Exploring Trends in LEGO Sets: Analyzing Themes Using Machine Learning

by Shivam Kashyap

LEGO sets through the analysis of data accrued on themes, colours, and components of the various LEGO sets over the past few decades. Hence, through an assessment of the development of the LEGO products, the purpose of this paper is to identify some typical patterns and improve an understanding of customers’ demands as well as LEGO’s strategies for innovation.

Our methodology involves:

  1. Data Collection: Accumulating all sorts of information about LEGO sets and incorporating the data on themes, colours, parts, and dates.
  2. Descriptive Statistics: Descriptive statistics to determine the dispersion and variation of LEGO sets with the passage of time.
  3. Visualization: Subgrouping the data and presenting them in the form of figures so as to give emphasis on trends and changes in the themes, colors and parts among others.

Some of the most important trends are identified; for instance, there is an increase in the number of themes and the introduction of new colours and components to diversify the process of constructing. Also, we see shifts in dominant themes, thus reflecting changes in consumers’ tastes and different cultural trends.

These concepts have managerial implications for the further patterns of LEGO’s product line and promotional activities and thus help the firm to better understand the market and stream its

creations after consumers’ demands. The paper adds insight to lego lovers and collector hence giving a detailed explanation about the evolution of LEGO sets. Additionally, the study contributes to the existing literature on the concept of innovation and creativity in the toys business, focusing on the key causes of successes and sustainability.

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