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阿里起诉淘宝假货店主,携手数家公司利用大数据打假

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 openfea
发布于 2017/02/15 19:35
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电子商务可以称之为过去十年间人们生活中最大的改变。现在我们可以在下午5点下单,第二天早上9点就能收到货,这在之前是很难想象的,因为之前人们通常都要花好几周的时间来找自己想买的东西。

电子商务的兴起也带动了新经济的发展,成千上万的商家都通过电子商务平台直接将商品出售给消费者。甚至还有很多人辞职后专门做电商,月薪高达六位数。

但是,电商的发展也导致了一些不好现象的发生,特别是假冒伪劣商品的肆虐。英国有个叫阿密特·沙马的人,通过在eBay卖假名牌服装,四年获利超过100万英镑,由此被判处21个月的监禁。

电商卖假货的问题并不只在美国和欧洲国家出现,在中国,阿里巴巴日前也起诉了两名假货贩卖商,他们通过淘宝销售假冒的施华洛世奇手表,阿里巴巴要求他们赔偿人民币140万元

质量问题也是电商行业的一大弊病,以次充好的情况非常严重。很多商家会买水军,增加商品的好评,并提高商家等级。这样一来,消费者购物时就会以为这个店里的商品或服务已经得到了很多消费者的认可。而事实上并非如此,商家只是花了点钱找了水军而已。

这给很多电子商务网站造成了很多的困扰,因为平台本身无法干预消费者对商家的评分。

如果你想买一块手表,在实体店里你可以先试戴,检查各部分是否完好无损,看看是否是正品,但是在电商平台就不可以了。如果人们在电商购物时遭遇了以次充好的情况,那么他们很可能就会回归传统的实体店购物方式。所以这个问题不得到解决,电子商务将流失大量顾客。

如果你花了50块钱买了坑爹货,正常人都不会愿意再花500块钱在电商平台买东西了。所以现在电商平台上很多价格较高的商品都不好卖,但是商家还要囤着货,这样一来很多商家都浪费了大量的储货空间,甚至还要在这些商品的安保上花费更多。

很多比较实诚的卖家都退出了电商平台,因为很多店家通过买水军的方式提高店铺等级,以这种方式恶性竞争。

在这些问题更加猖獗之前,我们必须要采取行动了。阿里巴巴已经携手数家公司联手打击假冒伪劣产品。阿里巴巴集团与路易威登、三星和玛氏公司达成合作协议,利用大数据找出淘宝平台上的假冒伪劣商品。

阿里巴巴集团首席平台官杰西·郑认为,大数据和分析是当今打击假货的最有力武器,各方必须联合起来共同行动,她说“我们的大数据分析能力非常出色,所以我们有信心此次合作能够有效的改变假货猖獗的情况。”

阿里巴巴与这些公司合作,阻止假货继续伤害它们的品牌。阿里巴巴本身打击假货的能力也是非常值得肯定的,在2016年4月至7月间,阿里巴巴没收了价值2.072亿的假冒伪劣商品,关闭了417家非法交易假货的店铺,帮助警方抓获了332名造假犯罪嫌疑人。

通过机器学习,阿里巴巴的系统每天都会检查1000多万产品清单,2015年8月至2016年8月间,累计剔除了38000万产品,取消了180,000个第三方卖家的销售资格。

此次阿里巴巴与各公司的合作将更加全面、有效地打击假货。阿里巴巴对假货问题的关注度之高可能会令外界震惊,在他们2016年年度报告中,“假货”一词出现了30次之多。

阿里巴巴并不是唯一遭遇假货问题的电商平台,亚马逊上的假货问题同样非常突出。

举例来说,此前苹果公司起诉了亚马逊上的一个店铺,该店铺出售的苹果产品90%都是假货,一旦这些假手机运行出现问题,亚马逊和苹果公司的声誉都会受到伤害。一些造假者甚至买通了亚马逊后勤部,让他们的假货也能进入亚马逊仓库,让消费者以为他们买到的是正品。

