The analysis of customer information offers great advantages in strategy development, as customer interactions, consumer response and behavioral patterns, among others, can be monitored and predicted. This information is useful for increasing customer acquisition, profitability and long-term customer loyalty.
How can Big Data be used to improve marketing and sales strategies?
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Feeling Analysis
By collecting information from websites, mobile applications, marketing campaigns and affiliate sources, a comprehensive segmentation of the target audience is obtained to observe how, when and where a product or service is perceived and how customers interact with them through the different channels of the organization.
Transactional Data Analysis
Product/service purchases, returns, reservations, etc. are analyzed, providing insight into customer spending habits, payment method preference.
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Service/Product Usage Data Analysis
Understanding product/service usage patterns helps to create a better customer experience and improve the product/service portfolio.
Descriptive Customer Analysis
Helps to discover what has happened or what is currently happening in the business by analyzing historical data and real-time customer-related data.
Also read: “Geospatial data for zone selection for new points of sale.”
Web Behavior Analysis
Knowing how customers move around the website, the places where they click on purchase/return, etc. Helps identify key points in the customer journey (where customers get stuck/abandon/convert), thereby enabling you to evaluate the performance of specific pages and adapt them accordingly.
Analysis of Customer-Created Texts
The analysis of comments on social media posts about a product/service helps to identify preferences, as they reveal complaints and problems to be solved and to be recognized.
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