Identifying Market Niches in the Age of Big Data

Week 2: Team Case Analysis: Identifying Market Niches in the Age of Big Data Group 5: Summary The amount of data available today to companies around to globe allows marketers to develop strategies and technology to analyze and collect the data available to create market niches. One example is the e-book market. In the E-book market, companies are providing their customers unlimited access to an extensive selection of titles and categories for a monthly flat fee. Services of this market, such as Scribd, Entitle, and Oyster are taking similar approaches to like the biggest companies like Amazon and Barnes & Noble to gather data on what their customers are reading. The collection of data by these companies allows them to know if customers finished a book, skipped portions of the book, most popular titles and categories read, and many more. With the collected data, marketers, as well as publishers and publishing companies, provides writers the necessary information to better target its customer's readership. The main problem with this approach in the E-book market is the union of large publishing companies with subscription services. (Laudon & Laudon, 2016, p.100) Other examples regarding the gathering of data are the airline and car industry. In the airline industry, the majority of carriers collect the data of their customers to keep track of their customer's flying experience. The collected data is linked to previous experiences of customers that may include seat preference, misplaced luggage, allergies from passengers, top customers, and more. With the gathered data, marketers can expand their knowledge and give them a great opportunity. For example, a travel company besides the flight can provide extra services like guided tours, car rentals, hotel reservations, etc. Another big industry that has decided to hop into the collection of customer data is the car industry. While the airline industry is focused on customer satisfaction, the car industry is focused on customer satisfaction and the performance of its product (cars). (Laudon & Laudon, 2016, p.100) A good example is Ford. In 2016, Ford Motors decided to implement a complex database that would allow them to develop a program to increase sales. With the collected data, Ford would be able to send specific recommendations to dealers so they could recommend or "persuade" customers to select a vehicle of the brand. Besides increasing revenue, Ford wanted to take a step further by collecting data on their product performance. Collecting fuel economy, vehicle performance, mechanical failure, safety metrics, it would allow Ford to improve the engineering of its vehicles. (Laudon & Laudon, 2016, p.100) The collection of data to create market niches and make it easier for marketers to have a better understanding of the market sound like a great idea. The problem with this type of approach is the privacy of the customer and security implemented to keep the data safe. Collecting the data of customers can reveal information such as the latest locations visited, bank information, personal information, address, and more. This creates a privacy issue and invasion because companies will be able to know information that the customer may not feel comfortable sharing or not willing to share to satisfy a customer experience or product performance. Companies in this modern era need to look for alternatives or secure methods to collect data that wouldn't invade or reveal the privacy of customers. Support Marketers are interested in data collection because of the many opportunities it provides to target customers. Data is a piece of information that can be provided in different forms, but some forms are more valuable than others. In the case of organizations, they tend to look into user-generated content (UGC). According to Lukyanenko et al. (2019), "Organizations are increasingly interested in user-generated content (UGC), information produced by members of the general public (the crowd), who are often unpaid and not affiliated with the organization" (p.624). Organization can gather data utilizing UGC from social media, blogs, customer reviews, or even create tools and processes to have a better understanding of markets. According to Lukyanenko et al. (2019), "Organizations can use UGC to better understand their customers, competitors, products, and services, or the social and political environment" (p.624). With the data, collected organizations can develop custom-build systems to distribute the data and organize it in different categories, as shown in Figure 1. Figure 1: Custom-build system organizing and distributing collected data into categories. While organizations are gathering information to have some penetration into the markets, there is a concern with the privacy and security of the data collected. According to Amiraullt (2019), "This brings up multiple, problematic issues surrounding individual privacy and security that remain unanswered and show no signs of satisfactory resolution in the near future" (p.59). Most of the time, when organizations collect data, they might obtain more than it was supposed to that even the customer may not be aware of but still be used by organizations to target their customers continuously. According to Seago (2018), "The more data the organization has, the more incentive it may provide malicious actors to hack into it, thus compromising security and privacy" (p.45). It is crucial for customers and organization know that the collected data is being kept safe because they never know who may be able to have access to it; as Robert Berry, executive director of Internal Audit at the University of South Alabama says "Know who is relying on the data and what they are using it for." Evaluation A niche market is a segment of a larger market that can be defined by its own unique needs, preferences, or identity that makes it different from the market at large. For example, within the market for women's shoes are many different segments or niches. A business niche is a specialized or focused