The human brain works by associating and classifying. For customers to associate with a product and its ad/marketing, various factors such as packaging color, layout, material, size and shape and other design elements like elegance and simplicity have to be considered before product launch/sale. In many of the cases, better and appropriate packaging can trigger the basis for customer loyalty and change brand perception.
The advertisement and marketing industry is on the rise from the last two decades. Amongst many factors that affect the sales of a product, the packaging is tangible and is preliminary. Attractive packaging is used to draw attention in customers and increase the probability of sales. This form of marketing has given birth to various innovative ideas. It’s a method of reflecting the quality, creativity, and authenticity of a brand.
In the earlier times, it was just a necessity for protection of product and no one paid attention to branding as there was an assumption of customers having no expectations. Companies just considered packaging as an afterthought but when they spend so much time perfecting the product, packaging needs equal attention. With changing times, packaging has taken a vital role in the development of any company and its marketing strategies. It has led to the emergence of an entirely separate packaging industry. The outer cover box has become a communication channel and salesman!
Statistical results show that about 70% of users see packaging as the first thing while making a buying decision. It is natural that if the packaging is sloppy, the consumer will look for a substitute. Luxury goods that come in intricate designs of packaging are better sold, especially amongst younger generations and the class of bloggers. There’s a section of customers who make an educational choice when purchasing any product by considering the environmental damage, economical factors and other technical advancements in the product packaging. However, many are ignorant of these elements and factors. Environmental factors are often ignored and a lot of customers are also unaware of the latest innovations and technological aspects of packaging such as tamper-evident packaging and QR codes.
Before any product sale, the mindset of the target section needs to be studied which will greatly influence the design of the packaging and resources required. A simple survey can reveal how customer loyalty can be triggered and broken by the new product while simultaneously, educating them. Resource allocation needs to be focused on subsets of individuals rather than a whole class of people as income, age and personal choices play an important role.
Analysis of the trends in the packaging industry is a study to understand the mindset, expectations and suggestions of the customers and target market for better branding of the company, more sales in a competitive marketplace and widening loyal customer base.
Various elements influence the decision behind a particular packaging, in terms of design, layout, colour, size, shape, material and even content on packaging.
The main features of good packaging are:
1. Convenient to transport, handle and open.
2. Attractive to catch the attention in first glance and intrigue the customer to check it.
3. Economical with decent cost price in regard with the resources used for the packaging.
4. Protection for the product is a must and is the primary purpose.
5. Communicative by providing all the necessary information about the product to the customer and should act like a silent salesman.
Studies show that packaging of products can increase customer satisfaction, increase visibility and set one product apart from its competition. The analysis study will showcase the factors most important for the customers and the expectations they have in terms of different elements.
The objective is to study, scrutinize, and analyze the survey results for a deeper understanding of consumer purchasing behaviors with respect to packaging. Various factors such as design, cost, product protection, technology, sustainability, and authenticity are covered by the questions in the survey. The aim is to gain insights into how product packaging affects the sales of a product.
1. In the proposed system, we are going to use the data collected from the survey to analyze and derive insights on the various influential factors customers act upon. We will preprocess the database to get reliable and accurate patterns and insights and use descriptive statistics to draw conclusions such as – major factors for purchase, ranking of packaging elements, categories of the packaging, technical and informative details on packaging.
2. Using EDA, we will show the trend of the growth of packaging in the world and how it expanded and customised. Using graphs, we study how one factor behind packaging is interrelated to the other.
3. We also do predictive analytics as to what the magnitude of the packaging trends can be in the future years.
A survey was prepared and data was collected using Google Forms. The form comprised of varying questions providing detailed explanation of packaging choices. The survey questions did not oversee basic information. Starting from standard questions such as age, income, and gender to detailed and focused questions like the preference of packaging materials, aesthetic and environmental factors, QR code, colour coded ingredients stripes and tamper evidence were covered. Avoiding a long survey and fatigue, only 20 short questions were asked. A person could finish the survey within 5 minutes.
