How to conduct data mining for monetization
“Data is rich, information is poor.”
with businesses adopting measures that are geared towards retaining and pleasing their shareholders and investors, the need to identify potential customers and generate demand has been made possible by interpretation of data available to them with the aim of defining possible opportunities that can be derived through studying the various trends in those datasets, a procedure also referred to as predictive analytics. Upon successfully identifying the undiscovered opportunities, the data can then be used to model new products and services as well as guide in determining the appropriate way of structuring internal processes towards attaining the desired efficiency levels.
In this article we are going to look at various perspectives that can be used to gather data with the intention of monetizing it by availing it to others as a means to innovating the necessary solutions to problems manifested by interpreting that data. To start with this platform, infomatism, we took it upon ourselves to monitor trading as conducted in the Nairobi stock exchange and with the passing of every month we compile a price trend that proves very useful to the existing shareholders on the possibility of a yield from their share capital in trading portfolios that are of particular interest to them. The data can also be used by speculative traders who wish to identify listings that guarantee maximum returns as well investment analysts who would wish to use the data as aid to summarize the performance of different economic sectors.
Data mining with the intention of monetizing must clearly demonstrate the problem or opportunity that lies therein when analyzed into a graph or some tabular representation. Let me use an ecological example in Kenya where wildebeest migration trends have led to the phenomenon largely known as the Maasai Mara migration. The detailed study of the pattern of this migration has led to setting up accommodation, payments and travel facilities that cater for all who tour the Maasai Mara to witness a first-hand account of this phenomenon. Other areas that could greatly benefit from monetizing data include the daily occurring routines like power consumption and airtime vouchers that help service providers gain an in-depth understanding of their customers as way of improving their services to them. For example, producers of smart gadgets for domestic use can monetize their data by availing to real estate consultants who will use it to come up with energy-efficient projects for their prospective customers.
Financial services could greatly benefit by analyzing the sale volumes by particular intervals as well guide businesses in conducting customer segmentation. The data could help a long way in establishing when it is necessary to intensify advertising to the appropriate customer segment as well offering product and services promotions. Financial tools also have the capacity to show the location of the customer when making payments and this could help the utilization of their services by region hence facilitating them to come up with the right approach on how to enhance accessibility or improve uptake where it is low. The geographical location for example in payment services greatly aids in identifying signals associated with fraud. App developers of mobile payments systems also use location indicators to sense adoption and engagement of their tools as a way of establishing outreach.
Service delivery as well inventory control could come handy when analyzing data utilization in the health care system. Important aspects in the health sector that make use of data include inventory control, machine utilization through access metrics, speedy access to quality healthcare aided by telemedicine where health care providers monitor patients who opt to recover from home while also catering for staffing and operational costs within their institutions. Data is also vital in assessing patient admission patterns as well diagnostic details that helps institutions predict patient admission volumes and revenue streams in addition to improving the time taken from arrival to treatment and avoiding costly U-turns that can tarnish their reputation.
With that we hope that you have gained an eye-opener on the importance of data mining in your area of specialization with the aim of improving efficiency in business operations and improved insight into customer needs to help you identify leads and generate demand.