Description
Assignment Details
This assignment builds upon your work in Units 1, 2, and 3.
Chapter 12 shows an overview of how data can be described using statistics. Descriptive statistics enables you to describe and compare the data values associated with the variables involved in answering a business question or resolving a business problem.
After analyzing the qualitative data using thematic analysis (see Unit 3), the Marketing Vice President (VP) discovered that the most recurring theme in participant responses was the length of time that the smartphone battery holds its charge. The Marketing VP knows that her company’s current battery supplier (Supplier A) has a battery that lasts approximately 10 hours. The marketing team conducted some exploratory online research and discovered that the average smartphone with continuous use results in a battery charge lasting 9 hours. The company’s Supply Chain Manager is recommending that the company switch to another supplier (Supplier B) that claims that their battery lasts 11 hours on a charge when the smartphone is in continuous use. It is important that the Marketing VP confirm whether Supplier B’s claim is true because Supplier B’s battery is more expensive than Supplier A’s battery. The team ran tests on 10 Supplier A batteries and 10 Supplier B batteries to see how long each phone’s charge lasted when the phone is in continuous use. The team then analyzed the collected data using descriptive statistical analysis. See the Descriptive Statistics results below.
Objective
Confirm whether either Supplier A’s or Supplier B’s batteries last 11 hours between charges.
Descriptive Statistics
The following are important terms in descriptive statistics:
Mean: Average in a collection of numbers
Standard error: Standard accuracy of an estimate
Median: Middle number in a sorted, ascending or descending, list of numbers
Mode: The most frequently occurring number in a set of numbers
Standard deviation: Measure of the amount of deviation in a set of values
Sample variation: Measure of the degree in which numbers in a list are spread out
Range: Difference between the lowest and highest values in a list of values
Minimum: The smallest value in the data
Maximum: The largest value in the data
Sum: Total of the observations (in this case, the number of tests ran on each battery type)
Count: Number of items in the test (in this case, the number of batteries of each type)
Review the Descriptive Statistics Analysis Results.
Complete a quantitative data analysis of the given quantitative descriptive statistics types.
Your 5-page analysis should include the following:
Evaluate the value of descriptive statistics in answering the given research question to achieve the research objective.
The introduction should introduce the reader to the use of descriptive statistics in business research.
Assess descriptive statistics options, the business research question, and the research objective to create a 1-page infographic slide showing how each descriptive statistics option either supports or does not support answering the given research question or objective.
Evaluate the given results of 2 descriptive statistics types to determine whether or not the results answer the business research question or achieve the research objective.
Argue a persuasive rationale for the value of using 1 of the given descriptive statistics types instead of the other for the business research question or the business research objective.
Watch this video on how to create an infographic.
Deliverable Requirements
The infographic showing how each descriptive statistics option supports or does not answer the business research question should comprise 1 graphic. The analysis of the 2 descriptive statistics results and the rationale for using 1 type versus the other to answer the business research question and objective should be 4 pages in length. Be sure to cite sources using APA properly; include references and in-text citations.
Submitting your assignment in APA format means, at a minimum, that you will need the following:
Title page: Remember the running head. The title should be in all capitals.
Length: 5 pages minimum
Body: This begins on the page following the title page and must be double-spaced (be careful not to triple- or quadruple-space between paragraphs). The typeface should be 12-pt. Times Roman or 12-pt. Courier in regular black type. Do not use color, bold type, or italics, except as required for APA-level headings and references. The deliverable length of the body of your paper for this assignment is 5 pages. In-body academic citations to support your decisions and analysis are required. A variety of academic sources is encouraged.
Reference page: References that align with your in-body academic sources are listed on the final page of your paper. The references must be in APA format using appropriate spacing, hanging indent, italics, and uppercase and lowercase usage as appropriate for the type of resource used. Remember, the Reference page is not a bibliography but a further listing of the abbreviated in-body citations used in the paper. Every referenced item must have a corresponding in-body citation.
