Time Series is a statistical technique that deals with time series data, or trend analysis. Time series data implies the data which is in a series of particular time periods or intervals. Whereas, sequence data mining signifies finding statistically relevant patterns between data examples where the values are delivered in a sequence.
Study of time series in data mining helps in better understand cyclical and seasonal trends. This gives a boost in analyzing the patterns that happen outside the usual turn of events. Data mining can go a long way in trend discovery, pattern mining and prediction. Retail companies have recently been using this method to keep a track of their business.
Data Mining has helped the e-commerce segment in various ways: starting from inventory intelligence, business operation to sales pattern. It has been of massive help for survival during this covid pandemic.
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Data Mining in Product Search
A customer’s buying patterns or liking can be tracked when a potential customer searches a product. Mining will help us understand user query intent. Product ranking is also possible by checking user’s click-through rates or product’s sell-through rates. The present pandemic situation has brought a drastic change in the whole product-searching pattern. Due to segregation of places into green, orange, red and containment zones as per the rate of vulnerability, the search pattern has altered owing to product availability. Product delivery is restricted in the containment zones; only essential goods being available and ready to dispatch in the comparatively safer zones, these factors have altered the usual turn of events.
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Data Mining in Product Recommendation
If product recommendation is correctly and efficiently, then it actually helps in enhancing customer experience in the platform. A happy customer can bring business. Thus, it is important to understand user behavior. It also facilitates popularity of a product. In order to discover similarity between different items, mining of data is required to understand product similarity. Tracing the similarity involves analysis of price range, user purchase patterns and category of the product. By using different data mining tools, we can tackle this problem. Compared with prior to covid situation, a few categories have witnessed more than 40% surge in their sales. As in electronics, auto parts & tyres, home decor, general merchandise to name a few.
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Understanding Business Intelligence
Categorizing & classifying each product properly enables better search experience, inventory tracking, distributing relevant products to their prospective customers. The lockdown has affected this retail online business in both ways. On one hand, many new customers have registered. On the other hand, the business has witnessed a downfall over time due to restriction of delivery only to essential items. However, the drive to reopen the e-commerce sector will prove to be a major boost to companies who were selling only essentials during this period.
The current situation has initiated a sea change in the overall business scenario. Traditional street-side business is witnessing a downward trend and people are taking their business online. Due to the sudden lockdown, panic buying of household essentials has increased. From supermarkets, people are depending more to online stores.
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