area of a broader market that businesses can serve to differentiate themselves from the competition. Business owners should find a niche in their industry that has underserved or unmet needs. Business Intelligence Differences Between Business Intelligence And Big Data Business Intelligence in simple terms is the collection of systems, software, and products, which can import large data streams and use them to generate meaningful information that point towards the specific use-case or scenario. Big data is the most buzzing word in the business. Big Data is changing our day to day business life. Everybody thinks that Big Data is nothing but a massive amount of data. But in reality it’s not a just massive amount of data, it is also about the structure of the data, processing the data with the purpose of delivering added value to the organization. Head to Head Comparison Between Business Intelligence and Big Data (Infographics). Below is the Top 6 Comparison between Business Intelligence vs Big Data Below is the list of items, explaining the differences between the Business Intelligence and Big Data. Both BI and Big data goal is to help the business to make good decisions by analyzing the huge datasets to expand the business and optimizing the cost. This data analysis not only enables decision making but also involves an active part in the development of strategies and methods that make sure the success of organizations. This data analysis can be called “Business Intelligence”, whereas “Big Data” is a relatively new term for Business intelligence. Business Intelligence is based on the principle of combining all business data sets into a central server, this data will be analyzed in offline mode, after saving the information in a platform or environment called Data Warehouse. The data sets are structured in a relational database with additional indexes and forms of access to the tables in the warehouse. Whereas in the Big Data environment, data is stored on a distributed file system (e.g. HDFS), rather than storing on a central server. Data will be distributed across the worker nodes for easy processing. The Distributed File System is much safer and flexible. BI solutions carry the data to the processing functions, whereas Big Data solutions take the processing functions to the data sets. Since the analysis is positioned around the information (Data), it is simpler to handle large amounts. BI solutions are more towards the structured data, whereas Big Data tools can process and analyze data in different formats, both structured and unstructured. Big Data technology uses parallel processing concepts (Map reducing algorithm), which improves the speed of analyzing and processing the data sets by distributing jobs into several parallel execution processes, at the end the results are combined and shown, this makes analyzing the large volumes easier. Conclusion: In the present era, the importance of data in business is very vital; because meaningful decisions can be made only with analyzing the data and these decisions will help business to grow further. Both the BI and Big data helps to analyze the data to get the insights and to view the relevant data. Business intelligence and Big Data need to be synchronized, need to be used together. They both are not the same thing, but they share a lot of the same common goals. A lot of the distinctions between Business intelligence and Big Data tend to be arbitrary. Management Information Systems (MIS) Micromarketing In the Age of Big Data: Scoring Bigger Payoffs For A Super Sales Play Micro Markets are sales hot spots with tremendous potential. Adopting a more granular strategy, micromarketing for sales has taken on new relevance in the age of Big Data. Combining, combing through, and sorting data is the key to an effective strategy for sales. It’s not just about sifting through transactional and purchasing data in the B2C space. B2B players are now mining data for a sound micromarketing strategy and personalizing sales pitches for customers in real time. Big Opportunities for Big Data: In the B2B space, Big Data is sourced from e-commerce sites, social networks or even call records. CRM databases are undergoing a paradigmatic shift, as data increases in complexity and mining software becomes critical for managing massive data sets and vast repositories of information. Big Data represents a whole new world of opportunities for B2B sales. Discovering new growth areas/micro markets and equipping sales forces to capitalize on these is a powerful way to reach sales targets. Micromarketing strategies are ultimately focused on mapping and tapping opportunities for sales growth. Sizing Up Your Micro Market For Sales: Micro Markets should be of an optimal size, so the sales force is effectively utilized and able to execute plans effectively. Drivers of customer purchases in each micromarket can point to which of these sales hot spots will actually thrive. Clarity on demographics, cost of capital and input and other factors driving customer purchases is imperative for identifying the drivers for success. Big Data analytics and sales data can then be used to gauge the potential for market share and growth. Understanding the variations in micromarket share that ensue and the reasons for these can impact the efficiency of sales strategies. Sales reps need to embrace sales strategies that actually work well, and for this reason, micromarketing is invaluable. Growth In Your Pocket?: Market share analyses can also point the way for which growth pockets to focus on. Prioritizing micro markets requires an approach that refines and builds on data. Mapping future opportunities is easier with a micro market map in place. Insights revealed by sales analysis can help in the effective deployment of resources. Salespeople need to understand how to implement micromarketing and align sales strategies with opportunities for creating the right plays. Only then can a brand power profits and reach record sales volumes. Powering Sales Play: For powering your sales play, your sales managers need to