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Grading Rubric: Maximum 140 Points
Grading Criteria Points
Deliverable requirements addressed; understanding of material and presenter’s message and intent are clear 60 points Followed assignment guidelines and criteria 30 pts Yes/Complete Mostly Not at all
Overall quality 30 pts Excellent Satisfactory Needs Improvement
Scholarly research that supports the writer’s position is properly acknowledged and cited, and direct quotations do not exceed 10% of the word count of the body of the assignment deliverable 30 points Title page, table of contents, tables, exhibits, appendices or reference page included 15 pts Yes Partially Not at all
Content is original with less than 35% match 15 pts Yes 36–50% 51% or over
Critical thinking: Position is well-justified; logical flow; examples 15 points Position is justified with examples 7.5 pts Excellent Satisfactory Needs Improvement
Presentation flows logically 7.5 pts Excellent Satisfactory Needs Improvement
Structure: Includes introduction and conclusion, proper paragraph formatting, and reads as a polished academic paper or professional presentation, as appropriate for the required assignment deliverable 15 points Includes introduction and conclusion 5 pts Excellent Satisfactory Needs Improvement
Paragraphs are formatted properly 5 pts Excellent Satisfactory Needs Improvement
Reads as polished academic paper or presentation 5 pts Excellent Satisfactory Needs Improvement
Mechanical: No spelling, grammatical, or punctuation errors 10 points Spelling and grammar are accurate 5 pts Yes Partially Not at all
Punctuation is accurate 5 pts Yes Partially Not at all
APA: Deliverable is cited properly according to the APA Publication Manual 10 points References are cited in accordance with APA formatting 5 pts Yes Partially Not at all
Reference page is included 5 pts Yes Partially Not at all
Reference
Venngage – Visualize your ideas. (2018, November 30). How to make an infographic in 5 steps [infographic design guide + examples] [Video]. YouTube. https://www.youtube.com/watch?v=uQXf_d5Mgjg
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Business Research
Jami Britton
American InterContinental University
Professor: Dr. Boris
Course: MGT510-2305B-01
Date: 12/2/2023
Business Research
Introduction
Companies invest a lot of money in market research since customer preferences are
always changing and failure to keep up with these changes can push a company out of the
market. Nokia is the perfect example of this as it was once the largest phone manufacturer in the
world. However, due to the failure to keep up with innovation in the industry during the
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smartphone revolution, it would begin to lose its market share and consumer loyalty. In the
present day, the company basically has no presence in the phone market. Market research can
hence not be underestimated since it ensures that the company remains attuned to changes in the
market and can hence be able to able to adapt accordingly based on the market trajectories
(Taherdoost, 2022). The phone market is very competitive, and companies hence invest heavily
in research and development in order to develop features that will increase the convenience of
their customers and no company in this industry can afford to be lax about understanding
customer preferences, particularly in terms of the features that drive purchasing decisions. This
paper hence delves into research methods and sampling techniques that can help the company
gain insight into the dwindling interest in its phones and how best to appeal to customers.
Quantitative and Qualitative Research Methods
In market research, there is often the need to determine a quantitative or a qualitative
approach in the design. A quantitative approach involves the investigation of phenomena through
the collection of quantifiable data and the application of mathematical models and statistical
techniques when performing data analysis. In business research, quantifiable research explores
the relationship between two variables and provides that are predictive, explanatory, or
confirmatory (Taherdoost, 2022). It involves the use of surveys, questionnaires, and structured
interviews. This option is often preferred since it provides actionable insight since most
businesses prefer making critical business decisions being guided by numbers. Due to being an
objective measure, it is often considered to offer a better perspective on issues relating to the
market and consumer preferences. This approach attempts to maximize objectivity, replicability,
and the generalizability of findings (Taherdoost, 2022). Experiences, perceptions, and biases are
hence set aside to facilitate this approach. In this approach, a single truth is hence thought to
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exist that is free from human perception. In this case, a quantitative approach can help determine
the significance of various features based on the available data, and patterns and correlations can
hence be identified that can inform the design and marketing process of the product.
Qualitative research is a more subjective measure, focus is hence placed on developing an
understanding of the experiences, thoughts, and perspectives of participants. The goal of this
approach is to hence gain meaning and purpose since it offers an interpretive and naturalistic
approach to the world. Qualitative research hence provides context by trying to make sense of
things and the meanings that people have ascribed to them. This approach hence generally
accepts that there is the likelihood of multiple truths that are socially constructed (Taherdoost,
2022). This research approach hence allows for detailed exploration into a particular subject. A
key feature is hence to allow participants to engage in a naturalistic manner with few boundaries
making it a more flexible and open research process. Replicability and generalizability of
findings is hence not a major goal of this research approach. These methods include interviews,
focus groups, and open-ended surveys, allowing participants to express themselves freely
(Taherdoost, 2022). In business research, this approach is preferred when there is the need to
gain in-depth insights into consumer preferences as a means of determining their needs and
motivations when it comes to purchasing a product. In this case, a qualitative approach may help
uncover nuanced and subjective aspects of customer preferences.
