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The Lego Group
MARKET RESEARCH PROPOSAL
Name: Tan Ying Yin, Evangeline Word Count: 2976 words
With close to 90 years of expertise in the toy industry, The Lego Group (Lego) is a globally recognized best-selling toy manufacturer. Founded by Ole Kirk Kristiansen in 1932, Lego has grown from a small carpenter's workspace to a multinational company that is now one of the world's leading toy producers. Its interlocking bricks offers a one-of-a-kind design with unlimited building possibilities.
With the mission 'Inspire and develop the builders of tomorrow’, LEGO Group focuses on fostering children's creative thinking and logical reasoning, as well as unleashing their capacity to build their future via System-in-Play, letting them experience the limitless human potential. Lego is undeniably a toy industry powerhouse, with a vast spectrum of products ranging from toys to movies. However, with the rapid advancement of technology and digital gadgets, Lego is now pitted against not only toy producers, but also technology and gaming firms. Furthermore, because of the current Covid-19 pandemic, which has caused many people to stay at home owing to restrictions, many families are turning to digital screens and smartphones.
As a result, Lego is interested in learning what kind of products might appeal to children in the next 5 to 10 years. They are also interested to know which type of marketing strategies can be used to promote their sustainable efforts, as well as the future possibilities of expanding their retail store network.
Our proposal intends to understand more of our customer’s opinions regarding Lego. Particularly, we want to observe Lego customers’ view on the toy industry. Following up with their feedback, we analyse strategies that Lego can consider implementing in the future.
To come up with a set of ways to achieve Lego’s objectives, we first identify our Research Aims (RA). Thereafter, we create Research Questions (RQ) followed by Research Objectives (RO) to gain a deeper knowledge of each aim we have. Finally, the research methodology which includes the statistical techniques used for each objective will be provided in detail, accompanied by sampling design, recommended timeline and budget.
With our recommended sampling design, the study will have optimal coverage, ensuring that every region within the population is represented. The project held remotely also simplifies the data collection process, enabling the study to be completed within Lego’s 4-month timeframe. We believe that this research proposal will allow us to contribute new insights that will help The Lego Group explore future possibilities. We feel that understanding not just the consumers' perspective but also constructing a lucrative strategy in the long run is critical for Lego to thrive.
Table of Contents
Named “Toy of the Century” twice1, The Lego Group (Lego) has gone a long way in the past almost 90 years. Sold across almost 130 countries, Lego is one of the most famous and frequently played toys in the world and has become a globally recognised brand with its Lego Brick. In recent years, Lego has also expanded its product line to include movies, games, competitions, and theme parks.
In this growing digitalized society, it is no doubt that the toy industry will continuously evolve to compete with the rising demand for digital gameplay. The increasing trend of children using mobile devices for entertainment has also put Lego against technology and gaming firms (Reed, 2018), especially with children’s screentime increasing by 500% during the pandemic (Yao, 2020).
Lego’s huge success also comes with a hefty carbon impact. Every year, Lego releases roughly a million tons of carbon dioxide(CO2), approximately three-quarters originating from unprocessed materials used in production (Eshkenazi, 2018). With the increasing awareness of climate change and impacts of plastics and CO2, consumers are more conscious when making purchases. (Emmert, 2021)
Our main goal would be to investigate and understand Lego’s target audiences and products and assess the future potential of our next step, to bolster Lego's future profitability and brand perception. We understand your concern with sustaining growth and market share in the toy industry in the face of rapid technological advancements. We also understand that knowing your customers and developing effective strategies are important objectives for you.
1 Lego website: https://www.lego.com/en-sg/aboutus/lego-group/the-lego-group-history/
With the detailed client brief, we have identified three important Research Aims:
For the above RAs, we have proposed a few Research Questions as follow: For RA1:
For RA2:
For RA3:
For each RQ, we have proposed Research Objectives to fulfil the client’s goals.