Link to the survey: https://docs.google.com/forms/d/e/1FAIpQLSfW72oHlubpiCDOc1EoVil-zE0FtB_ndcHqVcJXRtA2LgozLQ/viewform
The entire data was collected within a week. There were over 200 responses recorded of ages varying in the range of 16-56 years old. The median age was 21 and average was 25. The median income was 80,000 and the average being 1.9 lakhs. However, the raw data had few null values and repetitions.
Data was converted into a CSV file and analyzed on a jupyter notebook using Python. There were various data analysis tools used such as NumPy, pandas, Plotly, matplotlib, and chart studio. Now since the project contains different types of graphs and different aspects of it have been explored, so different type of data pre-processing has been done before plotting the respective graphs, which could be making of a new column or a new dataframe itself. Missing values were removed and anomalies were taken care of. Post data cleaning, further processing included Descriptive Analysis and EDA. For easier and faster analysis, all the columns were renamed and a new schema was created.
Exploratory Data Analysis refers to the critical process of performing initial investigations on data so as to discover patterns,to spot anomalies,to test hypothesis and to check assumptions with the help of summary statistics and graphical representations. Exploratory Data Analysis (EDA) is an approach/philosophy for data analysis that employs a variety of techniques (mostly graphical) to
1. maximize insight into a data set
2. uncover underlying structure
3. extract important variables
4. detect outliers and anomalies
5. test underlying assumptions
6. develop parsimonious models
7. determine optimal factor settings.
Descriptive statistics is the term given to the analysis of data that helps describe, show or summarize data in a meaningful way such that, for example, patterns might emerge from the data. Descriptive statistics do not, however, allow us to make conclusions beyond the data we have analysed or reach conclusions regarding any hypotheses we might have made. They are simply a way to describe our data.
Descriptive statistics are very important because if we simply presented our raw data it would be hard to visualize what the data was showing, especially if there was a lot of it. Descriptive statistics therefore enables us to present the data in a more meaningful way, which allows simpler interpretation of the data.
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Pandas: Pandas is a high-level data manipulation tool developed by Wes McKinney. It is built on the Numpy package and its key data structure is called the DataFrame. DataFrames allow you to store and manipulate tabular data in rows of observations and columns of variables. -
Numpy: NumPy is a python library used for working with arrays.It also has functions for working in domain of linear algebra, fourier transform, and matrices.NumPy was created in 2005 by Travis Oliphant. It is an open source project and you can use it freely.NumPy stands for Numerical Python. -
Matplot: Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.One of the greatest benefits of visualization is that it allows us visual access to huge amounts of data in easily digestible visuals. Matplotlib consists of several plots like line, bar, scatter, histogram etc. -
Seaborn: Seaborn is a library for making statistical graphics in Python. It is built on top of matplotlib and closely integrated with pandas data structures. A dataset-oriented API for examining relationships between multiple variables. Specialized support for using categorical variables to show observations or aggregate statistics. Options for visualizing univariate or bivariate distributions and for comparing them between subsets of data. Automatic estimation and plotting of linear regression models for different kinds dependent variables. Convenient views onto the overall structure of complex datasets. -
Plotly: The plotly Python library (plotly.py) is an interactive, open-source plotting library that supports over 40 unique chart types covering a wide range of statistical, financial, geographic, scientific, and 3-dimensional use-cases.
1. In the survey, while preprocessing, salaries of customers were recorded to understand buying trends of customers based on their income. However, 37% of the customers did not reveal their income.
2. Environmental andeco-friendly aspect of the product packaging is the factor that majorly influencing customers' preference during purchase. Followed by, cost and convenience features.
3. The customers were almost equally divided in their preference of convenience while opening packages. While 31% said that difficulty in opening package didn't effect them, 33% were effected by it and rest 36% didn't consider difficulty in opening packages as an influencing factor.
4. Preferred packaging for food : Glass containers followed by metal and then plastic.
5. Preferred packaging for fruits and vegetables : Paper/Cloth is the popular choice with more than 100 customers opting for it, followed by traditional packaging like Jute bags with around 35 customers. Metal is the least favourable option.
6. Preferred packaging for cosmetics: Plastic and glass are the preferred choice with around 60 and 55 customers respectively.