In essence while quantitative research deals with numbers and statistics, qualitative
research focuses more on words and meaning. Different kinds of knowledge can hence be gained
from approaching research from either perspective or this entails a mixed-method research
design (Murphy, 2023).
Sampling
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In research, sampling is key since it is both expensive and time-consuming to collect data
from the entire population. Obtaining a representative sample is hence critical since this allows
for findings to be generalized for the entire population. A representative sample allows for
findings to be an actual reflection of the population. There is both probability and nonprobability sampling. Probability sampling is usually the one used to facilitate the selection of a
representative sample; non-probability can allow for biases since sampling choices are not made
in a standardized and objective manner, one approach to probability sampling is random
sampling, in this approach everyone or every item from the population has an equal opportunity
of being selected. This ensures no bias since no one oversees the selection and any random
person can be chosen to be included in the sample. There is also stratified sampling where the
population is divided into subgroups based on defining characteristics such as geographical
location. Random samples can hence be selected from each stratum, hence facilitating a
representative sample. There is also systematic sampling where a fixed parodic interval is used to
choose a sample from a defined starting point. A sample can for instance be determined based on
every 100th person or item. Approaches that focus on non-probability sampling include
purposive sampling where participants are selected based on certain characteristics. For instance,
if a company is designing a product specifically for women, they may hence choose a
representative sample of women who are likely to buy this product. There is also convenience
sampling that is based on the availability and accessibility of individuals. This approach may
however lack representativeness (Murphy, 2023).
Comparison
In this case, the company is trying to determine what features customers value leading
them to purchase a product. A quantitative approach would hence establish patterns between
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features and purchasing decisions. This may involve conducting surveys that contain close-ended
questions that will allow for the collection of data and statistical analysis can hence be performed
(Murphy, 2023). Based on these results it is hence possible to quantify the importance of specific
features. This hence facilitates data-driven decision-making since it is possible to perform
numerical prioritization and determine the features that hold the most sway among consumers
and hence heavily focus the marketing of the phones on these aspects and hence essentially
increase sales. Quantitative methods also facilitate the generalization of findings to the general
population since they can provide broader perspectives on items of interest.
Through a qualitative approach, on the other hand, it is possible to add context to
customer preferences. Through in-depth interviews and focus groups, it is possible to explore the
depth and complexity of preferences. It is possible to delve into customer motivations as they can
describe what exactly they look for when making purchases (Murphy, 2023). Through this
approach, it is possible to determine what features matter the most to customers and why exactly
these features are prioritized. Researchers can delve into the underlying reasons behind customer
preferences including both personal and emotional components. It is also possible to determine
how these phones impact people’s lives and what role these features these roles play. This
process can hence lead to the uncovering of unexpected information that the marketing and
design team may not have considered This information can be very useful in not only designing
the phones but in determining the marketing strategy.
Based on this understanding, a mixed-methods research design may be the most
appropriate since it allows the company to respond to the declining interest in its phone offerings
in the most holistic manner. Through qualitative research, it is possible to explore to develop an
intrinsic understanding of the target customers and hence be able to develop and market a
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product that piques their interest. On the other hand, through quantitative research, it is possible
to confirm these findings on a larger scale to provide statistical validity to insight gained from
qualitative research (Myers, 2019). A mixed methods approach hence facilitates a
comprehensive understanding which allows for more effective decision-making for the targeted
launch of the new product in 6 months.
Sample Selection Technique
Based on the needs of the company, a stratified sampling approach seems to be the most
appropriate. This is since it allows for a representative sample since participants are selected
from different strata based on demographic factors such as age, and gender or usage patterns. By
having representation from each segment, it is hence possible to test the hypothesis of whether
battery life is the most relevant consideration when making phone purchases. This technique
allows for findings to be generalizable since the sample is representative and the information
obtained can hence present the full picture of the market hence guiding the company towards
making the most strategic decisions that will ensure increased interest in the product and drive
profitability for the company (Myers, 2019). This method is hence the most appropriate since it
accounts for diversity in the population as well as captures variations in the sample which
increases the likelihood of a sample that is an actual reflection of the population.