For RQ1.1:
For RQ1.2:
For RQ2:
For RQ3:
The market research objective involves the composition of exploratory, descriptive, and causal research. This allows us to further understand the market situation in an overall balanced perspective due to the uncertainty brought upon by the pandemic, affecting factors such as demands and shipping in the toy industry2.
The exploratory research allows us to delve deeper into the subject, obtaining meaningful insights relating to the doubts and concerns of respondents. Descriptive research provides an in-depth understanding by effectively investigating relevant variables and relationships statistically. Causal research examines and establishes possibilities of cause-and-effect relationships when implementing marketing strategies to promote to consumers.
To achieve quantitative and qualitative inputs, Online Surveys and Focus-Group studies will be conducted to achieve our primary data collection. In occurrences where potential research design errors may arise, we will engage both focus-groups with two moderators each to minimise interview errors. Monetary incentives are given to minimise the possibility of non-response errors, which increases the willingness of participants to participate, thereafter raising the overall response rate. (Toepoel & Schonlau, 2017)
Also, related variables such as Age and Age-Group will be reclassified to facilitate the analytical process.
2 Pandemic affecting toy industry: https://www.cnbc.com/2021/10/06/how-toy-companies-are-grappling-with-shipping-delays-this-holiday.html
With the time constraint of 4-months set by The Lego Group, we suggest implementing a cross-sectional design for our research. This approach, as compared to longitudinal design, which requires a longer time and fixed subject, allows us to gather information for Lego on our target market and compare multiple variables concurrently. Thereafter, establishing the possibilities of connections and associations between certain variables. (Institute for Work & Health, 2015)
Statistical techniques such as SPSS are used for analysing data. For each Research Objective, we propose the following statistical technique and tests:
R.O.1.1 – 2-Way ANOVA
R.O.1.2 – Focus Group (Duelling-Moderator)
R.O.2.1 – Focus Group (Dual-Moderator)
R.O.2.2 – Paired T-Test
R.O.3.1 – Multiple Linear Regression
R.O.3.2 – Contingency Table
Variables | Data |
Product Types | Categorical Nominal |
Age-Group | Categorical Ordinal |
Preference of products | Continuous |
Brand Perception before and after promoting | Categorical Ordinal |
Gender | Categorical Nominal |
Age | Continuous |
Household Size | |
Average Monthly Household Income | |
Region of Residence | Categorical Nominal |
Opinions towards visiting Lego’s retail store | Categorical Ordinal |
Preferential mode of purchase for Lego products | Categorical Nominal |
To determine the sample size for our market research, we advise adopting a two-step sampling technique. First, Stratified Sampling will be used to select the target population by region, followed by Simple Random Sampling (SRS). The regions are stratified as followed:
North America
South America
Europe
Asia-Pacific (including China)
Middle East & Africa
The official Lego website provides the region stratification3. We also considered Cluster Sampling, but since people of different countries and regions likely vary in play patterns and parenting methods (Ringen, 2015), stratification will ensure higher accuracy with all regions represented.
3 Lego regions available: https://www.lego.com/en-us/service/help/online_shop/changing-region-versions-of-legocom-kA009000001dbugCAA
With the population size of at least 3000, to calculate the number of Lego customers needed,
Since the survey has yet to be conducted, we assume a population proportion of 0.5. With 95% confidence interval, margin-of-error of ± 5% and minimum population size of 3000:
In addition to the minimum size, the response rate must be considered. Given that the average survey response rate is at 33% and giving respondents incentives increases the response rate to 10-15% (Lindemann, 2021), we estimate the response rate to be about 45%.
Similarly, since the population size for non-Lego customers is unknown and assuming that non-customers are less willing to participate, hence:
Because the sample sizes for both are close, we estimate the total number of responders to be near 2000. The selected sample of the focus-group is roughly 5% of the total sample size or about 100 people4, with additional 20 people in case of dropouts.
4 Chosen amount will be explained in Section 3.2
To gather sufficient information, focus-group studies and online surveys will be conducted.
