Advantages of Data Analytics in Business-to-Customer (B2B) Applications
Data analytics can be defined as a quantitative and qualitative processes as well as techniques that are utilized to boost profit in business and productivity. Extracted data s divided into various categories in order to identify and carry out the analysis of behavioral patterns and data. Technique for this may vary depending on the requirements of the organization (Singh & Reddy, 2015). Data analytics can be implemented to applications that are business-to-customer (B2B). Global companies extract as well as analyze data that are related to business processes, customers and practical experience. The data is divided into various categories, stored and then analyzed for understanding the purchasing patterns and trends. It also helps the organization in evolving the data facilitates with the help of proper decision-making.
An example of advantages provided by business analytics is that, a social networking site extracts information related to the preferences of user, community interests and many more (Kwon, Lee N., & Shin, 2014). This is done by considering some factors such as gender or age of people, demographics and some more. If the analysis is carried out appropriately, they reveal customers trends, customer trends and layout as well as the overall strategy. Data analytics provide various benefits to organizations; some of the benefits include data visualization, data diversity, agile analytics and many more (Stimmel, 2016). This report discusses regarding the benefits provided by data analytics to organizations. The benefits are described in details in the discussion part of the report.
The main asset of every organization is the data that it consists; data is the most important resource that an organization owns. Abundance of information changes the way an organization operates (Wang, Kung & Byrd, 2018). Data can be used to have insights that help the organization to take better decisions. There are various benefits that data analytics provide to the organizations.
The benefits provided by data analytics to organizations are as follows
- Data visualization: Raw data is extracted with volume as well as velocity. Data represented in graphical format is considered to be insightful compared to the representation done by numbering the sectors. This is the reason why data representation is very important (Kambatla, Kollias & Kumar, 2014). It helps any employee belonging to an organization to understand tough concepts and identify various unique patterns within the information available. They do not need to carry out complex analysis. The capacity of visualizing data is often considered as a tool that is good to have within an organization rather than a necessary tool. This leaves the valuable insights and the change required not realized by the organizations. The data that an organization owns should be commonplace and it helps them to make decisions (Qin, 2014). This is because they can use insights in order to carry out data mining. They are allowed to explore data for finding new patterns as well as relationships. It also helps in completing quantitative and statistical analysis for explains the reason of various results. It also helps organizations to test past decisions with the use of multivariate testing and A/B testing. Data analytics uses predictive analytics and predictive modeling to find out future results (Reyes-Ortiz, Oneto & Anguita, 2015). It also supports the organizations to carry out tactical proactive decisions. Business analytics make it possible for the organizations for automating decision making for supporting real-time feedbacks.
- Customer profiles: Data analytics made with the help of advanced data analytics solution help the organizations in acquiring complete profile of customers that allow more amounts of personalized experiences of customers at every point (Alsheikh, Niyato, Lin, 2016). Here the contact is done through the complete journey of the organization. Data analytics solution removes data niches. This is done so that companies can acquire a unique thought regarding the customers which consists of industry-specific and calculated matrices which allow the construction of a record in details for behavior of every client. The profiles give the organization a global and category of visualization tools is very easy for the organizations to adopt and provide an unexpected advantage to the organizations. Data analytics has helped the companies like Apple Inc., Samsung and many more to improve their customer experience.
- Data-driven decision making: Most companies use data analytics for making data-driven decisions. Business analytics allows the organizations to automate as well as optimize the processes of business (Ji-fan, Fosso & Akter, 2017). The data-driven organizations that use Business analytics enjoy an advantage that helps them in staying competitive erstanding of the clients that they have (Fosso, Ngai, Riggins & 2017). This understanding is carried out through in-depth knowledge of clients as well as its operations. A very good example of data-driven decision making is of Google. Google has created a People Analytics Department in order to help the organization to carry out HR decisions with the help of data available. The decisions that are made include decision regarding the difference brought about in the performance of team by the manager. The department uses performance reviews as well as employee surveys in order to answer this particular question.
- Data diversity: More information often leads to more insights. Data diversity involves tracking down the sources that are disparate, unstructured data and data sets that are varied (Liu & Shi, 2018). Usually most of the businesses are not able to overcome this obstacle. The data storage should not be a matter of problem; it might be stored in data warehouse, in Hadoop, in desktop, in excel or cloud. The data might be structured, unstructured or semi-structure. An example of this is that, Unilever has combined sales, social data and weather for optimizing advertizing in the marketing strategies. If the organizations keep employing the tools of data blending such as Alteryx, they can remove the space between the sources (Chen, Preston & Swink, 2015). A represent able process can be created which would consume only minutes and not weeks for refreshing. This process can be created by improving delivery approach.
