Zara Also Needs To Respond, Correct And Execute Quickly With Big Data.

< p > < strong > turn consumer voice into numbers < /strong > /p >
< p > enter the store, and cameras are installed in every corner of the counters and shops. The store manager carries PDA with him. When the guest reflected to the clerk: "this collar is very beautiful", "I don't like the zipper of pocket", these detailed details, the clerk reported to the branch manager, the manager passed the Zara internal global information network at least two times a day to deliver the information to the headquarters designer. After the headquarters made the decision, it immediately sent to the production line and changed the product style. < /p >
< p style= "text-align: center" > < img border= "0" align= "center" alt= "" src= "" /uploadimages/201305/28/20130528112301.JPG "/" < > > "
After closing the store, the sales staff settle accounts, check the daily up and down shelves of the goods, and make statistics on the purchase and return rates of the P customers. Combined with the counter cash information, the transaction system made the analysis report of the day transaction, and analyzed the hot sale ranking of the product. Then, the data went directly to the Zara storage system. < /p >
< p > collecting mass customers' opinions to make production and sales decisions. This way greatly reduces the inventory rate. At the same time, according to these telephone and computer data, Zara analyzed similar "regional popularity", and made the closest market segmentation in color and version production. < /p >
< p > < strong > online shop is the store's pre-test index < /strong > < /p >.
In the autumn of 2010, Zara set up online stores in six European countries at one breath, adding a large amount of data to p networks. The following year, in the United States and Japan launched the network platform, in addition to increasing revenue, online stores strengthened two-way search engine, data analysis function. It not only restores opinions to the production end, but also allows decision-makers to find out the target market accurately, and provide consumers with more accurate fashion messages, so that both sides can enjoy the benefits brought by big data. Analysts estimate that online stores have increased at least 10% of Zara revenue. < /p >
Besides P, online store is also the touchstone of marketing before launch. Zara usually conducts consumer opinion surveys on the Internet, and then extracts customers' opinions from the network feedback to improve the actual shipment products. < /p >
< p > Zara regards the massive data on the network as the pre-test index of the physical storefront. Because people who search for fashion information on the Internet will enjoy more interest in a target= "_blank" href= "//www.sjfzxm.com/" > dress > /a, and the ability to generate information, which is more avant-garde than the general public. Moreover, consumers who know the Zara information on the Internet will have a high ratio of consumption to physical stores. Zara chooses to cater for the products or trends that users like. Indeed, sales performance in the physical stores is still bright. < /p >
< p > these valuable customer data, besides being applied to the production end, are used by all the departments of the Inditex group of Zara. They include customer service center, marketing department, design team, production line and access channel. According to these huge amounts of data, the KPI of each department is formed, and the vertical integration axis of Zara is completed. < /p >
The massive data integration carried out by < p > Zara achieved unprecedented success and was later applied to the eight brands under the Zara group. In the foreseeable future, in addition to the design capability on the table, the information / data war on the table will be a more important invisible battlefield. < /p >
< p > < strong > with big data, we must respond quickly, modify and execute < /strong > < /p >.
< p > H&M has always wanted to keep pace with Zara, and actively use big data to improve product flow, but the effect is not obvious. The difference between them is getting bigger and bigger. Why? < /p >
< p > the main reason is that the most important function of big data is to shorten the production time, so that the production end can be corrected at the first time according to the customer's opinion. However, the internal management process of H&M can not support the huge data supply of big data. In the supply chain of H&M, it takes about three months from typing to shipping. It can not be compared with Zara two weeks. < /p >
< p > because H&M is not like Zara, the latter half of the design and production is maintained in Spain, while the H&M producing area is scattered to Asia and central and South America. The time of transnational communication lengthened the time cost of production. In this way, big data can not be improved immediately even if the customers' opinions are reflected on the same day. The result of the separation of information and production has limited the effectiveness of H&M's internal big data system. < /p >
< p > the key to the success of big data operation is that the information system must be closely integrated with the decision-making process, respond quickly to the needs of consumers, correct them, and execute decisions immediately. < /p >