Market basket analysis in insurance - the growing trend
Market basket analysis is a data mining technique used to search for meaningful associations in customers’ purchase data. The analysis is done using various data mining algorithms. Though it is largely used by the retail industry to drive sales, its applications are not limited only to the retail sector. It is also profitably used in insurance, banking, telecommunication, and healthcare. The insurance industry uses it to understand customer behaviour, existing and future purchase patterns, and how to incentivise and retain customers. Fraud detection is another useful application of market basket analysis.
Market basket analysis helps large retailers understand customer buying patterns. Analysts combine statistical techniques, machine learning (ML), and database technology to look at large data sets and extract hidden patterns across a combination of items frequently bought together. Market basket analysis is based on the theory that if a customer buys certain items, he/she is more likely to buy, or not buy, a similar set of items.
Market basket analysis helps businesses improve their marketing strategies, loyalty programmes, and other sales efforts that lead to growth in business. This way, businesses can be better networked and connected with potential customers.* Instead of focussing only on acquiring new customers, businesses can use market basket analysis to increase revenue from existing customers also.
Market basket analysis is not only about retail shopping. In fact, this technique can be used in healthcare to gather data pertaining to frequent diseases. Such information can then be used by medical and health authorities to take preventive measures and to keep the general public informed. Market basket analysis can be profitably applied to several other industries. The insurance industry is one such example.
Market basket analysis in insurance
New technologies, new products, and the emergence of many companies have made the insurance sector an intensely competitive one. Every company is striving to understand customer preferences and requirements. Companies collect and store massive amounts of data. Market basket analysis techniques help companies mine data patterns from these databases and understand their customers.
Understand client needs and forecast future purchases:
Build recommendation lists:
Detect claims fraud:
To maintain their position in a competitive market, insurance companies must understand customer behaviour and understand what factors influence their decisions. Data mining tools can determine purchase patterns of clients very reliably, which, in turn, can help companies gauge the popularity of their products. These analysis techniques, when applied on the data collected, can help companies become sentient regarding client needs.*
Such results could then be used to forecast the demand pattern for the next business cycle. And that, in turn, can help companies plan inventory, or in case of the insurance industry, hire enough expert advisors.
Market basket analysis is the basis for creating recommendation engines. Such engines can analyse requirements and recommend products and services to customers. This can be profitably used by insurance companies to boost sales.
Studying and analysing customer behaviour using market basket analysis helps companies suggest related insurance products to new as well as existing customers.
Companies can deter a customer from severing a relationship by using market basket analysis. A customer may be retained if the company is aware of the right incentives to offer.
Companies can use market basket analysis to detect medical insurance fraud. When companies build claim profiles, they can use this technique to determine whether more than one claim has been made by a same claimant during a specified time.
Success in market basket analysis
In addition to accurate and high-quality data, the success of market basket analysis depends on a few other factors as well.
Have enough data and suitable software:
Teamwork and support:
A company must have adequate methods and infrastructure in place to gather and store required data. Further, the data must be stored securely.
The company must have enough data to do a proper market basket analysis. A data scientist would be able to judge whether the available data is enough. Further, the company must invest in appropriate software packages to mine and analyse the data.
Finally, teamwork and collaboration between management, data scientists, ML engineers and other skilled personnel are key to the success of market basket analysis endeavours, irrespective of the industry.
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