- Provide ideas: Data analytics has the capability to provide ideas from an unlimited amount of information from various sources which include the ones that are received from the third party sources, social networks, and the information stored in database of the company, from internet and many more (Fan, Lau & Zhao, 2015). Real-time monitoring as well as forecasting of various occasions which hold the chances of affecting the operations or performance of the organizations. With the help of data analytics, organizations are allowed to locate, extract, get, change, blend and analyze data with the help of various tools. It also helps the companies to identify important data which can improve the type of decision making (Marr, 2015). It also helps the organization to mitigate numerous risks by optimizing various difficult decisions regarding events that are not planned. Identifying the reasons of failures and issues in real time. Complete understanding of the capacity of marking that is data-driven. Customers are provided with various offers depending on their buying habits. It improves commitment of client and increases their level of loyalty. Revolution of risks portfolio is carried out in n time. It also helps the organization to customize the experience of customers (Khan, Anjum & Soomro, 2015). Organizations can also add value to interactions taking place with the online as well as online customers.
- Overcoming challenges that are reimbursement: data analytics provide advantages in various businesses. It helps the medical field as well (Diamantoulakis, Kapina & Karagiannidis, 2015). It helps the medical fields by overcoming challenges that are reimbursement-based. Information storage as well as reporting is very important for the providers that are looking for showing results. Every medical institute changes their incentives structure and payment systems. Providers are supposed to adapt by the clinical analytics as well as tools of business intelligence (Park, Nguyen & Won, 2015). This helps the institute sin various ways such as payer underpayment, data-driven approach and pricing transparency. Underpayments lead to claims auditing and higher billing that are inefficient. It also leads to costs of contract administration. Usage of effective data analytics, providers are able to ensure the accuracy of payment and complete reimbursements. Following an outstanding strategy of data-driven approach allows in claiming increased accuracy and assessment process (Ahmed, Yaqoob & Hashem, et al., 2017). Employees want increased transparency, providers should strive in order to keep a constant balance between value and cost without compromising on the quality. One more advantage provided by data analytics to the medical field is flexible IT. It provides a backend which collects data from various sources. Some data collected include clinical data, tests, and medical histories, records regarding procedures carried out, diagnoses, medication, inpatient as well as ambulatory records and images. This contributes in providing better results. It helps in increasing the level of data access beyond a particular individual (Zhao, Fan & Hu, 2014). This as a result, helps in taking better decisions and increase in personalized care.
- Anticipating and proactive needs: Organizations face a huge level pressure due to the competition that has been going on in the market between various companies (Hu & Vasilakos, 2016). The competitive pressure creates an additional pressure on the organizations of understanding the requirements of customers and the ability of optimizing experience of customers as well as maintains a healthy relationship among them which would last long. Organizations share their data and allow the customers a relaxed privacy while they use the website of the organization. This convinces the customers on the fact that the organization knows customers through various interactions and allows a seamless and perfect experience (Choi, Chan & Yue, 2017). For this purpose, the organizations require to reconcile and capture different identifies of customers like email, addresses and cell phones into a single ID. This IFD would be provided to the customers and can be used by both the company as well as customers for future purposes. Customers do not need to provide their details to the organization on its official website. It saves time as well as makes the process much easier. Customers use different channels for interacting with the companies. As a result in order to understand the behavior of customers the sources of digital data as well as traditional data should be considered (Liang, Hong & Shen, 2016). Along with that, customers think that the companies require delivering real-time and contextually relevant experiences.
- Mitigating risks: The main objective of security analytics is to protect overall intellectual and financial assets. They secure the data from being misused by unauthorized users. They also help them in saving from external as well as internal threats. The analytics capabilities and efficient data helps in delivering better results by preventing frauds, as a result it provides the security to entire organization (Seddon & Currie, 2017). Deterrence needs various mechanisms which would let the organizations to find out fraudulent activities if any in no time. It also helps in anticipating the future activities and track perpetrators within the company. The organizations can use network, path, statistical as well as big data methodologies in order to predict models of fraud propensity that result in mitigation and alerts. Data analysis provides transparent as well as efficient reporting of the mitigation of fraudulent problems. It also provides a better process of fraud risk management (Seddon & Currie, 2017). Along with that, correlation and integration of data all over the organization might provide a unified display of fraud allover various categories of business, transactions and products. Data foundation and analytics that fall under the category of multi-genre provide more precise fraud trend forecasts and analyses. An example of this is that suppose, a user loses his phone and he has all his personal data saved in his device that can be misused by an unauthorized user. Just one tap on his device made by the thief would inform his closed ones and sometimes cops as well that his device had been stolen. This is done by some settings saved by the user in his device.
- Agile analytics: Time is the actual key that could help in gaining necessary insights from provided information. Business intelligence projects that follow the traditional methods take many years to come into action. A breakdown for a long term in the visibility provides a solution which does not fit into the actual requirements. Agile analytics has been turning the traditional BI and reduces the time to value (Jun, Liu & Lee, 2015). When new tools are introduced, better insights for business could be delivered within few weeks or months. In this case, they main key is collaboration. Analytics experts are able to perform the testing of iterative processes for creating a solution that is working. This is done by combining various factors such as raw materials, a group of people and hypothesis with enough knowledge on the domain. These sort of quick deliveries allow the organization to decide if the implementation of long-term would be good for their business.
