VHB 2015: A, AJG 2018: 4, ABDC 2019: A*

Abstract

This research presents a retail analytics application which uses machine learning (ML) to identify and predict under- and overperforming consumer packaged goods (CPGs) using retail scanner data. Essential to measuring market performance at the SKU level is the relationship between distribution and market share (the velocity curve). We validate that ML can reproduce the velocity curve, and ML is further used to predict underperforming, in-line performing, and overperforming SKUs relative to the velocity curve, based on a range of variables (SKU features) at a point in time. Our ML approach can correctly predict 83% of SKUs as under-, in-line-, or overperforming based on their characteristics. The research analyzes 9,321 SKUs of 2,565 brands across seven product categories of CPGs which were sold in 8,117 stores from 49 different retail chains of five different retail channels located in the US states of California, New York, Texas, and Wisconsin. The retail stores comprise convenience stores, drug stores, food stores, liquor stores, and mass merchandise retail stores. The data is Nielsen retail store scanner data for the calendar year 2014. The relationship between distribution and market share is a market-wide proxy for the ratio of relative sales in a category to, for example, aggregate shelf space, a key retail productivity metric. We further find indications that the distribution of SKUs across different store sizes, the stores’ category specialization, the line length of the brands, the overall performance of the parent brand, and sales consistency are the most important characteristics for the prediction of market share performance beyond the velocity curve. The methods and results presented will help CPG marketers (suppliers and retailers) understand which SKUs are under-, in-line-, or overperforming and the potential factors contributing to that performance. Optimizing assortments and portfolios is essential to decrease failure rates of individual SKUs. ML approaches can evolve to complementary support tools for such management problems.

More: https://doi.org/10.1016/j.jretai.2021.04.002

VHB 2015: C, AJG 2018: 2, ABDC 2019: A

Abstract

This study investigates the relationship between distribution and market share across various consumer packaged goods (CPG) categories and specific stock keeping units (SKUs). The study identifies product-related characteristics that result in substantive deviations above or below market shares predicted by the distribution – market share relationship. The association of product price, brand (private label [PL] v. national brand [NB]) and pack size with above (or below) expected market share for a given distribution level is analysed. Results indicate larger pack sizes, PL and medium price levels result in market share above what would be predicted by an SKU’s distribution. This presents a source for competitive advantage in markets driven by push–pull dynamics.

More: https://doi.org/10.1016/j.jretconser.2021.102533

ABDC 2019: B

Purpose

Little research on the influence of external factors, such as weather and holiday periods, on retail sales on alcoholic beverages is available. This study aims to investigate how weekly retail sales of different alcoholic beverages vary in association with daily maximum temperatures and annual federal holidays across selected US counties in the years 2013 to 2015. The research provides information, which can contribute to better sales forecasts.

Design/methodology/approach

Secondary data of weekly retail sales (volume) of alcoholic beverages from 37,346 stores in 651 counties in the USA are analysed. The data cover on average 21% of all existing US counties and 12% of the total US off-trade retail sales of alcoholic beverages in the period studied (Euromonitor, 2017). Additional data of federal holidays and meteorological data are collated for each county in the sample. Seasonal autoregressive integrated moving average models with exogenous regressors (SARIMAX) are applied to develop forecasting models and to investigate possible relationships and effects.

Findings

The results indicate that off-trade retail sales of beer, liquor, red and white wine are temperature sensitive throughout the year, while contrary to expectations rosé, sparkling and other wines are not. Sales sensitivities to temperature also differ by geography. In the warmest regions, liquor and white wine sales do not respond to temperature changes, as opposed to the coolest regions, where they are responsive. Public holidays, particularly Easter, Thanksgiving, Christmas and New Year holidays, represent a constant influencing factor on short-term sales increases for all investigated alcoholic beverage categories.

Originality/value

This is the first large-scale study of weather and holiday-related sales variations over time, across geographies and different alcoholic beverage categories. Seasonal and non-seasonal short-term sales variations are important for retailers and manufacturers alike. Accounting for expected changes in demand accommodates efficiencies along the supply chain and has implications for retail management, as well as adjusting marketing efforts in competing categories.

Read more: https://doi.org/10.1108/IJWBR-07-2020-0035

AJG 2018: 2, ABDC 2019: A

This study's purpose is to conceptualise a wine regional destination's perceived image, in the process integrating multiple theories such as servicescape, place-based and destination choice. The research (n = 334 respondents) outlines the conceptualisation of a wine region destination's image in the form of a winescape framework as perceived by visitors. The winescape construct is identified within a framework of eight dimensions for a well-known US wine region. The most important winescape dimension is the natural beauty/geographical setting. The first-time and repeat visit dynamic impacts upon visitors' wine tourism behaviour and perception of the region's winescape. For in-state and out-of-state-based visitors there are pronounced differences in their perception of the region's winescape dimensions. Increasing distance from the destination region is pivotal in the perception of the winescape dimensions. The decision to engage in wine tourism is seemingly impulsive from a timing viewpoint, and the motivations guiding the visitors' behaviour are mainly of a hedonic nature.

Further reading: https://doi.org/10.1080/13683500.2014.904846

ABDC 2019: B

Purpose

The purpose of this study is to measure the product involvement of wine buyers and to examine relationships with anticipated consumption situations, places and occasions combined with the buyer’s importance of various extrinsic product attributes.

Design/methodology/approach

A survey is conducted with 147 wine buyers using structured self-administered questionnaires in a central city retail location in Australia.

Findings

There are no significant relationships between consumers’ involvement with wine products and what occasion or constellation of persons is anticipated when purchasing wine in a retail store. From a consumption situation perspective, both high- and low-involved buyers primarily anticipate consuming their wine together with other persons, mainly with food. High-involved wine consumers tend to consume their wine alone compared to low-involved consumers who are more likely to buy wine for other persons than for themselves. Regarding the product attributes that play an important role in retailing, this study finds that the importance of grape variety, the origin of the wine, the brand, the vintage, awards/medals and the product design increases with growing involvement in wine. The age of the buyer/consumer and the envisaged consumption occasion also affect the importance of various product attributes. We also find that wine buyers would spend on average over $15 more per unit when the wine is not bought for their personal consumption (e.g. gift).

Originality/value

This study is of value to academic researchers, the wine industry in general and wine retailers in specific as it offers new insights on the role of product involvement and anticipated consumption situations when buying a product and their effects on the importance of product attributes.

Read more: http://dx.doi.org/10.1108/IJWBR-01-2014-0007