Predictive Analysis Of Predictive Analysis, An Integral Part Of Any Business

“Predictive analytics uses technology to predict the future and influence it.” [27] It is predominantly being used to improve business processes, which is a great opportunity for entrepreneurs to achieve positive business outcomes [26]. The goal of this white paper is to discuss the impact of predictive analytics in today’s world and the various concerns that come along with it. The paper addresses key research questions like what are the legal and ethical concerns that rise from predictive analytics? And where can we use predictive analytics to get positive results? We have tried to analyze the current market situation in order to answer these questions, focusing on the key areas where predictive analytics has had positive and negative impact. After intense scrutiny of the facts and details encountered by us, we have come up with some recommendations and solutions to address the issues caused by the use of predictive analytics and how their effects can be balanced by organizations.

* Forecasting is an impartial strategic ingredient that will ensure apt base for reputable planning. Our forecast is always the first step in developing plans in running the business along with our future plans of growth strategies. With this tool, we are able to anticipate our sales within reason that then can allow for us to control our costs in conjunction with inventory which will then help us to enhance our customer service. Sales forecasting is a vital strategic tactic in our company’s methodology.

The customer analysis is the depth analysis of the end-users; this entails all of the characteristics of the customer. These characteristics include the following:

essential to consider and focus on the value the customer base possesses. Marketing research was initially

Retention is a reflection of a customer’s willingness to remain with a particular company’s service or products and is useful to measure customer loyalty. The relationship

Do you really know your customers?  In recent years, managers have come to realize the importance of measuring and maximizing the lifetime value of individual customers - and with good reason.  After all, why spend valuable marketing dollars to attract and retain minimally profitable customers when you can spend the same amount - or less - to capture and cultivate more profitable ones?

Markets consist of buyers that differ in their needs, wants, resources, locations, buying attitudes and buying practices. To reach customer insight, it is important to understand the needs of different segments and to communicate pertinently to them (Brown L, Brown C, Gallagher SM, 2008).

Sales can mine the data to qualify prospects, use job titles to identify decision makers or locate companies similar to current customers. Discussions involving potential customers can reveal companies that are in need of your product or service, allowing sales to contact them earlier in the purchasing process and tailor the pitch to the customer's immediate need.

This gives businesses the opportunity to create product differentiation strategies that will help them establish and maintain a competitive edge in the market. This information also helps identify specific opportunities for further growth and development with existing products and services as well as potential opportunities for new products and services. The data gathered in this way helps businesses create successful marketing strategies that will appeal to customers personally and help promote great brand recognition. This area is so intriguing and worth more knowledge and development because it creates opportunity to get a better understanding of how people personally identify with the product or service they use and the why behind it. This method goes against the grain of management skills in which they stress the idea behind information is only as valuable as the money it can produce as this often refers to concrete numbers or dollars and sense and qualitative data is not captured in that way. It brings back the idea of getting to know your customers on a more personally level which helps to build trust and relationships that can be lost when looking at big box industries.

Many marketers agree that by reducing customer’s to competitors defection by only 5 per cent, companies can improve profits by anywhere from 25 per cent to 95 per cent. There is no question this will be a great advantage and could benefit any retailer. It is for this very reason why consumer’s relationship marketing and using tools such as loyalty scheme is

Comments: * 2.a) Financial ratios were calculated in the appendix but limited consideration was given to industry trends and benchmarks. To improve the response to an ME, ensure to include a discussion of relevant benchmarks and trends and leverage in the analysis of the alternatives. * 2.b) Some consideration was given to key decision analysis concepts and tools listed in this component (profitability, customer mix analysis) but overall the component can be improved. To improve the response to an ME, consider using additional tools such as a sensitivity analysis when considering the impact of different scenarios for the customer mix segments to target.

Regression models are very useful in determination of important statistics in the corporate world. For instance, multiple regression models can be used to determine whether advertising, product loyalty, or price is the most important determinant of business growth. With this information, businesses are able to focus their resources into the channels which will help them achieve their targets effectively. It can also be used to calculate the predicted mileage for a vehicle with respect to different possible variables such as weight of vehicle, age of vehicle, and climate of country. Car manufacturers can capitalize on

Customer retention/attrition is estimated by the Company to arrive at the adjusted revenue, however, no support is provided for the 75% of probability of retention.(Exhibit XI) Retention rate can be expected by conducting statistical analysis of historical customer turnover and revenue growth rates. When historical customer data of sufficient quality is not available, it may be necessary to rely on management estimates or industry data. Probability of retention is

A customer profitability analysis, when done right, shows the customers that are not only profitable but also those that are

Forbes used SAP BusinessObjects software to analyze and understand individuals, which helped them make precise decisions and increase their circulation. Both companies, Quidsi and Target, used predictive analytics to identify the trend and customer’s behavior. This helped them gain more customers, make effective decisions, and avoid time and money spent on useless things. Monster.com used SAS statistical modelling software and Unica marketing database to find potential customers who would likely purchase job listings and keep in contact with all of