Lara McBean, Shu Sasaki 

 

Link to Our Infogram: https://infogram.com/info419-project-1hxj48mpnpz052v?live

Link to our Tableau Data Files: https://us-west-2b.online.tableau.com/#/site/infovisubc/projects/549884?:origin=card_share_link

 

Intended Goals

As avid fans of the LEGO brand, our team has been noticing the increasing prevalence of more adult-oriented sets from the LEGO brand in recent years. Advertisements promoting sets for older audiences seem to be on the rise, and the emergence of more themes specifically targeting older audiences such as the LEGO Ideas line or the LEGO ICONS line lead us to suspect this. This move to capitalize on a new market demographic, which seems to be a branching-out from the brand’s primary target of younger audiences, led us to investigate what could have motivated this shift in the brand’s positioning.

 

Actions/tasks supported

From a high-level user-action perspective, we want our intended users to analyze pre-existing data. To do this, our team focused on telling a story with our data; aligning with the present goal (Munzner, 2014, p. 47). The intended users will be able to use the presented data to suit their discovery needs. However, as LEGO as a brand is enjoyed by a wide age range and community of individuals, we also anticipate more casual encounters with our infovis. In order to fulfill an enjoy goal (Munzner, 2014, p. 48) to support the curiosity of this new audience, we included a number of did-you-know style details about specific lego sets that marked a massive turning point in the brand’s history in order to be more educational and entertaining for our intended audiences. 

From a mid-level perspective, each viewer will have different expectations on how they want to approach this InfoVis. As our data hopes to accommodate for a wide user base from casual buyers, parents, avid fans looking to further immerse themselves, amongst many more demographics and age ranges, we feel it important to offer viewers the opportunity to engage however they please. As such, they will be able to browse  (Munzner, 2014, p. 53) the InfoVis to find specific visualizations that are relevant to them. 

From a low-level perspective, we focused our InfoVis on providing users with the data to allow them to compare and summarize the data. We compared multiple data sources and created visualizations to look for correlations. However, we have to provide ample support for comparison in our InfoVis due to our diverse audience, which is why a summary is necessary to provide a comprehensible overview of the data. Our data relies on story narratives, where we guide users to help them understand why we suspect that LEGO is diversifying their demographic to accommodate older demographics in recent years. Our ability to summarize the story allows this visualization to ultimately come together as a cohesive source of data for all audiences. 

The Intended users:

The intended audience for this InfoVis could be the LEGO corporation, parents of young kids, teachers searching for access to educational and creative tools, and avid collectors and fans of LEGO products. The visually intuitive design we aim to create using visual analytics tools should help all of the aforementioned audiences, regardless of their familiarity with the LEGO brand, to effectively understand the data we plan to showcase. Creating an InfoVis that all audiences can interact with is important, especially because we are dealing with the LEGO brand, as 

 

Dataset Details

As LEGO is a private company, they do not have a publicly accessible database that keeps track of the prices of each LEGO set ever sold. As a result, many LEGO fans utilize third-party software created by fans within the LEGO community, such as Brickset and Rebrickable. Websites such as Brickset, created by Huw Millington have been pillars of the LEGO community, cataloging an extensive list of mostly all LEGO set releases ranging as far back as 1949. As such we consider Brickset and Rebrickable’s data sources to be reputable sources of data. 

 

 Github user seankross’s legosets.csv contains a list of 6172 LEGO sets between 1970-2015. This data includes the set’s number, name, year released, Theme, Subtheme, piece count, Minifgures, links to the set’s images on brickset, as well as the Manufacture’s Suggested Retail Price (MSRP) for GBP, USD, CAD, EUR. This data set is extremely valuable, as none of Brickset or Rebrickable readily accessible data files includes the MSRP upon release. We deem seankross’s data to be reliable as their raw data shows that each field was picked from Brickset’s API, and thus is utilizing a data source that we deem is reputable. Utilizing this data set, our team was able to calculate and map out the increase in Price Per Part of each lego set throughout 1970-2015. Price Per Part is an important metric in the LEGO community, as it is a metric to determine if the set can be deemed “worth the price” or “too expensive” to purchase. This data allows our team to understand if LEGO’s increased marketing towards older audiences can be correlated to, if any, an increasing price of manufacturing. This suggested correlation led us to initially set up a hypothesis that a factor in LEGO’s marketing towards adults can be attributed to the fact that adults possess more purchasing power than younger audiences, and may therefore be more forgiving in spending more to purchase LEGO products specifically catered towards them.  