亚马逊对此非常头疼,他们在简化交易的同时,也让很多假冒伪劣商品趁机占领了购物网站。为了阻止这些假货贩卖商,亚马逊同样采用了大数据,提高第三方卖家销售大品牌产品的门槛。关于这一举措,亚马逊并没有公布太多细节,他们宣称已经在这个行动中投入了数千万美元。他们同时表示这一过程还需要各大品牌的参与合作。

阿里巴巴和亚马逊开始整治假货并不在人们意料之外,再不行动恐怕就要让他们陷入大麻烦了,毕竟法院和媒体都已经关注它们很久了。

苹果公司起诉了亚马逊上的Mobile Star店铺,该店铺通过亚马逊销售的苹果产品90%都是假货。尽管此案的被告并不是亚马逊,但是这对亚马逊来说也不是什么光彩的事情。还有一些其他的小品牌也曾公开指责亚马逊的假货问题,如TRX(美国健身器材公司)和勃肯(德国鞋业品牌),勃肯已经宣布从2017年1月1日起全面撤出亚马逊。

亚马逊确实是挺倒霉的,庞大的规模是他们的优势,但现在却让他们陷入困境。

2017年1月份亚马逊库存商品超过39800万件,较2016年12月增加了8%。在如此庞大的商品数量面前,光靠人工是不可能筛选出假货的。很多卖家都抱怨称亚马逊之前的系统只能在接到假货举报后才能处理销售假货的商家,但是这些受到处理的不法分子下次换个店铺名还能接着卖假货。所以仅仅靠举报系统和客服团队是不可能处理这么多假货的。

随着技术的日益成熟,大数据、机器学习和人工智能进一步发展,这些电商平台将可以更快速且高效地打击假货。亚马逊现在迫切需要认识到这一点,也许还要从他们的中国竞争对手——阿里巴巴身上多多学习。

 

英文原文

 

Can Big Data Stop The Shadiest Elements Of E-Commerce?

All is not well with many e-commerce companies, but could big data help?

E-commerce has been perhaps the single biggest change in people’s habits over the past decade. Now we can realize that we need something totally obscure at 5pm and have it in our hands by 9am the next morning, where previously we would have needed to search for weeks just to find it. It has also created a new economy, where there are now thousands of people who can sell their own products directly to consumers through e-commerce platforms. There have even been stories of people making six figure salaries by selling through these kinds of platforms instead of holding down regular jobs.

However, the opportunities that it has given honest people has also led to a considerable rise in the number of counterfeit and low quality products available. There have been stories like that of Amit Sharma in the UK, who earned over £1 million in 4 years selling counterfeit clothing on eBay and was jailed for 21 months after being caught. It is not just a problem for US and European countries either, with Alibaba suing Liu Huajun and Wang Shenyi for 1.4 million yuan for ‘violation of contract and goodwill’ after they were found to have been using Taobao to sell fake Swarovski watches.

Similarly there have been issues with low quality goods being sold as considerably higher quality than they are. This is achievable because many online sellers have realized that they can utilize companies who offer to increase the user ratings for products and seller accounts on e-commerce sites. This means that people who buy these products normally do so under the impression that hundreds of customers have been happy with the quality of the product and service offered by the seller. In reality they may have simply paid a company to increase their user ratings.

This represents a serious issue for e-commerce sites, as it abuses the one thing that they can never offer - a preview.

In a brick and mortar store, if you want to buy a watch, you can try it on, check that everything is working properly and check the authenticity. Nobody will ever be able to do this with the majority of e-commerce companies, so if people are a victim of either of these problems they are far more likely to be driven back to traditional forms of shopping experience. It also has an impact on the amount people are likely to spend online. After all if you get burnt buying a $50 watch, you are never going to risk it with a $500 one. This creates a situation where e-commerce sites will struggle when it comes to selling big ticket items, but will still need to stock them - so excess stock will be held by the company, wasting warehouse space and likely requiring additional security.

