Marketing Analytics

178 views 7:22 am 0 Comments May 27, 2023

UNIVERSITY OF LEEDS

LUBS5403M Marketing Analytics

Student Name:
Student ID:

Table of Contents

Introduction

The report includes the crafty chocolates with the confidentiality that is one of the premium chocolate manufacturer. It is involving the marketing consultancy and developing the marketing report and then providing the recommendations for increased performance of marketing. The datasets are provided with demographics, chocolate rating, and the products along with the key attributes for the chocolate products. The primary collection of the data and the secured approach is about the attributes for the chocolate products and the sample of existing and potential consumers are for the demographics with the purchase of sustainable products that have been labelled with the orders that are direct from the website of company. The conjoint data is for the respondents with the choice of the developed products of chocolate. The discussion is about the making of orders online with the 500 consumers with the developed consumers products with the major supermarket partner for the consumers handling the shopping basket. The company needs to focus on the previous advertising spending on the platforms and the monthly sales with the versions of the ads that is displayed on the video based social media platform like Tik Tok with the focus on the subjective benefits of the sustainable labelled chocolates.

Problem Definition and Model Specification

The Crafty Chocolates is for the confidentiality with the making of orders with the company website, and then handling the cohort of the 500 consumers. The choice is based on the development of products, with the major supermarket partner with consumer shopping market and then spending on different platforms or the sales in the monthly manner. The marketing and the customer related decisions are for the business that involves the statistical modelling and analytics. It is important to support the decision makers to work on strategic decisions which is based on the data (Chang, 2018). Hence, integration is for the statistical modelling with marketing strategy that is referred to the analytics. The customer acquisition is found to be expensive than the retention with the business sensing for retaining the customers with profitable ones. The machine learning models is probability of the customer to leave or churn. The logistics regression model is for predicting the churn of customers. The data processing is for the file that is holding the demographic data with the general population to handle the functions and the memory reduction. Not only this, there are handling of missing values where there are columns that are contained for more than 70% of the missing values. The customer segmentation is for the use of unsupervised learning methods to analyse the attributes with the establishing of the customers and the population to create the segments of customer. The analysis is about the population with the mail order of the company that involves the capturing of maximum variance in the data and then reducing the dimensionality of data. The marketing is for predicting the supervised learning model with the target of training dataset that has the machine learning model for learning about the parameters and predicting about the customer response in the test data. The data preparation is about the segmentation report that fills the marketing campaign. The segmentation report is for the training data which is negative and the positive potential customer through the applied k-means clustering to identify the customer segments. It is based on responding to the marketing campaigns (Hanamanthrao et al., 2017).

Discussion on Data Analysis

Managing customer heterogeneity

For the customers, there are difference of the drivers it is based on the strategic marketing decisions where the firms tend to differ for the consumers. The heterogeneity is for he variations among the customers with the needs, desires and the behaviour. It is based on the efficiency costs and the benefits to match the solution. The issue of the facing of managers is based on the preferences and then handling the effects of the issue. The offering of the differed stock keeping units is based on the evidence for the dozens for the configuration that involves different brands, sizes and the single product for the entire target market. The approach is for the industries with competitors recognizing the opportunity and the niches of customers with the needs that are served poorly through the demand soared with competitors offering the products that are matched through fragmenting the customer desires. The category is about the growth in size with the competitors recognizing the opportunity with the niches of customers that are poorly served through the incumbent products and the targets with tailoring of the offering of the alignment with the needs. The firm’s marketing strategies tend to cater the differences for the product customer preferences (Fan et al., 2017). The competitor tends to work on the satisfying factors with the valuable customer segments with the growth and profitable approach. The firms identified are found to be flow growth and less profitable with the focus on the catalogues that tend to identify and attack the profitable subsegments of the customer base. They are for the homogenous customer groups that tends to offer the specialization of tools with innovative products. The crafty chocolate is for the sample of existing and the potential consumer for the demographics and then handling the purchase of the sustainable products that are labelled completely. Hence, the historical approach is for the supermarket partners with consumer shopping basket that is on different platforms and the monthly sales. The experiment data is about the versions of the ads that is based on the video of social media platform and the benefits are for the sustainable labelled chocolates and the ads version of B focus on the objective quality of the sustainable chocolates which are labelled.

