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The purpose of this paper is to examine commonly relied upon product sampling strategies, direct‐to‐consumer sampling and event sampling, to determine which method can deliver the greatest return on investment in a variety of situations.

The paper explores information and data collected via case studies in actual programs presented to brands. The trial, sample, and purchase numbers were actual averages from sampling effectiveness studies for these types of programs.

The paper identifies and segments different types of products and the method by which the products are most effectively implemented into trial and sampling programs. ICOM reveals hard statistics on the return on investment of programs utilizing multiple methods of sampling including point‐of‐use, direct mail and event sampling.

Marketers should follow the STEPS outlined in this study to apply the best brand sampling strategy for a given product. Knowledge of targeted consumer base along with careful pre‐event analysis will deliver the best return on investment for a trial campaign.

The paper reveals reasons for a growing shift in corporate budgeted marketing dollars from event marketing to direct consumer product sampling. While event sampling is not always an ineffective or inferior marketing method,the reader can discover methods for a pre‐event return on investment analysis that will reveal the sampling strategy sure to deliver the most “bang” for the marketing “buck”.

This paper aims to investigate the impact of in‐store sample promotions of food products on consumer trial and purchasing behavior. The authors investigate differences in the trial rate for free samples across different products and consumer types, as well as the impact of sampling on product and category purchase incidence. The results of this study are relevant for retailers and manufacturers who invest in in‐store free sample promotions.

The authors use data from a field study, which leveraged an actual free‐sample program implemented by a US grocery store chain. Data was collected on six different products promoted by in‐store free samples over six different weekends. The data collected included consumers' trial and purchasing behavior with respect to the free sample, as well as their attitudes towards the free sample that day and free sample promotions in general.

Free sampling is very effective in inducing trial, especially among lower educated consumers. For consumers who are planning to buy the product in the promoted category, free sampling can encourage switching from the planned to the promoted brand. For consumers who do not have such previous plans, free sampling can “draw“ them into the category and encourage category purchase. Samplers' interactions with the person distributing the sample or with other samplers at the scene also seem to boost post‐sample purchase incidence.

Despite the importance of free samples as a promotional tool, few studies have examined consumer trial and purchasing behavior with respect to in‐store free samples. This paper presents one of the first known field studies that examines this topic.

The purpose of this paper is the determination of reliability sampling plans in the Bayesian approach assuming that the lifetime distribution is exponential.

Sampling plans are used in manufacturing companies as a tool for carrying out sampling inspections, in order to make decisions about the disposition of many finished products. If the quality characteristic is considered as the lifetime of the products, the plan is known as a reliability sampling plan. In life testing, censoring schemes are adopted in order to save time and cost of life test. The inverted gamma distribution is employed as the natural conjugate prior to the average lifetime of the products. The sampling plans are developed assuming various probability distributions to the lifetime of the products.

The optimum plans n and c are obtained for some sets of values of (p1, a, p2, ß). The selection of sampling plans is illustrated through numerical examples.

Results obtained in this paper are original and the study has been done for the first time in this regard. Reliability sampling plans are essential for making decisions either to accept or reject based on the inspection of the sample.

The goals of this paper are to determine the effectiveness of product sampling in terms of usage, to draw a consumer profile who is reactive to free samples and to determine product characteristics that would lead to free samples usage.

An experiment and a questionnaire inquiry were conducted. An outlet database was also used. Perfume, skin care and make‐up samples were given away to 500 women. In order to test the hypotheses logit models were employed.

Launching product sampling campaigns is quite effective as free samples usage appears to be high (72 per cent). Managers should give away samples of new products involving important advertising budgets. They also should offer samples of product types with a high‐penetration rate. In addition, it is better to sample well‐known brands rather than unknown ones. Moreover, the authors recommend targeting family brand users when offering free samples. Also, it is not profitable to target consumers with low‐annual spending within the product category. Finally, the authors suggest giving away samples to non‐working housewives.

This is the first paper to examine the determinants of free samples usage. Moreover, the study considers three methods of data collection. Finally, it has interesting practical and theoretical implications.

The purpose of this paper is to design a modified version of the double sampling plan to handle the inspection processes requiring a minimum sample size to assure the median life for the products under the new Weibull–Pareto distribution. The economic design of the proposed plan is also considered to assure the product's lifetime with minimum cost.

The authors have developed an optimization model for obtaining the required plan parameters by solving simultaneously two non-linear inequalities and such inequalities have been formed based on the two points on the operating characteristic curve approach.

