Market Basket

3 Key excerpts on "Market Basket"

• 

  eBook - ePub

  Marketing Analytics

  A Practical Guide to Improving Consumer Insights Using Data Techniques

  • Mike Grigsby(Author)
  • 2022(Publication Date)
  • Kogan Page

    (Publisher)

  This returns a probability between 0% and 100% for each customer (2.71828 = e). So apply this formula to your database and each customer will have a score (that can be used for a lift chart, see above) for probability to purchase.

  HIGHLIGHT

  USING LOGISTIC REGRESSION FOR Market Basket ANALYSIS

  Abstract

  In general, Market Basket analysis is a backward-looking exercise. It uses descriptive analysis (frequencies, correlation, mathematical key performance indicators (KPIs), etc) and outputs those products that tend to be purchased together. This gives no insights into what marketers should do with that output. Predictive analytics, using logistic regression, shows how much the probability of a product purchase increases/decreases given another product purchase. This gives marketers a strategic lever to use in bundling, etc.

  What is a Market Basket?

  In economics, a Market Basket is a fixed collection of items that consumers buy. This is used for metrics like consumer price index (CPI – inflation), etc. In marketing, a Market Basket is any two or more items bought together.

  Market Basket analysis is used, especially in retail/CPG (consumer packaged goods), to bundle and offer promotions and gain insight in shopping/purchasing patterns. ‘Market Basket analysis’ does not, by itself, describe HOW the analysis is done. That is, there is no associated technique with those words.

  How is it usually done?

  There are three general uses of data: descriptive, predictive and prescriptive. Descriptive is about the past, predictive uses statistical analysis to calculate a change on an output variable (e.g. sales) given a change in an input variable (say, price) and prescriptive is a system that tries to optimize some metric (typically profit, etc). Descriptive data (means, frequencies, KPIs, etc) is a necessary, but not usually sufficient, step. Always get to at least the predictive step as soon as possible. Note that predictive here does not necessarily mean forecasted into the future. Structural analysis uses models to simulate the market, and estimate (predict) what causes what to happen. That is, using regression, a change in price shows what is the estimated (predicted) change in sales.

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  eBook - ePub

  Big Data Analytics

  Applications in Business and Marketing

  • Kiran Chaudhary, Mansaf Alam(Authors)
  • 2021(Publication Date)
  • Auerbach Publications

    (Publisher)

  The analytical model has derived its name from the fact that customers in the supermarket place the purchased items and commodities in their shopping cart or Market Basket. But in the prevailing times, the application of the Market Basket analytical concept is not limited to supermarkets. Instead, it can be applied to any industry and sector that involves selling a broad range of items such as banking institutions, direct marketers, and cataloguers and to new sales channels, especially the internet.

  (Blattberg, Kim, & Neslin, 2008)

  Several studies have been carried out exploring how the MBA tool is deployed in retail contexts, supermarkets, or multiple store settings. Chen et al. (2005) have conducted a study to examine MBA in multiple store settings. The method has been used to discover customer buying patterns by extracting the cooccurrences from the stores’ transaction database. But, while performing the analysis, a number of barriers could arise that could restrict the ability to capture important assumptions. For example, in the study, one assumption that acts as a barrier is that it is believed that the commodities under consideration are on the stores’ shelf at all times. In order to make optimum use of the analytical tool in the multi-store setting, it is necessary to address several elements that could act as obstacles. For instance, the buying pattern’s temporal nature needs to be considered, as it could act as an issue while using MBA. Temporal rules have come into existence to overcome the weaknesses associated with the static association rules that consider that patterns remain consistent over time or locate patterns at a specific point in time. It is necessary to address the issue while applying the analytical method or one may generate biased results (Chen et al., 2005, p. 2).

  3.3 Role of Market-Basket Analysis in the Business Setting

  Studies indicate that the MBA model’s application sheds light on marketers’ rich and useful information. In his work, Li has suggested that the analytical model is of high relevance for manufacturers as it helps them position their commodities and goods in the market setting. The role of MBA in the business setting is important as it captures valuable quantity and time information that helps produce insightful results (Blattberg, Kim, & Neslin, 2008). The usefulness of the MBA approach is considered an integral component of the analytical system in diverse business settings such as retail entities. The analysis that revolves around technology plays a cardinal role as it helps marketers operating in the ever-evolving business setting to make a diverse range of strategic decisions. Some of the decisions like ascertainment of the placement of commodities and designing suitable sales promotions for diverse customer segments improve customer satisfaction. Hence, the analytical process can help strengthen a business’s profit (Annie & Kumar, 2012).

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  eBook - ePub

  Getting Prices Right

  Debate Over the Consumer Price Index

  • Dean Baker(Author)
  • 2016(Publication Date)
  • Routledge

    (Publisher)

  As could be inferred from the discussion above about the complexities of a modern dynamic capitalist economy, the CPI program is a complex and difficult undertaking. To make it manageable, the BLS applies a simplified view of the marketplace and consumer behavior. This simplified view is reflected throughout the CPI approach. It takes expenditures for a fixed Market Basket of goods and services at some point in the past, called the base or reference period, and estimates what it would cost today to purchase the same Market Basket. The formula used to construct the CPI, called Laspeyres, assumes that purchases are made in fixed quantities based on decisions from some previous period’s experience. In other words, the CPI attempts to answer the question, “what is the cost, at this month’s market prices, of purchasing the same Market Basket actually purchased in the base period?” Since the Laspeyres formula does not allow for the substitution of products or services in response to current prices and choices, it is an “upper bound” to a cost of living.

  The Market Basket consists of total expenditures on items directly purchased by all urban consumers, that is, food, clothing, shelter and fuels, transportation, medical services, and other goods and services that people buy for day-to-day living. The BLS uses scientific sampling techniques to select specific items. The BLS measures the price changes in these items over time. The sample design involves a multistage process for sampling by geographic area, retail outlet, item category, and individual goods and services within an outlet and category.

  Several samples are used to try to make the CPI representative of the prices paid by consumers: urban areas selected from all U.S. urban areas, consumer units within each selected area, outlets from which these consumer units purchased goods and services, specific items — goods and services — purchased by these consumer units, and housing units in each urban area (for the shelter component of the CPI). The key sources of information used to determine the items which comprise the Market Basket and the outlets at which prices are to be collected are the Consumer Expenditure Survey (CES) and the Point-of-Purchase Survey (POPS).

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