7. Preferred packaging for pharmaceuticals: Plastic
8. Preferred packaging for accessories: Paper/Cloth is the popular choice for storing any accessory, with a count of approximately 65-70 customers. Plastic and traditional packaging are further preferences of customers.
9. Preferred packaging for clothes: Paper/Cloth bags is the most preferred packaging material.
10. Preferred packaging for E-goods: Plastic, cloth, traditional packaging like cardboard boxes are preferred with a count of approximately 70, 50 and 45 customers respectively.
11. The survey had maximum active participaction from customers of age group 19 to 23.
12. Jute bags and wooden containers are the choice in traditional packaging that customers prefer for certain goods. While many also consider bamboo baskets a good choice, around 20 customers from the survey of 200 don't like and take traditional packaging as a suitable choice and option.
13. 65% of the survey participants opt for smaller packages for goods and products and find them to be more convenient. Customers would rather buy many in small packaging than less in larger sizes.
14. In a busy world, 48% customers opt for prepacked bags of fruits and vegetables while 28% don't opt for it, if it comes with a price hike.
15. With a small minority of customers preferring cheaper packaging, the rest are almost equally distributed between wanting only aseptic/tetra packaging and only fresh products, statistically being 47% and 45% respectively.
16. Chips are the favourite go-to snack! While the chips fanatics account for 53% - supporting modified atmosphere nitrogen packaging, the rest is completely against it and would not prefer any product in such packaging, which studies have shown to be quite harmful for the health.
17. The colour code strips at the bottom of creams and toothpastes are believed to signify the ingredients that go into making those products. Many consider this to be factual but it is claimed that the colour codes are for sensors to produce tubes of a particular shape and size. However, a small section of 26% customers do buy products based on this colour code. It is sometimes prescribed that a blue stripe on the tube of toothpaste means 'drug-containing toothpaste'. Green stripe means completely natural. Red strip means a mixture of natural and chemical and black stripe means completely chemical. Rest of them either don't notice it at all or don't buy these products based on this reasoning.
18. Majority customers agree that the information on the packaging provided by the producer is detailed and enough to get all information about the product.
19. Upcoming technology includes QR codes that contain all additional information needed on the product. Accouting to 51% of total, customers are well aware of it but never use it and 35% claims to use it sometimes.
20. The survey revealed that most of the people, 175 out of 203, prefer to buy a high quality product in substantial and good packaging over a high quality product in flimsy packaging or a low quality product.
21. About 150 participants would change company for a better appealing package but only if the other brand is better than the previous one but a strong count of 70 revealed to stay loyal to the company.
22. Correlating the preference of small packaging and effect on purchasing due to difficulty in opening small packaging revealed that half of the people who prefer small packaging find it difficult to then open it and this has a negative impact on purchasing. On the other hand, equal number of people, who prefer smaller packaging, didn't have any issue with opening the packaging or didn't care about it.
23. Correlating the two factors reveals that majority people who prefer to only buy packaging which is environmental friendly, also prefer prepacked products of the same.
24. Correlating the two factors reveals that majority people who prefer to only buy packaging which is environmental friendly, most of them would then go for aseptic/tetra packing which is not always ecofriendly. This shows the contradictory purchasing choices of customers. Almost equal number of people, on the other hand, are absolutely against it.
25. Understanding customer behavior in regard with offers and sales. 35% of the surveyed customers would prefer to buy a product in quantity of three-four at once, in an offer of lower price. Closely following, approximately an equal amount of people would buy a product only when on sale.
26. With little more margin, 52.7% of surveyed customers buy and consume products with modified atmosphere packaging such as chips packets.
27. The surveyed customers ranked factors that they focus on from first to last while purchasing. Surprising, expiry of the product is a factor ranked 1 by most of the customers, during purchasing. People give the least importance to the design of the product.
28. Graphical representation of the ranking of preferrences.
29. Majority customers never want to compromise. They would always prefer to buy a high quality product in a high quality packaging.
30. Half the customers always buy tamper evident packaging and the rest are distributed between not preferring and not caring, with 20.7% and 28.6% respectively.