Conclusion
In conclusion, a mixed methods approach seems to be the most appropriate research
method for the company’s needs since it borrows from the strengths of both quantitative and
qualitative approaches allowing for a more comprehensive understanding of customers’ needs
and preferences. On the other hand, a stratified sampling technique is the best in this case as it
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facilitates a representative sample and the findings of the research can hence be generalized for
the entire customer base.
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References
Taherdoost, H. (2022). What are different research approaches? Comprehensive Review of
Qualitative, quantitative, and mixed method research, their applications, types, and
limitations. Journal of Management Science & Engineering Research, 5(1), 53-63.
Myers, M. D. (2019). Qualitative research in business and management. Qualitative research in
business and management, 1-364.
Murphy, V. L. (2023). 18. Multilevel mixed methods research designs in business and
management. Handbook of Mixed Methods Research in Business and Management, 275.
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Data Collection Strategies
Jami Britton
American InterContinental University
Professor: Dr. Boris
Course: MGT510-2305B-01
Date: 12/11/2023
Data Collection Strategies
In business, information is power since it leads to more effective decision-making that
contributes to the success and profitability of a company. Data collection is hence necessary
since it allows a business to get an understanding of customer preferences, behavior, and trends.
This leads to more informed decisions when it comes to product development and marketing
since insight gained can be leveraged to customize products, services, and marketing according
to customer preferences and behaviors which contributes to improving the customer experiences
and hence customer satisfaction (Smith & Bazis, 2021). Through this, a brand can build customer
loyalty and retain valuable customers. Investing in business research also allows a business to be
able to adapt to changing market conditions which is necessary to ensure continued success. A
business that does not keep up with changing market conditions cannot be successful in the long
run since it is likely to be pushed out of the market. The phone industry is for instance very
competitive and brands such as Apple and Samsung invest billions in research and development
to not only keep up with customers’ needs and preferences but to also ensure that these
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businesses remain at the forefront of new revolutionary technologies (Haro et al., 2020). In
marketing research, data collection strategies are critical as they inform how businesses
personalize their marketing and provide better customer experiences. This is since the data needs
to be in the right context and structure to be useful. Otherwise, this data is just a set of random
facts that have no real direction in terms of how it can help businesses make data-backed
decisions. Businesses can take either a quantitative, a qualitative, or a mixed-methods approach
to data collection.
Quantitative and Qualitative Data Collection
Quantitative data collection involves measurable data that can be expressed in figures or
numerical form. Specific questions are hence asked to extract information from prospects or
customers. Through this it is possible to test models, gauge trends as well as segment customers.
This approach is instrumental in assessing the usage of a product, identifying areas of
improvement, measuring customer sentiment, and recognizing opportunities that will enhance
the experience of the existing customer base. After collecting data mathematical calculations and
statistical analyses are performed to help shed light on important insights regarding the market.
Quantitative data collection is often preferred since it is cheaper and takes less time when
compared with qualitative data collection. This data is also standardized or normalized and hence
requires less data cleaning (Smith & Bazis, 2021).
Quantitative data collection methods include surveys or questionnaires, polling, and
experiments. Through surveys, it is possible to administer a structured set of close-ended
questions to a large audience. This is often used in business when there is the need to gather
numerical data on customer preferences, attitudes, and behaviors. Through polling on the other
hand, it is possible to get a quick snapshot of public opinion and can be very useful when making
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product development and marketing decisions (Poth et al., 2023). Through experiments, it is
possible to test hypotheses as well as understand causal relationships between variables of
interest. Data obtained from these methods can be used to test ideas, make predictions, learn
more about customers, determine trends, and hence make informed business decisions. Data
obtained from quantitative methods is considered objective and reliable (Smith & Bazis, 2021).