We recommend contacting and engaging with respondents via email which will boost efficiency owing to the large number of 2000 respondents. Current Lego customers can be contacted via Lego's newsletter subscription service or LEGO VIP membership account. We may advertise survey opportunities on social media channels for non-Lego consumers.
We can boost the total response rate and accuracy by offering the online survey in multiple languages, promoting engagement since respondents can better grasp the question, providing more accurate replies. (Farris, 2021)
Likewise, for focus-group sessions, it will be conducted online in their respective native language in case of misinterpretation or wrong translation. A modest scale of 8 respondence each across six groups5, held around 80 minutes would be the most effective. (Prasad & Garcia, 2017)
During this pandemic, these online sessions are more convenient, cost-effective, and safer for responders (dataSpring, 2020). With the survey and focus-group session conducted online, the project will be more time-saving and cost-effective since we can cut facility rents, participant travel costs and miscellaneous costs such as refreshments.
To boost the response rate of selected samples, monetary incentives are offered. Since it is an online session where participants join remotely, incentives are adjusted based on the average market rate6. The online survey pays £5 gift-card per person, and the focus-group session pays £30 per person.
Nevertheless, this will require respondents to have basic computer knowledge since both the online survey and focus-groups are conducted online. The management team must also be prepared to send out prompt reminders, along with detailed instructions on joining the online meeting. In the event of connection or technical issues, buffer time should also be included.
6 Average incentive given for focus group: https://www.driveresearch.com/market-research-company-blog/how-much-does-a-focus-group-cost-focus-groups-syracuse-ny/#:~:text=As%20a%20general%20rule%2C%20the,%2Dto%2Dend%20project%20management.
2-Way ANOVA is used in RO1.1 for Lego to understand the product types that appeal to children. The independent variables are Product Types and Age-Group, while the dependent variable is the Preference of Products. We formulate our hypothesis as follow:
H₀ | Preference of products does not differ across product types and age-group |
H₁ | Preference of products differs across product types and age-group |
X1 | Product Types |
X2 | Age-Group |
Y | Preference of Products |
Physical
Digital
Blended
Under 18
18 to 25
26 to 35
36 to 45
46 to 55
Above 55
With “Test of Between-Subject Effects” table generated from SPSS, we can statistically identify if the independent variables and their interaction have significant statistical effects on the dependent variable.
If p-value(Sig.) < α (Significance level), the null hypothesis H₀ is rejected, and we conclude that Preference of products differs across product types and age-group. Furthermore, Partial Eta Squared value can measure the independent variable accounting towards the overall variation in the mean of the dependent variable.
This qualitative online Focus-Group will obtain direct feedback from consumers on how preference of toys will appeal to children over the next 5 to 10 years’ time, and on their thoughts regarding future Lego gameplay possibilities.
With consent, the 80-minutes session will be recorded, with the transcript carefully analysed to provide insights into their viewpoints. The participants’ expressions and behaviours are observed and recorded, then analysed for uncertainty in case of response-errors.
Duelling-moderator would be appropriate for this group, as the opposing moderators will try to facilitate fresh ideas by evaluating different viewpoints, evoking more thoughts from participants on opposing sides. The goal would be to challenge participants’ thinking, confronting their opinions to elicit additional information. This strategy was chosen since perspectives on children's interests and preferences are likely to have conflicting viewpoints among individuals of different demographics, and participants are more inclined to speak up if surrounded by people sharing their perspectives.
Furthermore, if respondents can engage with Augmented Reality (AR) in gameplay during the session, their comments will be based on their experience, rather than initial, hypothetical ideas. Respondents can provide greater insights regarding their usage experience if they are more involved. (Eskenazi, 2011)
Initially, this focus-group idea was to have a discussion session with children, but we feel that parents are the ones with purchasing power and gameplay concerns, and it would be difficult to manage the session remotely with children. Therefore, making it more appropriate if we gathered information from parents or adults living with children7, on the types of toys they are most likely to buy. Holding the meeting online also makes it easier for parents to obtain immediate feedback from their children if needed.