Kaggle.com user JONATHAN KRAAYENBRINK’s LEGO Sets & Themes Database (1949-2023) contains a list of 21,503 LEGO sets from Rebrickable’s API. This data includes each set number, set name, year released, number of parts, image url and the theme of each set. This is helpful when calculating the average size of sets over the years. No dataset broke down each LEGO set released per year by age group, which was required to solve one of the key aspects of our investigation; visualizing how each age group is prioritized over the years. In order to combat this, we looked at the LEGO website to manually record information on their current themes and sets, taking in the total number of sets per theme and the number of occurrences for 18+ sets. LEGO has only introduced the 18+ labeling in 2020, so by comparing the count of these sets to the younger age ranges, we can determine how much LEGO is dedicated to a solely adult audience.

We will also use LEGO’s annual report, which is posted directly onto their website’s ‘About’ section. This has information about the company’s revenue, and highlights the company’s values, and future steps for growth. Also, from 2012, the Lego group also began sharing data of their top performing themes, which is useful in helping us understand LEGO’s customer base by considering the targeted age ranges for each theme. As this data is coming directly from the LEGO company, we can confirm that this data is credible. However, it is potentially susceptible to bias in favor of the company. In order to parse through the data, we manually collected and created a dataset from scratch on Microsoft Excel and utilized Tableau Prep to prepare our dataset for Tableau Desktop and Infogram. 

 

Tools Used

We first utilized Tableau Prep and Tableau Desktop respectively in order to clean and analyze our datasets. By utilizing Tableau Prep’s clean step, we were able to remove unnecessary fields and help us effectively grapple with the gargantuan data sets (over 20,000 rows) we were analyzing. Furthermore, Tableau Desktop allowed us to make sense of the data we were seeing, and allowed us to create custom pills to calculate important metrics such as the Price Per Piece metric, which we utilized to ultimately backup our findings. However, while Tableau Prep and Desktop respectively are useful in the initial visualization processes, they lack the tools to properly incorporate visual narratives in order to tell a cohesive visual story, thus making it a lackluster tool for the scope of our project.

 Once the data had been studied, and key metrics for our data analysis were located, our team exported the data files over to Infogram, where we created a visualization utilizing their interface. While we had initially considered Figma, the data tools we collected felt better represented in the customizability of Infogram, which ultimately led to our decision. Unlike Figma, which lacks the robust infrastructure to handle large data sets and deal with decimals, Infogram’s capacity to incorporate not only eye catching visuals, but seamlessly incorporate texts to guide users allowed us to feel confident that the InfoVis we created could truly be utilized by all intended audiences we account for. 

Analytic Steps

When starting the design process, we were not sure of any specific trends, we only knew about the recent popularity of adult LEGO. We then hypothesized what type of data we should look into to visualize the adult demographic as part of the LEGO market. Some of our ideas included Price per Piece. If there was an increasing trend line, then it might indicate an increase in cost which would deter younger people from purchasing sets. We then thought of the Average Size of Sets Over Time, because it seemed intuitive for larger sets (with more pieces) to be intended for older age groups. We also wanted to explore the popular themes over time because the primary age group for each set is different.  We looked for datasets that had the information we wanted through Google Dataset and used those results as a jumping point to explore the development of 18+ products and how adults were a viable market. However, we were not able to find datasets for themes over time

This led to researching sets admired by AFOLs (Adult Fans of LEGO) before the first instance of an 18+ rating on a LEGO set in 2020. These were particularly the Ultimate Collectors Sets and the LEGO Modulars. Then we looked into how 18+ sets compared to the other ranges since 2020. We also looked into LEGO conventions where older builders could display unique LEGO builds, which indicates how adults are a viable market for the brand.