Qualitative data on the other hand happens to be more descriptive than numerical. This
data is meant to answer questions such as why and how and is gained through observations,
focus groups, or in-depth interviews. This method uses open-ended questions and the answers
obtained are descriptive and have little to no numerical value. This approach allows for
businesses to be able to delve deeper into the thoughts and behaviors of prospective or already
established customers. Data obtained from this approach allows for the generation of new ideas
and marketing opportunities, the formulation of predictions as well as explaining data obtained
through quantitative methods (Smith & Bazis, 2021). This data is hence more subjective in
nature but facilitates a greater depth of understanding. Interviews and focus groups are the most
common approaches to qualitative data collection. Interviews facilitate the understanding of
complex motivations, and perceptions, and the uncovering of nuanced insights. Focus groups on
the other hand capture diverse perspectives and generate insights that come from group
interactions. Market researchers can also observe how participants interact with a product
without making direct contact. Through this, it is possible to get an understanding of the natural
inclinations regarding the product based on how they interact with the product. Qualitative data
collection can be prone to human errors due to its subjective nature while open-ended questions
can make using this data difficult (Smith & Bazis, 2021).
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A mixed methods approach is often preferred in business research since it is possible to
benefit from the complementary strengths of both approaches. It is for instance possible to obtain
depth from qualitative methods and breadth from quantitative methods. Through qualitative data
collection, one can delve into individual experiences, motivations, and behaviors while
quantitative methods allow for findings to be generalized to a larger population. The subjectivity
of qualitative approaches can also be countered by the objectivity of quantitative approaches.
Combining these methods hence facilitates a more comprehensive understanding of market
conditions and customers’ behaviors, attitudes, and preferences (Smith & Bazis, 2021).
Assessment of Quantitative and Qualitative Data Collection Options
To determine which smartphone features, lead consumers to make a purchase, the
company will, first, conduct a focus group using a representative sample of the customer base.
This will allow for diverse perspectives regarding what features contribute to making the choice
to buy a smartphone. During the focus group, the discussion will hence be centered on
smartphone features to allow the participants to share their opinions and experiences. Openended discussions will hence be facilitated to prompt unexpected insight from the participants
and hence the discovery of new ideas. The focus group will be recorded and detailed notes will
also be taken on participant responses and interactions. After the focus group is completed, the
researchers will comb through all this information to identify common themes and patterns
related to smartphone features. The insight obtained from this process will then be used to design
close-ended survey questions that will be administered online. This survey will be made to reach
as many consumers as possible and will be available on the company website, social media
channels, and will be sent to emails of already established customers. Incentives may be offered
such as gift cards to encourage participation and increase response rates. This data will then be
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analyzed using statistical tools and through this, it will be possible to lend statistical validity to
insight obtained from qualitative data collection. Correlation or contradictions can be established
by comparing the focus group results with the survey results. The combined data however offers
a more complete picture of the market (Poth et al., 2023).
Justification
Purchase intentions have become crucial in the overly competitive smartphone market.
To sustain one’s market share there is the need to constantly upgrade various features including
product appearance, features, service quality, and software. Smartphones have also become
embedded into the daily lives of customers since they have become more of a necessity than a
luxury (Haro et al., 2020). There is hence the need to understand how various features impact
consumers’ lives. Through the focus group, it is hence possible to delve deep into consumer
preferences and determine how they influence purchase decisions. The survey on the other hand
allows for the researcher to confirm that sentiments shared by the small focus group are
applicable to most of the customer base. The insight shared during the focus group is hence
compared and validated against a larger sample. This improves reliability and strengthens the
validity of the results and ensures that the company makes data-backed decisions regarding
product development and marketing that will ultimately ensure success. This approach hence
leverages the strengths of qualitative and quantitative data collection methods hence ensuring the
company gets a holistic understanding of the market and at the same time minimizes the
limitations associated with each method.
Conclusion
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Using either a qualitative or a quantitative approach in data collection can present a
limited view of the market, however, by combining these approaches, a complete picture is
formed that ensures that a research problem is explored in terms of both depth and breadth.
Based on this discussion, it is possible to observe that a mixed methods approach allows
researchers to understand individual experiences and preferences surrounding smartphone
features while at the same time ensuring that these findings can be applied to the general
population. Qualitative data collection sets the stage for quantitative data collection since
insights gained from focus groups inform the design of the surveys. Quantitative data collection
makes it possible to quantify trends, measure preferences, and test hypotheses. Qualitative
approaches add context while quantitative approaches ensure the reliability and validity of
findings. In the end, a more complete picture is formed which leads to informed decisionmaking.
