Kiilto – Price Elasticity in the Category of Household Cleaning Products

Kiilto is a Finnish family company that produces solutions for the chemical industry in four different business areas. Kiilto is the market leader, especially in consumer-oriented household cleaning products. To respond even better to the changing needs of consumers with its product range, Kiilto wanted to deepen the understanding of consumer behaviour in this category. We started to seek the understanding especially in the factors guiding consumers’ purchase decisions, shopping experience and the navigation on the store shelf, while also aiming to gain information about the price sensitivity of consumers in the category.

Through many phases to a holistic understanding

At nSight, we got to create holistic understanding together with the Kiilto team. A comprehensive understanding was formed through a multi-phase research, where the depth of analysis was sought by utilizing more advanced quantitative methods, such as structural equation modeling, Conjoint and MaxDiff analyses. Quantitative surveys were also combined with elements of behavioural research by using the virtual store environment. In this internationally widely used method, respondents are directed to shop in a virtual hypermarket, where the real shopping experience and store behaviour can be imitated in a cost-effective manner. Through the section focusing on purchase decisions, the understanding of how consumers make decisions in the category and what the shopping experience and navigation on the shelf look like was deepened.

Price elasticity research creates certainty for decision-making

As part of the research, we carried out a price elasticity study using Conjoint analysis. Conjoint analysis is the most reliable way of studying the effect of pricing on product demand. In the so-called ‘choice based conjoint’ analysis, consumers are not asked directly which price they find most attractive or how much they are willing to pay, but consumers are placed in a situation that simulates a real choice situation, where they make choices between different product features and price points. This diversity produces clearly more diverse and reliable data compared to asking them directly. The analysis makes it possible to predict changes in demand if the price or other studied product characteristics change. Through the analysis, it was possible to determine the optimal price for Kiilto’s cleaning sprays from the perspective of consumer demand.