The key findings from this session can help Lego better understand their customers, and they can gradually orient toward that trend over the following years if they can gauge people's interest.
7 Questionnaire Q8 filters out people with children in their household
This Focus-Group session holds discussions on how Lego’s progressive environmental stance can further improve the company’s brand image through advertising. With a Dual-moderator feature, the session’s first moderator ensures that everything runs smoothly with full participation. The second moderator ensures that all issues presented have been covered. This strategy was chosen since it ensures full coverage and participation, with these questions being more discussion-oriented, requiring more in-depth responses.
Set in a similar operating environment as the previous focus group, each session should last roughly 80-minutes, and the 8-person session will be recorded with transcripts and analysed. The session will include the different types of advertisements that Lego has made in the past, such as those found on billboards, social media, and video platforms.
A polling Q&A portion may be included in the session, where participants can join the web event link, submitting questions or votes using their own devices (anonymously if needed for introverts).
The key findings from this session help Lego better understand and adjust their priority and marketing strategy regarding the type of advertisements they should use to promote their sustainable efforts of using recycled plastic bottles in brick production, thereafter, improving their brand image.
Paired T-test is used in RO2.2 to find out if promoting sustainable efforts improves brand perception.
H₀ | Consumers’ brand perception of Lego has no improvement via promoting the use of recycled plastic bottles in brick production |
H₁ | Consumers’ brand perception of Lego has improvement via promoting the use of recycled plastic bottles in brick production |
Let μd be the population mean difference in the Before-test and After-test scores, where d is the difference of brand perception before and after promoting.
H₀: μd = 0 H₁ : μd ≠0
The brand perception before promoting the use of recycled plastic bottles in brick production would first be recorded, then we proceed to show an advertisement/excerpt. Next, we measure the consumers’ brand perception of Lego after viewing the excerpt.
If p-value(Sig.) < α (Significance level), the null hypothesis H₀ is rejected, and we conclude that there is a significant improvement in brand perception before and after promoting. The finding is further supported if the value of 0 is not within the 95% confidence interval, allowing us to conclude if promoting the use of recycled plastic bottles affects consumers’ brand perception.
Multiple Linear Regression is used for RO3.1. to test if identified factors will impact the opinions towards visiting Lego’s retail store.
H₀ | There is no relationship between opinions towards visiting Lego’s retail store and the demographic variables: | |
H₁ | There is a relationship between opinions towards visiting Lego’s retail store and the demographic variables: | |
X | Age Household Size Average Monthly Household Income Gender Area of Residence | 𝑋1 𝑋2 𝑋3 𝑋4 𝑋5 |
Y | Predicted value of opinions of visiting | |
Age
Household Size
Average Monthly Household Income
Gender
Area of Residence
Age
Household Size
Average Monthly Household Income
Gender
Area of Residence
The multiple linear regression equation is:
Additionally, with the ANOVA table, we use Global F-test to examine the significance of Xᵢ and whether they will improve the model fit. If p-value < significance level, the null hypothesis is rejected, and we conclude that some Xᵢ contribute to Y. The Partial T-Test then determines if Xᵢ contributes significant predictive power to another model containing other variables.
With Adjusted R-Squared, non-significant variables are identified to improve model fit, enabling us to know the significant variables affecting opinions towards visiting Lego’s retail store more. However, there is a possibility that respondents cannot accurately categorize themselves as rural or urban8. A 'Suburban' option may be included, although being unlikely to make a significant difference statistically because Lego stores are often found in urban region malls.
