For e-commerce based companies, it is worth important to know about their customers. Different solutions are used to become aware of their customers expected response. Normally companies use old data of their customers, analyze it and finally offer some products based on this analysis. E-Commerce is and example just to explain the idea and use case, but we can extend and expand this based on different trades of life.
But in my opinion it is not effective to just know about the past history of a customer to predict the expected behavior of a customer. Although it can be helpful, but still is has great room to do more accurate predictions about the customer behavior.
Based of this problem, I tried to think of an idea to make use of social media data to identify Personality types ( based on Mayers Briggs personality types). We will make use of this data using IBM Watson to determine the personality types. Once we determine the personality types, then we can extend our personality analysis based on different trades.
Following fields can be benefited with this idea.
- We can predict the behavior of a customer more precisely based on social media data related to him. Because it is not necessary for any customer who buys a product regularly would buy the same if he is in a different mud (based on social activities).
- Air lines can offer promotional tickets to customers, if they can predict that he might be planning for a trip in coming days.
- Recruiting agencies can determine the interpersonal skills at first and filter out the key persons out of thousands.
- and many more applications...
- All the industries that want users to be better predicted for their system.
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