 

Design Process

We ensured to follow the principles of utility, soundness, and beauty/attractiveness within our infographic through the following: 

• Utility: Our infographic follows the utility of an explorative infographic by providing statistics and facts from reputable sources 
• Soundness: All data was received by reputable data sources from Google Dataset or manually recorded from the official LEGO website
• Beauty/attractiveness: We followed the bright colours fitting of the LEGObrand without reducing the readability from readers

We relied on the visual channels of shape and colour to differentiate between different statistics. The bright colours of red and yellow from the brand are used to accentuate differences in the pie charts and graphs we have made.

 

Story

Through this InfoVis, our team is looking to answer 2 main questions. 1), Has LEGO been increasing the number of LEGO sets targeted towards adult, more advanced builders? 2), If so, what could be a reason for why they are doing so? 

As fans of the LEGO brand ourselves, we’ve noticed the emergence of a new age rating in 2020, the 18+ line, and have been noticing an increase in LEGO sets with larger piece counts, and typically more expensive sets. This diversification in their demographic portfolio, one that is no longer only catering to the main target demographic of children, is a fascinating shift to see for a toy company. 

We answer the aforementioned 2 questions by taking users on a data visualization journey, accompanied by a narrative text that helps guide users to understand why we are using the data. 

We begin the explanation with the brand’s history of creating sets for more advanced builders. From the introduction of the Ultimate Collector Series in 2000, the LEGO® Modular Buildings line in 2007, the most expensive retail LEGO set in history in 2017, to the  introduction of the official 18+ age rating in 2020, LEGO’s has been targeting advanced builders for sometime now. This data is backed up by the annual increase in the percentage of 18+ sets since the introduction of the rating in 2020. 

Given the data that LEGO has been diversifying its portfolio to market towards adults, we provide 2 theories on why they may be doing this: Increase in Manufacturing cost, and Increase in AFOL Demand. Though we are not on the board of directors at LEGO, and therefore cannot know the real intent, we believe that our theories do shine a light on the potential reasonings behind this move. 

Given these findings, we can conclude that there is both an increase in the number of LEGO sets for adults, and that this increase may be due to the rising demand from adult fans of LEGO. 

 

Pros and Cons

Pros:

One of the strongpoints regarding our project is our utilization of narratives to help tell our story in a cohesive manner. Through the inclusion of narrative storytelling that guides users through our thought process, providing entertaining and interesting information about the brand, and imagery to help provide context for our data works as a way to keep audiences engaged with our info visualization, and promotes audiences to scroll through our data to the bottom to learn more. 

 

Cons:

As we are drawing from a diverse range of angles to tackle the question of whether LEGO’s targeting demographics are shifting towards more adult demographics, we acknowledge that one of the potential shortcomings of our designs could be a lack of cohesion in the data presented upon initial viewing. While there may not be the most apparent connection between data of Price per Piece and attendance at BrickCon, we are confident that our narrative can effectively tie these concepts together. We also acknowledge that the increase in attendees to an adult event cannot fully explain the increase in adult interest in the LEGO brand on the whole. While this may be the case, we hope that looking through the multitudes of different data sources can help viewers understand that the reason behind why an industry leading toy manufacturer  may choose to market towards adults is far more nuanced than simply due to a shift in the cost of production. 

 

References:

BrickCon. (1 C.E., January 1). About BrickCon. BrickCon 2024! https://brickcon.org/about-us/ 

 

LEGO System in play. (n.d.). LEGO® History. https://www.lego.com/en-us/history/articles/lego-system-in-play

 

Lankow, Jason, et al. Infographics: The Power of Visual Storytelling, John Wiley & Sons, Incorporated, 2012. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/ubc/detail.action?docID=882721. 

 

KRAAYENBRINK, JONATHAN. LEGO Sets & Themes Database (1949-2023). (2023, August

23). Kaggle. https://www.kaggle.com/datasets/jkraak/lego-sets-and-themes-database/data

 

Munzner, T. (2014). Visualization Analysis and Design. https://doi.org/10.1201/b17511 

seankross. (n.d.). lego/data-tidy/legosets.csv at master · seankross/lego. GitHub. https://github.com/seankross/lego/blob/master/data-tidy/legosets.csv