Benefits of data mining tools

SAP Expand child menu Expand. Web Expand child menu Expand. Must Learn Expand child menu Expand. Big Data Expand child menu Expand. Live Project Expand child menu Expand. AI Expand child menu Expand. Toggle Menu Close. Search for: Search. Data mining techniques are used in communication sector to predict customer behavior to offer highly targetted and relevant campaigns.

Data mining helps insurance companies to price their products profitable and promote new offers to their new or existing customers. Data mining benefits educators to access student data, predict achievement levels and find students or groups of students which need extra attention.

For example, students who are weak in maths subject. With the help of Data Mining Manufacturers can predict wear and tear of production assets. They can anticipate maintenance which helps them reduce them to minimize downtime. Data mining helps finance sector to get a view of market risks and manage regulatory compliance.

It helps banks to identify probable defaulters to decide whether to issue credit cards, loans, etc. Data Mining techniques help retail malls and grocery stores identify and arrange most sellable items in the most attentive positions.

It helps store owners to comes up with the offer which encourages customers to increase their spending. Service providers like mobile phone and utility industries use Data Mining to predict the reasons when a customer leaves their company. They analyze billing details, customer service interactions, complaints made to the company to assign each customer a probability score and offers incentives. E-commerce websites use Data Mining to offer cross-sells and up-sells through their websites.

Often, an expert needs to modify and interpret the clusters suggested by the algorithm before the results can be put into actual use. This is because sometimes it occurs that different algorithms end with a different set of clusters for the same data set.

The goal is to create groups so that members of a group have maximum similarity, and across groups members have minimum similarity, which can be useful for segmenting customers and directing appropriate marketing tools to the segments.

Sequential relationships discover time-ordered events. A clear example is predicting that an existing banking customer who already has a checking account will open a savings account, followed by an investment account within a year. Data mining has become a tool in addressing many complex business problems and opportunities, and has been proven successful in many different areas, including;. With its goal to build one-on-one relationships with customers by developing an intimate understanding of their needs and wants, data mining can come in very useful.

With all the data that is generated from various events product inquiries, sales, product reviews , there are many different ways data mining can provide more insight.

Data mining is complicated, but once you understand what it is about, it provides value in many different aspects. Fundamentally, a storyteller. After more than 10 years working in different marketing roles, she gained expertise and experience in marketing and growth strategies, B2B marketing, team management, product marketing, etc.

She joined Datumize in and since then she is being responsible for the overall marketing strategy, with especially focus on content generation. Big data vs. How Data Mining works Data mining builds models to detect patterns in collected data internal and external.

Associations Associations find commonly co-occurring groupings of things, discovering interesting relationships among variables in large databases. Predictions Predictions tell the nature of future occurrences of certain events based on the past.

Clusters Clustering means having natural groupings of things based on their characteristics, for example, assigning customers in different segments based on their demographics and previous shopping history. Sequential relationships Sequential relationships discover time-ordered events. And just as data mining does present real risks, it also presents the opportunity to significantly improve the fortunes of an organisation.

Ultimately data mining is all about uncovering information, and someone in the organisation needs to be ensuring that the costs of unearthing this information are smaller than the benefits it delivers. Mar 16, Jun 23, AI in Business.

Benefits Costs Data Mining Risks. You may also like. The Limits of Analysis Apr 3, Big Data and the Madness of Crowds Aug 4, Decision Automation — the next big productivity leap Nov 28, Cloud Economics — Try and Buy May 22, Mishal Roomi April 09, Data mining is a process where data is arranged systematically depending on the needs. In short it summarizes all the data and information for the sake of later use. It was introduced mainly to overcome the limitations faced during data analysis.

Where is Data Mining used? Today, data mining is used in various fields such as business, healthcare, insurance, transportation and government. Especially, data mining is used by businesses to understand large amount of data so that they can come to better conclusion regarding business growth.

Even though data mining offers countless advantages, it is still with some inconveniences. By knowing the pros and cons, the businesses can determine if its a worth investment. Through this post, you will know the pros and cons of using data mining.

Data mining process paves the way for new business opportunities. With all of the products, the right kind of business approach can be implemented using data mining. For an example, the right product can be delivered to the customer guarantying product sales.

Other than that, with the data mining information the businesses will be able to approach with different marketing techniques. Using data mining techniques, the businesses can create data models. From this models, they could easily identify the customers who will be interested in their products. Thus, the products that the businesses will be bringing into the market can be guaranteed to be profitable. So whatever the products introduced will be contributing to profit growth of the company.

Whenever a company is launching a new product, the data mining techniques can be used to develop it better. With all the information gathered, it can be compared with the competitors so that companies will be able to understand their customers better.

Hence, it is no doubt that data mining strengthens your company brand. For the purpose of data mining, various information are gathered on the basis of market.

Even if there is large amount of data, the analyzing can be performed without any problem.