MICS

Clustering is an unsupervised data analysis technique that involves grouping a set of objects in such a way that objects in the same group (cluster) are more similar to each other than to those in other groups. This technique is widely used to discover inherent groupings or structures within data.

The primary goal of clustering is to partition a dataset into meaningful subgroups based on similarity measures. By identifying these clusters, researchers and practitioners can gain insights into the underlying patterns and characteristics of the data.

Understanding and quantifying consumer perceptions is a critical step in market analysis. These perceptions, which reflect consumers' attitudes, beliefs, and evaluations regarding products, brands, or services, can be measured through various data collection methods. Questionnaires and surveys are common instruments used to gather data on consumer preferences, opinions, and the importance they attribute to different product or service attributes.

Once data on consumer perceptions are collected, clustering techniques can be applied to segment the consumer base. This process involves grouping consumers with similar perceptual profiles into distinct segments. By analyzing the characteristics of each segment, companies can tailor their strategies, such as product development, marketing campaigns, and communication, to better meet the specific needs and preferences of different consumer groups.

• Cluster 1 – Heritage and Aesthetics Seekers:
  This cluster stands out for its strong emphasis on design and Made in Italy labeling, with the latter ranking the highest across all clusters. This group also assigns relatively high importance to the technical features of the products, suggesting attention to quality and functionality. However, ethical standards and environmental impacts are given the least importance, indicating that sustainability-related concerns are secondary in their purchasing decisions of furniture products. Brand and price hold moderate relevance.
  In the barplot, grey bars represent the observed frequencies in the overall sample, while the colored bars refer to the observed frequencies within the specific cluster.


• Cluster 2 – Ethically-minded Performance Seekers:
  This cluster is characterized by a strong preference for design and technical features, with the former ranking the highest across all groups. This cluster is also characterized by considerable importance assigned to aspects related to the environmental impact and ethical standards associated with the furniture product. Conversely, it assigns the least importance to the brand and to price, suggesting that product characteristics outweigh economic and brand-related considerations.
  In the barplot, grey bars represent the observed frequencies in the overall sample, while the colored bars refer to the observed frequencies within the specific cluster.


• Cluster 3 – Price-driven Pragmatists:
  This cluster prioritizes design and technical features. What distinguishes this group is the great importance assigned to price, which is the third most important factor for this group, indicating a more cost-sensitive and pragmatic consumer. Environmental impact and ethical standards hold moderate importance and brand is ranked among the factors holding the least importance.
  In the barplot, grey bars represent the observed frequencies in the overall sample, while the colored bars refer to the observed frequencies within the specific cluster.


• Cluster 4 – Brand Enthusiasts:
  This cluster is characterized by a strong focus on design and technical features, with price and brand ranking also high. The brand plays an important role in the decision making process of this group, being the highest rank assigned among all clusters. Yet, environmental and ethical considerations are of less concern, suggesting their preferences are driven more by quality and image rather than by sustainability.
  In the barplot, grey bars represent the observed frequencies in the overall sample, while the colored bars refer to the observed frequencies within the specific cluster.


• Cluster 5 – Conscious Buyers:
  This cluster stands out for its strong emphasis on ethical standards and environmental impact, among the highest of all groups. It also assigns relatively high importance to technical features, while scoring low on brand, and price, and ranking last for the importance attributed to design, confirming that moral and environmental concerns guide their purchasing behavior.
  In the barplot, grey bars represent the observed frequencies in the overall sample, while the colored bars refer to the observed frequencies within the specific cluster.

The example presented here illustrates a specific application of clustering to consumer perception data. Successfully applying and interpreting clustering techniques in other contexts requires tailored analytical approaches and the expertise of skilled professionals to ensure that the findings are both valid and relevant for the specific business objectives.