focus on micro markets that share commonalities. Micromarket peer groups must be identified to target the right audience. For selling into micromarkets, salespersons need to aim for high-growth markets and devise the best sales play in approaching the customer segments. Sales managers work hand-in-hand with field salespersons to understand the rationale for peer groups. They also need to devise micro marketing strategies and plays for groups. For micromarketing to succeed, sales should ideally focus on experiential elements. Hot and cool micro markets have to be identified and tested against hard data. Experimenting with sales plays is not a one time effort. Data needs to remain at the heart of sales forever. Your sales department should, therefore, be data-driven to realize the potential for B2B growth. Essentially, micromarketing involves expanding sales strategies on the strength of data analytics. Data handoffs and feedback loops between marketing and sales further serve to bridge the gaps. The most effective sales organization is clearly the one that puts data analytics at the center of sales strategies. Know Why Customer : Consumer purchase history, service experience, satisfaction levels, product usage, and consumption patterns are just some data points that serve to inform the micromarketing sales strategy. Bridging the gap between data and sales, micromarketing is the key to understanding the customer and building a powerful brand. Moving past sales scripts that don’t work to sales pitches that do, micromarketing strategies are a leap forward for a salesperson as the Fourth Industrial Revolution powers growth and helps businesses to thrive. Conclusion : Micro Markets are sales hot spots that serve as catalysts for accelerating sales growth. Utilizing local growth, a geo-targeted, niche or segment-oriented approach pays off. Bigger is not always better. With micro marketing strategies in place, less is more. To offer campaigns and marketing messages customers actually find useful, personalization is missioncritical, and this is where such strategies work like a charm. Micromarketing helps sales managers and reps to focus on what delivers value to the customer and delight them with magical “wow” experiences. In the age of Big Data, where the customer is king, this offers incredible returns. Using content and campaigns to humanize your brand is easier than you think, with micro markets aligning with big-ticket sales and marketing plans. Micromarketing is the strategy sales personnel clearly need to utilize if they seek big payoffs and bigger ROI for their B2B brand. Questions After studying and working on this team case analysis below are the question which we would like to address. 1. What are the kinds of data being analyzed by the companies? The different companies mentioned in the case analyze different kinds of data. To begin with are the companies that specialize in the e-book market, and these include Scribd, Oyster, Entitle, Amazon, Barnes and Noble, and Good reads. These include data on preferred reading materials, frequency of reading, and most desired topics. Analyzing such information would guide the ebook companies on what to supply to their readers. Secondly are companies in the airline industry such as British Airways, Delta Airlines, Qantas Airways, and United Airlines. This can be xplained furthur taking examples of three industries. Data about e-book purchases and reading habits are being collected and potentially sold to book publishers. The data include whether a book is completed, if pages are skimmed or skipped, and which genres are most often finished. Airlines are collecting all kinds of passenger data that can be consolidated to build comprehensive customer profiles. Cabin crews can then use the data to identify certain characteristics about on-board passengers and personalize the flying experience. Car companies integrate databases and use complex algorithms to more closely match car lot inventory to buyer demand. Vehicle turnover rates improve and the price a consumer pays minus the manufacturer subsidy rise, increasing Ford Motor Company’s profits. Using vehicle Internet connections, the company intends to collect fuel economy data, mechanical failures, and other safety and performance metrics to improve product engineering. 2. How is this fine-grained data analysis improving operations and decision making in the companies? What business strategies are being supported? This question can be explained taking examples of below three gaint industries: E-book data: The idea is that writers can use it to better tailor their work to their readership and book editors can use it to choose which manuscripts to publish. Business strategy supported— focus on market niche, product differentiation. Airlines: the data collected can enhance the passenger experience, improve customer service and fashion relevant marketing pitches. Business strategy supported—product differentiation, customer intimacy. Car companies: which cars to build, which features to include or enhance, which cars sell better than others in different parts of the country. Business strategy supported customer and supplier intimacies, product differentiation, focus on market niche. 3. Are there any disadvantages to mining customer data? Companies can mine too much data on customers to the point of upsetting customers and turning them against the company. Customers have complained that companies are collecting too much data and integrating it from too many sources. Companies defend their use of demographic data and data not covered under their privacy policies. Even customers who accept the inevitability of profiling are miffed when they receive unsuitable offers based on faulty personal information. Most customers want a line drawn between data collection to facilitate useful offers and data collection that is too intrusive. Although some airlines have curtailed their use of data collected, they continue to collect it nonetheless. None of the airline carriers currently allow customers to opt out of their data programs.