How to Develop Insurance Precision Marketing

Big data can provide some business transaction characteristics and capital demand characteristics, help business departments analyze and screen the capital demand of enterprises, provide cash management products, and help enterprises solve liquidity problems. Big data can help credit card centers track hot information, provide accurate marketing products for specific groups of people, and increase new card users, such as popular movies, entertainment activities, catering group purchases, etc. Banks launch customized wealth management products and insurance products for specific groups of people.

2. Social marketing

People's social behavior produces huge data. With the help of social platforms and big data analysis, the financial industry can carry out low-cost social marketing, and promote products and channels with the help of an open Internet platform and a large number of customer demand data. Through the massive data returned by the Internet social platform, we can evaluate the phased results of the marketing plan, adjust the marketing plan in real time, and use word-of-mouth pyramid schemes and viral communication to help the financial industry quickly promote products, brands and channels.

3. Data platform

How to achieve accurate marketing and thus increase customer stickiness is undoubtedly relying on powerful data platform, relying on big data platform, similar to cloud data, as a fulcrum to guide customer demand and continuously strengthen the practical application of internet plus, so as to quickly obtain customers' purchasing desires and needs from big data.

4. Credit risk assessment

Banks can use big data to increase the latitude of credit risk input, improve the level of credit risk management, and dynamically manage the forms and use risks of enterprises and individual customers. Establishing a credit risk assessment model and method based on big data will improve the financial support of banks for small and medium-sized enterprises and individuals. The establishment of personal credit scoring standards will help banks to take the lead in the coming credit consumption era. The dynamic credit risk management mechanism based on big data will help banks predict the default time of high-risk credit in advance, intervene in time, reduce the default probability and prevent credit fraud.

5. Fraud risk management

Credit card companies can use big data to predict and discover malicious fraud events in time, even if measures are taken to reduce the risk of credit fraud. Banks can establish an anti-fraud monitoring system based on big data to dynamically manage fraud events in online banking, POS machines, ATMs and other channels. Big data provides multi-latitude monitoring indicators and linkage methods, which can make up for and improve the current anti-fraud monitoring methods. Especially in identifying customer behavior trends, big data has great advantages.

6. Enhance the customer experience

Based on big data analysis, banks can provide customized services and greetings to customers who enter outlets, provide customized services to customers on holidays, predict the future capital needs of corporate customers, make appointments in advance, and enhance customer experience. According to the big data analysis report, private banks can help customers invest in financial market products, earn excess profits, form competitive advantages and improve customer experience. Insurance business can provide effective services to customers in advance according to big data forecast, improve customer experience and increase business opportunities. The wealth management business can use large number analysis to quickly launch industry reports and market trend reports to help investors keep abreast of hot spots and improve customer satisfaction.

7. Demand analysis and product innovation

Big data provides overall data from which banks can filter by using overall sample data. Customers can be classified according to their occupation, age, income, residence, hobbies, assets, credit, etc., and customer needs can be determined according to other data input latitudes, and products can be customized. Banks can also predict the development characteristics of the industry according to the transaction data of enterprises and provide financial products and services for corporate customers.

8. Improve operational efficiency

Big data can show the actual income and cost of different product lines and help banks manage products. At the same time, big data provides a comprehensive report for management, revealing the efficiency of internal operation management, which is powerful for improving internal efficiency. Big data can help marketing departments effectively monitor marketing plans and promotion, improve marketing accuracy and reduce marketing expenses. Big data can display a risk view to control credit risk and speed up credit approval. Big data can help the insurance industry to provide insurance solutions to customers quickly, improve efficiency and reduce costs. Wealth management products can also use big data to dynamically provide industry reports to help investors quickly.

9, decision support

Big data can help financial enterprises to provide data support for upcoming decisions, and at the same time, it can also analyze and summarize laws based on big data and further deduce new decisions. The decision tree model based on big data and artificial intelligence technology will effectively help the financial industry to analyze credit risk and provide strong support for business decision-making. Before the new products or services of the financial industry are put on the market, they can be tested in local areas. Big data technology can accurately analyze the collected data and provide decision support for the marketing of new products through statistical analysis reports.

Further reading: How to buy insurance, which is good, and teach you how to avoid these "pits" of insurance.