- Holistic approach: providers have seen the value of interpreting and understanding information from numerous sources that are nontraditional like socio-economic factors. Providers require relying on the vendors in order to provide a specific IT infrastructure that would comply with the given deliverables. It also helps in collecting and analyzing data from various disparate sources, provides analysis of round the clock nature and facilitates the data searches
- Delivering appropriate products: Products are sort of life-blood for any organization. Products are the part of an organization where they invest the most because quality of the product is more important for customers (Lee, Bagheri & Kao, 2014). The role of the project management team to understand the trends that lead the roadmap of strategies for new innovation, services and new features.
- Personalization and service: Companies continuously struggle with data types that are structured. They require being very responsive in order to maintain their standard with the level of volatility that is created by the customers. This happens when digital technologies are introduced into various organizations (Kalantzis, Malossi & Bekas, 2018). Advanced analytics helps the organization to convince the customers that they are really valued and react in real time. This increases the intensity of the activities going under the organization; it also increases customer satisfaction among the customers. Data analytics provides the opportunity to an organization to maintain a healthy level of interaction on the basis of the customer’s personality. This is done by gaining knowledge regarding their considering factors like real-time location. Real time location helps the organization to deliver personalization in an environment of multi-channel service (Kalantzis, Malossi & Bekas, 2018). The interaction can also be maintained by understanding the attitudes of the customers by knowing about their likes and dislikes, products that they prefer more, products that they often buy and any more.
- Self-service analytics: Various professionals belonging to different organization have this misconception that handling data needs advanced skills in programming. Previously this might be happening and due to which, the professional grew this misconception. Nowadays the development in technology has solved the problem and professionals do not need to acquire advanced skills of programming (Ribeiro, Silva & da Silva, 2015). In these days, professionals having basic data regarding data handling can be considered as data scientists. The usage of analytics tools and providing basic training to the employees every team in a particular business can get the desired value from the data. Providing training to the employees has been proven to be the most helpful for data handling. Various organizations are working continuously in order to improve the skills of employees as a subpart of agile approach to the data analytics. This ensures development of the organization. Data can be blended and visualizations can be built. This process would require the help of an IT infrastructure. Proper data collection from the third party sources. Here people express their options and thoughts that are combined with the analytics (Ribeiro, Silva & da Silva, 2015). This would help the companies to remain competitive in the market. It also helps them to stay constant when the demand of customers change or other new technologies are introduced into the organization.
- Improving and optimizing customer experience: Poor or improper management of various operations would result in myriad of different costly issues such as damaging customer experience, it would result in damaging the brand loyalty. Implementing analytics for the purpose of designing, optimizing the operations of the business in production of services and goods, controlling the processes and many more ensures the effectiveness as well as efficiency of fulfilling expectations of customers (Manogaran, Thota & Lopez, 2018). Advanced analytical strategies could be deployed for improving the field efficiency, productivity and operations. It can also be deployed to optimize the workforce of organization based on the needs of the business as well as customer demands. Utilization of analytics and data would ensure constant improvement in the processes undergoing in the organization. For example, numerous organizations consider inventory as the greatest asset that they posses. Excess inventory or deficit of inventory may affect the organization’s profitability as well as direct costs. Data analytics is able to help organizations in inventory management. This is done by allowing uninterrupted production of customer-service levels and producing sales in very low costs. Usage of data analytics allows the organization to maintain transparency among the planned as well as current inventory position of the company (Hurwitz, Kaufman & Bowles, 2015). it also helps in delivering insights in the drivers of various height and composition it also delivers insights to drivers with location of stock and aid determination of the strategy of inventory as well as decision making. Customers want a seamless and relevant experience; they also want the organization to gain knowledge regarding the places where they engage themselves.
- Advanced analytics: Advanced analytics has been used by various organizations since a long time, but it is being continuously prevalent, even for the ones who do not hold a PhD degree. Most of the businesses use analytics in order to learn from their past experiences. As mentioned above, data is the most valuable asset of an organization, companies might move from the ‘descriptive’ form of analytics to the ‘perspective’ form of analysis (Cheng & Li, 2016). Before following the procedures to make the changes, the organization should be sure that they are utilizing the right processes as well as tools. The organization should be very confident that their historical data are appropriate and then proceed with shifting to ‘perspective’ form of analytics.
For example, the major aspiration that can be taken into consideration is that the data management betterment can be seen in the case of the prosecution of the Ritz Charlton hotel that provides brilliant after use services and this case scenario will definitely prove the better understanding of the business intelligence.
Conclusion
From the above report, it can be concluded that the procedure of analyzing data for deriving conclusions that would be useful for the organization in future is called data analytics. Data analytics consists of various operations on tables or data sets that are available in the database. These operations consist of data profiling, data extraction, data deputing and data cleansing and many more. The solutions and tools are utilized by different industries such as finance, banking, telecom, insurance, aerospace, healthcare, social media, retailers and many more. It helps the organizations to delete duplicate data and saves a huge amount of memory that can be used for other purposes. The major advantage provided by business analytics to the organizations is reducing their costs. The advantages are described in details in the discussion part of the report.
Benefits of Data Analytics for Organizations
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