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新技術(shù)的發(fā)展,直擊家裝業(yè)痛點(diǎn) !
2019-07-24

新零售時(shí)代所帶來的海量的新技術(shù)的應(yīng)用讓家裝行業(yè)非可控的因素越來越少,標(biāo)準(zhǔn)化程度進(jìn)一步提升。家裝行業(yè)的個(gè)性化和標(biāo)準(zhǔn)化似乎存在著一種不可調(diào)和的矛盾,照顧到哪一個(gè),另外一個(gè)都會(huì)被忽視。

The new retail era brings a large number of new technologies to the application of home decoration industry uncontrollable factors are becoming less and less, and the degree of standardization is further improved. There seems to be an irreconcilable contradiction between individualization and standardization in the home decoration industry. Whichever one is taken care of, the other one will be ignored.

新零售時(shí)代的來臨則為調(diào)和家裝行業(yè)的個(gè)性化和標(biāo)準(zhǔn)化的問題提供了一種全新的思考方式,這主要是通過新技術(shù)的應(yīng)用來實(shí)現(xiàn)的。無論是大數(shù)據(jù)技術(shù)、云計(jì)算技術(shù)還是人工智能技術(shù),其實(shí)能夠在提升效率的基礎(chǔ)上,實(shí)現(xiàn)個(gè)性化和標(biāo)準(zhǔn)化的完美統(tǒng)一。

The advent of the new retail era provides a new way of thinking to reconcile the personalization and standardization of the home decoration industry, which is mainly achieved through the application of new technologies. Whether it is big data technology, cloud computing technology or artificial intelligence technology, in fact, it can achieve the perfect unification of personalization and standardization on the basis of improving efficiency.

以大數(shù)據(jù)為例,傳統(tǒng)家裝時(shí)代和互聯(lián)網(wǎng)家裝時(shí)代每一個(gè)用戶的設(shè)計(jì)方案都是不一樣的,每一個(gè)設(shè)計(jì)方案之間也不存在必然聯(lián)系,設(shè)計(jì)方案的個(gè)性化不僅讓家裝效率得到了降低,而且讓家裝產(chǎn)品浪費(fèi)非常嚴(yán)重,建材、工人等環(huán)節(jié)由于不同的設(shè)計(jì)方案無法復(fù)用,最終讓家裝行業(yè)的效率無法提升。

Taking big data as an example, the design schemes of every user in the traditional home decoration era and the Internet home decoration era are different, and there is no inevitable connection between each design scheme. The individualization of design scheme not only reduces the efficiency of home decoration, but also makes the waste of home decoration products very serious, such as building materials, workers and so on. Because different design schemes can not be reused, ultimately the efficiency of the home decoration industry can not be improved.

大數(shù)據(jù)時(shí)代的來臨則讓這個(gè)問題得到了緩解,并且讓家裝行業(yè)的效能真正得到了提升。雖然每一個(gè)用戶的裝修方案是不同的,但是在海量的大數(shù)據(jù)庫里,我們總是能夠找到用戶家裝需求當(dāng)中共性的東西,通過將共性的東西進(jìn)行標(biāo)準(zhǔn)化的處理,將個(gè)性化的東西進(jìn)行區(qū)別化對(duì)待,不僅能夠?yàn)榧已b上游廠家提供了數(shù)據(jù)借鑒,更是讓用戶的個(gè)性化需求得到了滿足。困擾傳統(tǒng)家裝和互聯(lián)網(wǎng)家裝的痛點(diǎn)和難題,最終通過大數(shù)據(jù)的手段得到了一定程度上的提升和優(yōu)化,家裝效率再度提升有了新的可能性。

The advent of the era of big data has alleviated this problem, and has really improved the efficiency of the home decoration industry. Although each user's decoration plan is different, but in the massive large database, we can always find the common things in the user's home decoration demand. By standardizing the common things and differentiating the personalized things, we can not only provide data for the upstream manufacturers of home decoration. Reference, but also let the user's personalized needs have been met. The painful points and difficult problems that perplex traditional home furnishings and Internet home furnishings have been improved and optimized to a certain extent by means of big data, and the efficiency of home furnishings has new possibilities.

除了大數(shù)據(jù)之外,人工智能、VR技術(shù)等新技術(shù)元素的加入都為我們打開了兼顧家裝行業(yè)個(gè)性化與標(biāo)準(zhǔn)化的鑰匙。通過新技術(shù)的持續(xù)應(yīng)用,原本看似不可調(diào)和的個(gè)性化與標(biāo)準(zhǔn)化之間的矛盾有了解決的可能性。對(duì)于由于個(gè)性化和標(biāo)準(zhǔn)化之間的矛盾不可調(diào)和導(dǎo)致效率低下的家裝行業(yè)來講,無疑能夠看到提升效率的解決方案。

In addition to big data, the addition of new technology elements such as artificial intelligence and VR technology has opened the key to both personalization and standardization of home furnishing industry. Through the continuous application of new technology, the contradiction between individualization and standardization, which seems to be irreconcilable, has the possibility to be solved. For the inefficient home furnishing industry due to the irreconcilable contradiction between personalization and standardization, there is no doubt that we can see the solution to improve efficiency.



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