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References
Haro, A., Oktaviana, D., Dewi, A. T., Anisa, W., & Suangkupon, A. (2020). The influence of
brand image and service quality towards purchase intention and its impact on the
purchase decision of Samsung smartphone. KnE Social Sciences, 329-336.
Poth, C., Bullock, E. P., & Eppel, E. (2023). Adaptive mixed methods research design practices
to address complexity in business and management research. Handbook of Mixed
Methods Research in Business and Management, 329-347.
Smith, M. C. H., & Bazis, P. S. (2021). Conducting mixed methods research systematic
methodological reviews: A review of practice and recommendations. Journal of Mixed
Methods Research, 15(4), 546-566.
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Qualitative Data Analysis
Jami Britton
American InterContinental University
Professor: Dr. Boris
Course: MGT510-2305B-01
Date: 12/17/2023
2
Qualitative Data Analysis
Mobile phones are no longer used solely for communication purposes; as this technology
has evolved, these devices have become a source of entertainment, comfort, and convenience for
consumers. In the race to develop novel products there is hence the need to consider how these
devices fit into the consumers’ way of life, their professions, and their hobbies. Due to increased
smartphone usage, various factors go into making the decision to purchase a specific brand and
model. Mobile phone companies, hence, need to consider features consumers value the most
before making major product development and marketing decisions since this ensures that the
products they put on the market are, in fact, in line with consumers’ tastes and preferences (Santy
& Atika, 2020). Innovative features and applications are hence constantly being added to
smartphones to meet customers’ needs and to allow these devices to perform a wide range of
functions. The market is incredibly competitive and companies are required to constantly work
hard to attract and retain customers. There is, hence, a race to constantly put out new
smartphones frequently with updated features and technologies as a means of gaining a
competitive advantage and avoiding being pushed out of the market (Santy & Atika, 2020). The
race to market is brutal, and failure to keep up with new technologies and capabilities could
mean the death of a company. This hyper-competitive nature of the market is intensified by the
ease of entry into the market and the many brands in the global market that are eager to gain
market share and greater brand recognition; as such, when one company falls, there is another
one willing to take its place. Features that influence purchasing decisions include product
features, brand image, perceived quality and value, and price, among others (Santy & Atika,
2020). The company took a qualitative approach to data collection and analysis in an attempt to
determine which product features the consumers considered carried the most weight in
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determining whether they made a purchasing decision or not. This paper hence discusses the
results of this research and how customer responses would influence decision-making in the
company.
Qualitative Data Analysis Strategy
The first step in the process is to arrange the data in a manner that makes sense. There is
the need to go through the transcripts of the interviews and systematically arrange the largely
unstructured information. The responses are then coded based on key features identified by the
participants that contribute to making their purchasing decisions. Computer-assisted qualitative
data analysis software can be used for this purpose. Group-related codes are then placed in
broader categories, such as battery life, camera quality, and the display of the phone. This
process will be simplified by using smaller samples of the customer feedback data that will be
used to establish the set of codes that capture the various themes that emerge, and as the sample
size increases, it will be possible to build on the emerging patterns (Lester et al., 2020). With
increasing sample size, adjustments will be made to enhance the codes and ensure greater
accuracy and consistency in capturing the nuances of the feedback. As overarching themes
related to smartphone purchasing decisions begin to emerge, it is then possible to explore the
connections between the different features and purchasing decisions. Through coding, it is also
possible to compress the tremendous amount of information collected into a digestible format
(Lester et al., 2020). It is also possible to build on patterns and gain incredible insight into the
data that facilitates informed decision-making. The use of software in this process not only
speeds up the process but can allow the uncovering of hidden insight that may not be visible to
the naked eye, hence facilitating a more comprehensive analysis of customer feedback.
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What follows is the actual data analysis that can relate the information to different
demographics as well as customer profiles, hence providing actionable insight that can guide the
company’s decision-making process. Using the responses, customer segmentation is, for
instance, possible based on demographic factors, age, customer behavior, and interests, among
other considerations. This data can then be visually represented through charts and graphs,
allowing for the frequency and prominence of each feature to be connected to the customers’
responses (Mezmir, 2020). The findings can then be organized into a comprehensive report
detailing the key features that influence customers’ purchasing decisions supported by quotes and
data from the analysis. There is the need to communicate and narrate the findings in a manner
that paints the full picture to the decision makers since the findings and insight are instrumental
in deciding the course of action in the development of the smartphone as well as the marketing.