This then causes issues for genuine sellers who refuse to use these kinds of services, because traditionally the companies with the most highly rated reviews are the ones who appear at the top of searches.

However, there are moves being made to prevent these issues from becoming unmanageable, with Alibaba teaming up with several companies to try and combat counterfeiters. The company is going to be working with a selection of companies including Louis Vuitton, Samsung and Mars to utilize big data and identify fake products on their platforms. Alibaba have great faith in the move with their chief platform officer, Jessie Zheng claiming ‘The most powerful weapon against counterfeiting today is data and analytics, and the only way we can win this war is to unite…With our robust data capabilities, we are confident the alliance will accelerate the digital transformation in our global fight against counterfeits.’

It is likely that the collaboration with companies with a vested interest in stopping these counterfeiters and damaging their brands. It is likely to bring even more robustness to Alibaba’s already reasonably robust approach, having already seized $207.2 million of counterfeit goods, shut down 417 production rackets and helped to arrest 332 counterfeiting suspects between April and July 2016.

Using machine learning, Alibaba’s system scans 10 million product listings every day and had removed 380 million product listings and 180,000 third party sellers in the 12 months leading up to August 2016. It is hoped that by bringing together every stakeholder impacted by fake products this process could become even more thorough and effective. It is little surprise that this has been such a focus for the company given that some form of the word ‘counterfeit’ appears 30 times in Alibaba’s 2016 annual report.

Alibaba aren’t the only company suffering from this phenomenon though, with Amazon being a highly visible target for counterfeiters. For instance, according to a lawsuit filed by Apple, 90% of Apple products (mainly chargers and peripherals) sold on Amazon are counterfeit, meaning that Amazon’s reputation and Apple’s reputation is damaged when these fake goods malfunction or break. The fraudsters are even taking advantage of the logistics offered by Amazon, allowing them to send their fake products directly to an Amazon warehouse, giving them an air of authenticity. It has created a major headache for Amazon, who’s attempts to make selling through their marketplace as simple as possible has led to a huge number of fraudulent products flooding the site. To prevent this, they are also looking to utilize big data with their partners, as well as making it more difficult for third party sellers to sell big brand products. The public details of this are limited, although Amazon have said they spend ‘tens of millions of dollars’ on the endeavour. They also say that they need to work with brands in order to make the process work.

It is little surprise that both Alibaba and Amazon are suddenly taking this move seriously, because it is beginning to hit them where it hurts - in the courtroom and in the media.

For instance, Apple filed a lawsuit against Mobile Star who sold Apple products through Amazon after it found that 90% of the Apple merchandise sold by the company was counterfeit. Although this was not a lawsuit against Amazon, having the world’s most valuable company suing somebody for something they did through your marketplace is not good for business. There are also multiple examples of smaller companies like TRX and Birkenstock openly criticizing Amazon for their approach, with Birkenstock actively withdrawing all products from Amazon as of January 1 2017.

In many ways you have to feel sorry for Amazon, as it seems that their biggest strength has also turned into their biggest weakness - their size.

Amazon stocks over 398 million products as of January 2017, with an 8% increase from December 2016 alone. Taking a ‘human first’ approach would be impossible in the face of these kinds of numbers. Many of the sellers who have complained about counterfeiters have needed to rely on a reporting system where they can report to Amazon who then take down the counterfeiter’s page, only for the same seller to appear under a different name days later. This could happen to any one of the nearly 400m products, so trying to manage this with a report system and complaints team would be impossible.

As technologies progress and the use of data, machine learning and AI improves even further, the chances of stopping this more quickly and effectively is going to increase too. It is something that Amazon is desperate need of and perhaps they should be taking the cues from their biggest Chinese rival.

 

转自:灯塔大数据;微信:DTbigdata

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