived from the original (PDF) on 2015-07-07. Retrieved July 7, 2015.
  6. ↑ Kim S. Nash (April 30, 2015). "Carnival strategy chief bets that big data will optimize prices". The Wall Street Journal. Retrieved July 7, 2015.
  7. ↑ Smallwood, Richard (October 1, 1991). "Using conjoint analysis for price optimization". Quirk's Marketing Research Review. Retrieved September 27, 2018.
  8. ↑ Leslie Scism (February 20, 2015). "Loyalty to your car insurer may cost you". The Wall Street Journal. Retrieved July 7, 2015.
  9. ↑ Perakis, Georgia (2016-07-25). "A Revolutionary Model To Optimize Promotion Pricing". Huffington Post. Retrieved 2018-10-01.
  10. 1 2 "Price optimization models". Bain & Company. June 10, 2015. Retrieved July 7, 2015.
  11. ↑ "Use Discrete Choice Simulator to Launch the Right Product | Infosurv". Infosurv. 2012-08-03. Retrieved 2018-09-27.
  12. ↑ Arie Shpanya (2015) "Test Until Your Price is the Best"
  13. ↑ Arie Shpanya (2014) "There's No Such Thing As One Right Price in Retail"
  14. 1 2 3 4 Özer, Özalp; Phillips, Robert (2012). Models of Demand" in The Oxford Handbook of Pricing Management. Oxford University Press. ISBN   978-0-19-954317-5.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.