A detailed report utilizing insight from the data analysis sets the company up for success
(Mezmir, 2020). The report should hence sort the information according to demographics and
specific customer information that can make decision-making faster and more straightforward.
The report can hence include specific recommendations regarding how the company should
approach product development and marketing of the new model of the smartphone.
The Strategy and Answering the Business Research Problem
Through the strategy described, the manager can develop an appropriate approach to
product development, marketing, and customer attraction and retention. By ensuring that the
product being released into the market meets the customers’ needs, the product will sell, hence
ensuring that the company continues to be profitable.
Product Development
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Battery life was identified as the most prominent feature that contributes to making a
purchasing decision. 32 of the 60 participants identified long battery life as a key feature they
consider before making a purchasing decision, with some even specifying a battery life of at least
7 hours. During the product development process, this will hence be a key consideration since
the company needs to ensure that the smartphone they develop has a long battery life. 29 of the
participants, on the other hand, discussed the quality of the camera as another feature that they
consider important when making a purchasing decision. The quality of the camera, including
features such as crisp and clear pictures, sharp resolution, and camera pixels, was consistently
highlighted. The clarity and crispness of the display were significant to 17 participants. Mobile
payment functionality was mentioned by 16 participants. Other features that mentioned by a few
users include remote control capability, multiple windows view, and processing power. During
the product development process, these features will hence be prioritized to ensure that the
smartphone developed is in alignment with the prevailing needs of the customers.
Marketing
Following product development and the incorporation of these specific features, the
marketing approach can be designed around how these specific smartphones tick all these boxes.
Through this approach, it is possible to draw in customer since they recognize that this product
embodies the features they value and can hence be incorporated into their daily lives to increase
the convenience of handling their responsibilities. The marketing campaign is hence likely to be
successful, which means increased sales for the company and increased profitability. By ensuring
that the company has the finger on the pulse of what customers value, they are likely to have an
edge in the market and, hence, be able to draw in more customers and effectively increase the
company’s market share (Arjuna & Ilmi, 2019). By ensuring the final product incorporates all
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these elements that customers value, it is possible to appeal to a wide range of customers. This
approach allows for a deep understanding of customer preferences in terms of product features,
and hence, informed decision-making occurs during the marketing of the product. The marketing
efforts are hence tailored to address customer preferences effectively (Arjuna & Ilmi, 2019).
Customer Attraction and Retention
In a dynamic market such as the mobile phone market, there is the need to ensure that
customer retention strategies are effective in meeting the prevailing customer sentiments
regarding specific products. There is, hence, the need to apply strategies that are responsive and
customer-centric. Customers’ opinions about a brand can be leveraged to guide how a brand is
able to enhance or revise its reputation to ensure that it remains relevant and visible in the
market. Through meeting customer expectations, a company is able to build a cult-like following
that ensures the business continues to thrive and reach new levels. This has been key to the
success of companies such as Apple and Samsung (Arjuna & Ilmi, 2019)
Conclusion
The smartphone market is incredibly competitive, and as such, companies need to
understand and meet the needs of the customers in order to remain in business and expand their
market share. Through qualitative data analysis, a company can make informed decisions
regarding its products. The insight gained can be leveraged to make strategic choices that will
contribute to the increased profitability of the company. This is based on the fact that it uncovers
nuanced insights into the features that truly resonate with the customers, allowing the company
to enhance existing products and introduce new features that are in alignment with customers’
expectations. The comprehensive report that is obtained from the qualitative data analysis can
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hence be used to inform product development, marketing strategies, and customer retention
strategies.
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References
Arjuna, H., & Ilmi, S. (2019). Effect of brand image, price, and quality of product on the
smartphone purchase decision. EkBis: Jurnal Ekonomi dan Bisnis, 3(2), 294-305.
Lester, J. N., Cho, Y., & Lochmiller, C. R. (2020). Learning to do qualitative data analysis: A
starting point. Human resource development review, 19(1), 94-106.
Mezmir, E. A. (2020). Qualitative data analysis: An overview of data reduction, data display, and
interpretation. Research on humanities and social sciences, 10(21), 15-27
