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  • Getting Customer Feedback in Ecommerce Business with Data Science

Getting Customer Feedback in Ecommerce Business with Data Science

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An ecommerce company will only be sustainable in the long term if it is able to ensure that the customer finds value in returning to the site. For this, it is of the utmost importance that you take cognizance of the customer feedback you receive and derive actionable insights from it.

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One of the problems with customer feedback analysis is that often the feedback is only present as open text. In this scenario, you can use text analytics to mine useful information from it. What is generally done in these cases is to build a "bag of words" which is a collection of relevant words with a negative or positive weight attached to them. So for each customer feedback, string matching is used to get the positive or negative score for each relevant word. The sum of such scores for a feedback gives the overall score for a feedback.

 

Additional Reading

Read more about sentiment analysis (a technique in text analytics) in the links below:

So, you started with the business models of the ecommerce firms and saw the application of data analytics in the various stages of the ecommerce value chain — inventory management, marketing, improving user experience, fraud detection, shipment of delivery and customer feedback analysis. You can read more about the application of analytics in ecommerce domain at this link from Analytics Vidhya.