Managing customer dynamics

The rapid proliferation and technology advancement is for the consumers to adapt to the technology at the rapid pace. It comes with the digital disruption that gives the business an opportunity for the increased negotiation of customer (Yang et al., 2019). The social network and the mobile, involves the customer expectations with responsiveness, trust and more. Not only this, there is a need to handle the sustainable approach with serving and managing the customer better digital age. The customer and business relationships are for customer dynamics which tends to involve the expansion of the scope and the end-results with customer business relationship that comes with the channel of contribution. The dynamics are for the emerging theory for customer business relationship with the exchange that tends to occur on the wider range of the communication channels. The customer dynamics is for the preferences and the addressing of effective marketing strategy that helps in growing the volume and diversity of interactions which directly impacts the customer business relationship. It is for the customer relationship and the revenue generation, business that can create the competitive differentiation with the intent to meet and support the business intent. The framework is based on the converting of CRM, marketing program and then losing the input data of customer into the dynamic segmentation and strategies where the managers tend to follow a series of steps, and dynamic customer lifetime value of segments and migration. The boundaries are for the customers and business which is blurring and the relationship is also beneficial. It tends to sustain the profitability and the business to the next level. The customer perspectives are for managing the orders with company placing and handling the users with the account that involves the details about the customer portal. The segments are for the firm existing customers which is based on the Markov models and the combined lifecycle and segmentation methods tend to match to the strategic marketing thinking and identifying the groups (Conner et al., 2020).

Managing sustainable competitive advantage

The competitive advantage involves the competing on the pricing with the providing the differentiated offering with the focus on the specific market niche that involves the tailored offering for the segment of market. The other advantage is for the competitors with the understanding of the attention with the service levels with the quality, branding, pricing. The designing of business model is to support and deliver the value proposition. The staff is for the selling and guiding the decision making and direction of the sharp focus. The new opportunity is for the business that involves the sustainable competitive advantage with the long term position of strength and stability (Leung, 2018). The sustainable competitive advantages is based on the real value investments with the position over the competitors and the low cost provider and low pricing that includes powerful brands, with the preferring of the brand over the competitors. The adapting of product line is for product differentiation with building customer loyalty to lose market share to competitors with handling quality, number of models and the flexibility in ordering for the customer service that is considered to be the major aspects of positive differentiation. The resources are hard to find, with the improved company efficiency of chocolate, or effectiveness that reduce the competitive weakness. The sustained competitive advantage includes the understanding of the drivers of business with the achieving of great results (Yaqoob, 2017).

The vision, mission, leadership and governance is for the firm fundamental reason with the existing firms that involves strategy to message, with reinforce the levels in and out of organization. The culture, commitment, objectives, and communication are for the support through the organization with the employees wanting to be the part with enhancing the possibility for creative and engaged parts.

Analysis of the tools and datasets

The analysis is based on the resource and the capabilities with the factors that involves the best practices for the firm. The r software includes the challenges with the features of big data analysis that provokes and handle the compile the experimental or captured data. The quality of data with the effective consideration about the data outcomes. The beneficial big data platform tools are to work on the profiling and the data visualization that is to manage the fields of data. It is also for enlisting the different attributes and the statistics that is for the scatter-ness of time series data. The approach is based on communication that relates to the R software control for the computer and non-computer scientists. The interactive web applications is for the apprehending approach of the tool with the new and also some of the good ideas. In the big data, the tableau is for the local and the data resources which comes through in-memory performance. This comes with the point and click analytics with real time drag and drop that includes real time regional data exploration. The analysis of spreadsheets, public data tools, and the data sets with several connectors like the Google and the Big Query. The network organization and the colourful presentation s for the trending charts with promising plots that is executed through Tableau. The data analysis package is for the solver of add-ins and analysing the data with advanced methods with the 3D graphs and maps with the data filtering that helps to analyse the data in specific manner. The report is thematic with pivot handling, modelling that is framed and then working on dashboard presentations. The business intelligence tools are for exploring and visualizing the data through Tableau that includes operational intelligence and the adjunction with the influential factors that includes business case, data load scripting and the creation of visualization. The profitability analysis and the project management includes the business related current and potential problems. The software helps to comprehend on time with the interpretation of outcomes for the customers (Nufiez et al., 2017).

Results

 

Figure 1: Customer Heterogeneity Plot by Demographics

 

Figure 2: Customer Dynamics (Age Group)

 

Figure 3: Customer Dynamics (Gender)

The resource-based view is for the trade-off which is for the internal sources with competitive advantage. The seeking of more than the less competition with limitations rather than the support of the functional success with destroying rather than the protection of the same exclusively. The live situations are for the resource-based view that includes the resources and capabilities that is for the broad perspectives. The desirable resource characteristics is based on the industry factors with focusing on the key characteristics approach. The desired approach is for conducing the perspectives with the overall trade-off that involves the generation through understanding the making of decisions. The management of broader contexts with the chocolate craft that is for failure to recognize about trade-off and recognize and focus on capabilities with maintaining the resources and capabilities. The key management tasks are for managing trade-off with the valuable capabilities through relative status, importance, and perceived value. The external trade off is for the resources and capabilities with firms owning to deploy the multiple resources and capabilities to maximize the overall values (Flore et al., 2018). The exclusive alliance partnership is for the firm that provide the partners with the proper access to the different forms of resources and capabilities. The approach is based on the alliance management operations with the managing of distribution, delivery, and the warehouse of the operations to manage the website. It is for the networking trade-off with the firm external network of customers that involves the relationship with the other firms and then handling positive and the negative effects of the firm.

