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In the context of omnichannel distribution development, this study aims to understand how and why trying products out helps people make good purchase decisions (i.e. decisions that they do not regret later).

The paper uses mixed methods consisting of an experiment (n = 162), a series of interviews with consumers (n = 16) and in-store observations (n = 202).

Results show that trying products out allows us to evaluate how they will fit, which increases purchase intention. They also indicate that trying leads to better decision-making.

This paper enriches product trial literature and sheds new light on how sales channels combine in omnichannel distribution.

The conclusions of this research will be useful to retailers who want to help consumers make better purchasing decisions.

Helping consumers make better decisions minimizes the societal impact of consumption by reducing the frequency of re-purchases and product returns.

The originality of this research lies in using mixed methods, providing a complete understanding of why consumers try products out and how they do so.

Seeks to study the effect of a low‐price guarantee (PG) on store price image and store patronage intention. Two kinds of low‐price guarantee are studied: a price‐matching guarantee (PMG) where the price difference is refunded and a price‐beating guarantee (PBG) where a retailer offers an additional compensation.

A questionnaire is used to collect information on 180 non‐student respondents in an experimental framework where low‐price guarantee dimension is manipulated through three advertisements for printers.

Findings are: first, that PG indeed lowers store price image, increases the confidence that the store has lower prices and increases patronage intention; second, that, compared with a PMG whose effects are positive but rather small, a PBG further lowers the store price image on the low prices dimension without increasing the intention to search for lower price, this intention being already rather high in the PMG condition; third, that a larger effect is observed for non‐regular customers.

Research limitations are associated with the data collection. For greater reality the study uses an existing retail chain, so specific effects coming from this chain could influence the results but this bias cannot be evaluated as the experiment involves one retailer only.

Practical implications are that price image can be manipulated without any change in pricing policy by a low‐price guarantee and that the interest to adopt a price‐beating guarantee is real.

The contribution of this study lies in its focus on a large PBG level that retailers already apply and in demonstrating that a PG depends on the relationship between the consumer and the retailer with a stronger effect on non‐regular customers.