The results show that the average sample number, average total inspection and total inspection cost under the proposed plan are smaller than the same of a single sampling plan. This means that the proposed plan will be more efficient than a single sampling plan in reducing inspection effort and cost while providing the desired protection.

The proposed modified double sampling plan designed to assure the median life of the products under the new Weibull–Pareto distribution is not available in the literature. The proposed plan will be very useful in assuring the product median lifetime with minimum sample size as well as minimum cost in all the manufacturing industries.

The purpose of this project was to explore and identify factors that influence a consumer to purchase wine during an afternoon of product sampling (wine tasting). A panel of consumers was recruited for an afternoon of wine tasting at vineyards in Napa, California. Several potential hedonistic, utilitarian and logistical factors (i.e. winery facilities, quality of the wine and order in which the winery was visited) were measured using a journal log that was maintained by participants following the tasting experience for a period of one‐month. The conclusions drawn from this study were that group size, confidence in one's ability to purchase wine and overall assessment of a vineyard's wine portfolio were more important than the hedonistic factors in terms of inducing a sale immediately following a taste.

The purpose of this paper is to propose a new mixed repetitive group sampling (RGS) plan based on the process capability index, C_pk, where the quality characteristics of interest follow the normal distribution with unknown mean and unknown variance. Tables are constructed to determine the optimal parameters for practical applications for both symmetric and asymmetric fraction non-conforming cases. The advantages of this proposed mixed sampling plan are also discussed. The proposed sampling plan is also compared with other existing sampling plans.

In order to determine the optimal parameters of the proposed mixed RGS plan based on C_pk, the authors constructed tables for various combinations of acceptable and limiting quality levels (LQLs). For constructing tables, the authors followed the approach of two points on the operating characteristic (OC) curve. The optimal problem is formulated as a non-linear programming where the objective function to be minimized is the average sample number (ASN) and the constraints are related to lot acceptance probabilities at acceptable quality level and LQL under the OC curve.

The proposed mixed RGS plan will be a new addition to the literature of acceptance sampling. It is shown that the proposed mixed plan involves minimum ASN with desired protection to both producers and consumers compared to other existing sampling plans. The practical application of the proposed mixed sampling plan is also explained with an illustrative real-time example.

In this paper, the authors propose a new mixed RGS plan based on the process capability index C_pk, where the quality characteristic of interest follows the normal distribution with unknown mean and unknown variance. Tables are constructed to determine the optimal parameters for practical applications. The proposed mixed sampling plan can be used in all production industries. This kind of mixed RGS plan is not available in the literature.

Describes a study of consumer behaviour carried out in a chocolate store involving free samples of chocolate, which found that sampling significantly increased the immediate sales of chocolates but that this effect was restricted to small amounts and to those varieties of chocolate other than the variety sampled. Discusses the implications of the findings for marketing management and consumer behaviour theory. Concludes that while sampling produces positive effects, these effects appear to be more complex than they would first seem, therefore further consumer research is needed.

Examines the practice and marketing consequences of giving out free food samples. Reports on a study, taken over a period of three days, of customers who entered a well‐established, ten‐year‐old chocolate store in a major suburban shopping mall, who received a free sample of chocolate. Shows that sampling immediately increased the sale of chocolates. Cautions that this positive effect was restricted to small purchases and to the purchase of chocolate varieties other than the variety sampled. Discusses the implications of the findings for marketing management and for consumer behaviour theory.

Acceptance sampling plans are a decision-making process on the basis of a randomly selected sampling from a party, where it is not possible to completely scan the products for reasons such as time and cost being limited or the formation of damaged products during the inspection. For some products, the life span (time from beginning to failure) may be an important quality characteristic. In this case, the quality control adequacy of the products can be checked with an acceptance sampling plan based on the truncated life test with a censored scheme for the lifetime of the products. In this study, group acceptance sampling plans (GASPs) based on life tests are studied under the Type-I censored scheme for the compound Weibull-exponential (CWE) distribution.

GASPs based on life tests under the Type-I censored scheme for the CWE distribution are developed by using both the producer's risk and the consumer's risk.

In this study, optimum sample size, optimum number of groups and acceptance number are obtained under the Type-I censored scheme for the CWE distribution. Real data set illustration is given to show GASPs how to be used for the industry applications.

Different from acceptance sampling plans with just considering the producer's risk, GASPs are constructed by using two-point approach included both the producer's risk and the consumer's risk for CWE distribution.