Impacts of Big Data to the Retail Industry

Student Name: Grace Zhang 張嚴云
Student ID: D0740679

Blog#3:  Impacts of Big Data to the Retail Industry

    This article is discussing about the the connection between big data and retail industry. It is important for retailers to control the amount of their products. They need to know how much they should offer to their customers and what is the exact demand of their customers. To meet the best equilibrium, big data could help a lot to analyze the information.

    Here it mentions four critical business intelligence strategies. To predict client’s spending comes in the first strategy. This strategy use the most common method of big data which is to gather the customer activities and shopping histories. By doing so, the retailers can provide personalized recommendations to their customers. Moreover, they can learn what their customers prefer and get the opportunities to revise or improve their services.


    Nowadays, customers require a smoother shopping experience between online and physical store. Based on the combination of big data and retailing strategy, the retailers can satisfy their customers. One of the strategy is to analyze the customer journey. This strategy is kind of replace the traditional questionnaire steps. We can use the data from customer previous experience, current customer experience, and future experience all through big data analysis.

Comments

  1. Amy Le May 18, 2020 at 6:44 AM

    What an interesting and practical impact of Big Data on Retail Industry. For a retailer, big data means a vast understanding of the shopping habits of consumers and how you can expand your clientele. Based on clients’ purchase history, you can create custom recommendations to guarantee personalized shopping experiences. Also, the super-sized data can help predict trends and make strategic business decisions based on the analysis of customer behavior in the market. I truly believe the widely implementation of big data in the leading retailers like Amazon, Alibaba, Target, etc.

    Here are the application of this crucial business intelligence strategy which I will keep in mind!

    1. Predicting client spending
    Among the most common methods of gathering big data is via loyalty programs, credit card transactions, user logins, IP addresses, and more. As you collect more information, you can analyze the fluctuations and flow of spending and shopping historically and come up with personalized recommendations.

    2. Personalizing customer experience
    Information from data creates opportunities for retailers to better the experiences of customers. Through this resource, businesses can learn customer preferences and tastes and suggest any relevant products.

    3. Demand forecasts
    To add to business intelligence, retail businesses can use additional algorithms to analyze web browsing and social media trends. This makes it easy for them to predict any new innovation or taste that would take the market by storm.

    4. Analysis of customer journey
    The customer journey is not always a straight line, but a zigzag that begins from research to purchase. Business intelligence can help your retail store get a grip on the journey and offer better experiences. Furthermore, it helps entrepreneurs ascertain where clients seek product information and the most effective methods of reaching them and compelling them to buy.

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