Discussion

The extending development is for the workbench that includes the system management with the business application software that intends to navigate the information. It is based on product promotions and allowances with visualized approach for the analysis and system management and business that includes the Metanalytic and the microscopic details of business. The business includes the manufacturing with products that is for the multiple standards with conjoint of the data with the same respondents with the demographics csv that is for the different platform with consumer shopping basket monthly sales. The marketing resources are for the primary actions with the competitors challenging the source of advantage and the allocation of strategies across time. The approach is based on the customer needs and the industry segments with the focus on targeted segments along with firm commitment on the different segments. The pricing, promotion and program decisions with allocation of decisions, with the segmentation, targeting and the positioning analysis. The system management and business applications are for the features with the Tableau or the Excel with enterprise level governance of data. The attractive aspects includes the senior managers that includes the microscopic details for business. The manufacturing fast moving consumable comes with using the reseller model through products across the local and the global regions (Yaqoob, 2017).

Future Works

The product promotions and allowances are visualized in the analysis with the guided paths that includes the managers for monitoring the performance in business. The analysts tend to drill down with microscopic details of business with the corporate organization capable of manufacturing and the reseller model that is based on the transactional history data from supermarket partner. It involves the spending on different platforms and monthly sales and the online experiments are for the social media platform that focus on the subjective hedonic benefits with the sustainable chocolates. The focus is on the objective quality for the sustainable labelled chocolates.

Conclusion

The discussion is on the MS excel with the non-coding purpose. Hence, R is for the complex that is based on the coding language with the lattice package. The approach is for the iteration, modelling and communication that is easy to use for R. The business analysis is based on the Tableau or MS Excel with the business trend showing R with the visualization that is followed by Tableau. The information is based on banding for the senior managers with customers snag shareholders with the building competitive advantage that holds the potential with lowered costs and maintaining sustainable development. The firm operations are for the lens of sustainable development which not only reduce the costs but also increase the revenue. The commensurate of the risks is for facing the fines and penalties and costs of remediation with proper clean up. The environmental performance, R&D efforts is for the social well-being of employees with the proper treatment of programs.

References

Chang, V. (2018). Data analytics and visualization for inspecting cancers and genes. Multimedia tools and applications77(14), 17693-17707.

Conner, C., Samuel, J., Kretinin, A., Samuel, Y., & Nadeau, L. (2020). A picture for the words! textual visualization in big data analytics. arXiv preprint arXiv:2005.07849.

Golfarelli, M., & Rizzi, S. (2020). A model-driven approach to automate data visualization in big data analytics. Information Visualization19(1), 24-47.

Chang, V. (2018). A proposed social network analysis platform for big data analytics. Technological Forecasting and Social Change130, 57-68.

Marjani, M., Nasaruddin, F., Gani, A., Karim, A., Hashem, I. A. T., Siddiqa, A., & Yaqoob, I. (2017). Big IoT data analytics: architecture, opportunities, and open research challenges. ieee access5, 5247-5261.

Nguyen, V. Q., Nguyen, G. T., Nguyen, S. N., Choi, J., & Kim, K. Big Data Analytics and Visualization Techniques: A Case Study from Agriculture Domain.

Fiore, S., D’Anca, A., Elia, D., Palazzo, C., Nuzzo, A., Weigel, T., … & Aloisio, G. (2018, April). ECASLab: a user-friendly, integrated environment for scientific data analytics and visualization in the European Open Science Cloud landscape. In EGU General Assembly Conference Abstracts (p. 18497).

Núñez-del-Prado, M., & Goméz, R. (2017, March). Learning data analytics through a problem based learning course. In 2017 IEEE World Engineering Education Conference (EDUNINE) (pp. 52-56). IEEE.

Hanamanthrao, R., & Thejaswini, S. (2017, May). Real-time clickstream data analytics and visualization. In 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) (pp. 2139-2144). IEEE.

Fan, X., He, B., & Brézillon, P. (2017, June). Context-aware big data analytics and visualization for city-wide traffic accidents. In International and Interdisciplinary Conference on Modeling and Using Context (pp. 395-405). Springer, Cham.

Leung, C. K. (2018, September). Data Science for Big Data Applications and Services: Data Lake Management, Data Analytics and Visualization. In International Conference on Big Data Applications and Services (pp. 28-44). Springer, Singapore.

Yang, H. F., Chen, C. H. K., & Chen, K. L. B. (2019, July). Using big data analytics and visualization to create IoT-enabled science park smart governance platform. In International Conference on Human-Computer Interaction (pp. 459-472). Springer, Cham.