• Financial sector. Analysis of collected data on customer transactions allows banks to develop the quality of lending.
Retail. Retail networks use data on online and offline purchases
product preferences to form personalized offers and improve the consumer experience of their target audiences.
• Telecommunications. Telecom operators analyze load data to optimize network infrastructure in order to provide their subscribers with the best quality of service at any time. Moreover, big data analysis allows identifying characteristic subscriber patterns before changing providers and developing customer retention measures.
• Healthcare. Analysis list to data of clinical big data improves the accuracy of diagnosis and disease prognosis. They are also used to monitor population health and carry out preventive treatments, which, of course, increases people’s satisfaction with the quality of service.
• Automotive industry. Companies in this industry use big data to improve car safety systems. In addition, the data also dealing with agile challenges in a remote landscape helps in testing new models and determining customer preferences.
• Tourism and hospitality. Companies in this industry use big data to implement flexible pricing and demand management, and analyze information about the preferences of regular customers to create personalized offers.
The use of big data is ond over time we can expect that its analysis will play an even more importaness strategies of companies.
How does Big Data technology work?
For big data application at the enterprise it is necessary to implement a whole set of tools and processes. In general, their structure looks like this:
1) Data collection. The primary and most difficult stage. Its main problem is to determine the sources necessary for the company’s tasks. Data can come:
• From websites and applications: content views, clicks, page visit time, etc.
• From social networks: posts, interests, likes, comments and other user interactions.
• From payment services and systems: purchases and transactions.
• From smart devices: search queries, sensor readings, etc.
• Partner data: transactions, orders of goods and services, anonymized customer profiles, etc.
2) Data storage. Large volumes of information require a special IT infrastructure of servers, which is either located in a data center in Moscow or provided by cloud storage.
3) Data processing. Special software cleans, transforms and aggregates the collected information for subsequent analysis.
4) Data analysis.
5) Data visualization. S They summarize the findings in the form of graphs, dashboards and structured interactive reports.
6) Decision making. At the final stage, big data marketing software allows you to make informed decisions, which may include:
>>>>>>lass=”yoast-text-mark” />>• optimization of marketing promotion strategies;
• improvement of the market offer;
• expansion of sales markets;
• development of new products.
How is big data processed?
Processing big data for marketing purposes is far from a simple process, where one analyst cannot cope. In egypt data many ways, the procedure depends on what conclusions the company seeks to obtain for making its decisions.