8 Classification accuracy of area of residence: https://www.intellisurvey.com/marketing-by-urban-suburban-rural-segments-a-quick-client-case-study
Contingency Table (Cross-tabulation) will find out if the preferential mode of purchase for Lego products differs by Region of Residence. Using Preferential mode of purchase for Lego products as the dependent (categorical) variable, Region of Residence as independent variable, we have the following hypothesis:
H₀ | There is no relationship between the preferential mode of purchase for Lego products and Region of Residence. |
H₁ | There is a relationship between the preferential mode of purchase for Lego products and Region of Residence. |
X1 | Preferential mode of purchase for Lego products |
X2 | Region of Residence |
Next, Chi-Square test can be used to identify the presence of an association between independent and dependent variables. Small Chi-Square value shows a minimal relationship between the categorical variables, whereas a large value signifies association. When p-value < α, null hypothesis is rejected, indicating that the independent and dependent variables are associated.
We use Cramer's V to test the strength and direction of association because the dependent and independent variables are nominal in the 3x5 table. The V value between 0 and 1 represents the strength of association for both categorical variables, where a large value indicates a strong association.
The following budget breakdown and chart:
Lego could consider broadening their research demographic to include adults, better understanding the types of products that appeal to them. The existing term AFOL–Adult Fan of Lego9 is also a community worth investigating.
Next, depending on the number of questions, the two focus-groups can consider consolidating into one, which we will further discuss. This reduces costs and time over hosting separately, but the moderators must be ready and capable of handling the situation if participants get overwhelmed.
Lastly, before expanding retail stores, I would recommend further researching the country’s restrictions and current pandemic regulations since it would affect the human traffic flow, thereafter the store’s profitability.
9 AFOL (Adult Fan Of Lego) description: https://www.brickfanatics.com/lego-exclusive-afols-taught-us-to-take-adults-seriously/
Thank you for taking the time to answer this survey.
The Lego Group is conducting research to determine market trends and interests.
By assisting us to better understand you, we will be able to continue developing ideas and strategies to improve our products and advertising on sustainability efforts.
Please note that all questions are mandatory, and your honest responses are required. We assure that the information acquired is used only for overall statistics, research, and analysis and that it will not be used for any unsolicited reasons.
The survey will be carried out over the period from 7 Mar- 21 Mar 2022.
This survey will take around 5-10 minutes. The Lego Group would like to thank you with a gift-card worth 5 pounds for completing this survey.
We greatly appreciate your participation in this important research.
Q1. What is your current age (as of 1 Jan 2022)?
Q2. What is your gender? (assigned from birth)
Male
Female
Q3. What is your household size?
Q4. What is your average monthly household income?
Q5. What is your current region of residence?
Asia-Pacific (including China)
Middle East & Africa
Europe
North America
South America
Q6. Which of the following best describes the area you live in?
Urban (City)
Rural
Q7. Have you purchased any Lego products within the last five years?
Yes
No
Q8. Do you have any children between the ages of 0 and 17 in your household?
Yes
No
Q9. Which of these products do you prefer?
Physical
Digital
Blended (mixture of both)
Q10. What is your current brand perception of Lego?
Not at all favourable
Not so favourable
Somewhat favourable
Very favourable
Extremely favourable
Q11. In June 2021, The Lego Group announced its success in making its bricks from recycled plastic bottles, allowing its product line to become more environmentally friendly by switching away from oil-based plastic.
What is your perception of Lego after reading the above excerpt?
Not at all favourable
Not so favourable
Somewhat favourable
Very favourable
Extremely favourable
Q12. What are your opinions towards visiting Lego’s (physical) retail store?
Very Disinterested
Somewhat Disinterested
Neither interested nor disinterested
Somewhat Interested
Very Interested
Q13. What would be your preferential mode of purchase for Lego products (if you decide to do so)?
Online delivery
Physical store
Click & Collect (Buy online, Collect from store)
Q14. Would you be interested to participate in an online focus-group session for further discussion? (Further incentives will be provided)
Yes
No
Survey Completed – Thank You for your participation!
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Vetted by Mr Dion Chan
Word count excluding executive summary, table of contents, appendix, footnotes, labels, equations, questionnaire, table labels is 2976.
Lego’s logo retrieved with courtesy from https://en.wikipedia.org/wiki/The_Lego_Group
Terms and Conditions in the Online Survey will be further provided and discussed in the presentation session.
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