Decrypt the cosmetics industry Big Data Age "beautiful Truth"

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Big data is a good thing, big data is bad. Cosmetics are good things and cosmetics are bad. Depending on who is using and how to use it. If the big data turned people into deep ice, it was bad.

But if the big data turned the cosmetics industry into deep ice, it was a sin. Today, we are going to use a case of cosmetic industry to treat large data diseases slightly for many industries.

Big Data Circles

The whole world is talking about big data, anything that has something to do with data, people give it the name of big data, this reminds me of "gong" story. Many people may have been fascinated by big data, but when big data really came to you and came to your industry, you were terrified and helpless. This is gong.

Literally we all know that big data is big because it's big, so it's hard to control because it's big. More importantly, there are not too many cases to follow, so once there is a case, may become a treasure, some people may be tucked away, for fear of being stolen.

Specific to a certain industry, living cases less, even if there is no summary, everyone seems to be caught up in the concept of the concept of the circle, like the internet thinking, we have a swarm of thinking, very few people talk about what enterprises operating the Internet thinking of successful cases.

specifically to the cosmetics industry, as far as I know, cosmetics industry is a relatively more impetuous industry, many enterprises are more inclined to do brand and concept hype, rather than substantially improve product quality and service to enhance the user experience. So there are many advertising companies in the cosmetics industry, the conference investment is rampant, few enterprises can calm down and think seriously. Since there is no need to think, there is no need for data to support thinking.

More in vain talk about collecting user data, conducting detailed analysis, and then improving products and services to win the trust of users.

Give the big data the next my own definition

Large data has actually been deified, in fact it is not so mysterious and tall, it is a tool, and often can be combined to achieve the effect of technology. Today we're going to make this monster a prototype.

What is big data? (The following content from Baidu Encyclopedia, has not yet to pay the reprint costs.) )

Large data, or huge amounts of data, refers to the amount of information involved is too large to pass the current mainstream software tools, in a reasonable time to achieve capture, management, processing, and collation to help the business decision-making more positive purpose information.

That should be the right thing to say. But after looking at it, do you know what the big data is? or do you know what to do?

Today I'm going to give the big data my own definition, and I'm not afraid to say I'm wrong.

The author thinks, large data or large data application is, from the huge database to find the enterprise needs, can support enterprise development, help enterprises to find the enterprise strategy, sales strategy, team formation strategy and other wars, strategies, including user characteristics, user needs, use habits and other data process. It contains processes such as collecting data, analyzing data, and using data.

Cosmetics enterprises (not industry, but specific to the enterprise) for large data can do the work is, in the brand promotion, sales and other processes, the bait thrown out, and then the data fishing back.

The specific approach may be:

1, in the street to do a questionnaire survey, every person on the accosted, to the end of the send paper towels, experience products and so on.

2, do ground activities, fill in the relevant information, sweep the two-dimensional code, send gifts.

3, on the site to do 1, 2 of the work.

The content of the questionnaire generally includes the skin properties (oily dry sex), the current skin problems and other options.

It's weak! If this is called Big data, then we can do it in the 890 's, why wait until now. We have been doing this until the next generation of computer technology revolution.

Case: Uncover the "beautiful truth" of grapefruit shed big data

The big data looks beautiful, and it's more beautiful. But the more beautiful things experience the more pain. Because this is a difficult job, is a systematic, long-term work, need an implementation mechanism to support the operation, the general enterprise is really difficult to effectively implement.

Fortunately, in more need of large data in the cosmetics field, there are some enterprises to do some such attempts, with technical means as the core, opened the cosmetics industry large data "beautiful truth" for its sales strategy, enterprise strategy formulation and adjustment, played a certain guiding role.

Cosmetics Internet brand Pomelo has developed a "beautiful Truth" app, the software, in the grapefruit homes may be the original intention, so at first they used the combination of mobile social strategies to attract fans to participate. Pomelo Shed in the publicity, also has been preaching its interest, and the mobile social strategy to promote the role.

But in the author's opinion, this is a good data collection tool. This set of beautiful truth of the software, has now been connected to the micro-letter port, the user focus on the Grapefruit shed public account, click on the "Beautiful Truth" service, according to the prompts to upload a photo of their own, the system can automatically analyze the user's skin characteristics, skin properties, skin age. In addition, Pomelo also added some entertainment features, including charm Index, male and female index and star face, the intention is to increase their interest, and then let fans willing to forward and share.

But in fact, they got an unexpected added value, which is user data. Plus, they cooperated with a number of marketing promotion activities, so that a large number of users involved in the software experience, so that the user data has been a more substantial upgrade. According to statistics, the software is online within one months, as the micro-believers in pomelo grew by two hundred thousand or three hundred thousand, the grapefruit shed had more than more than 400,000 photos and more than 400,000 women's skin data, and the data was growing and updating, as the software was always in close proximity to their mobile social strategy, And Pomelo's mobile social strategy has been on the move, and fans have been keeping growing. In time, I believe that grapefruit homes will be able to get a close to the truth of the amount of data.

As we all know, the core of large data is the prediction, and the data are analyzed and the decision is guided by the forecast result.

After getting these data, how does the grapefruit shed do the processing, because there is not too much public data, the author is unknown. But the author recently landed Grapefruit House official website was surprised to find that their official website made a big change, the previous official website columns are based on product classification, but now they have to do a lot of topics according to user needs, covering sensitive care, maternity care, summer care, member interaction and other plates, There appears to be a trace of sales strategy adjustments after analyzing user data.

But no matter how, we from this case, still got some enterprises especially cosmetic enterprises how to enlarge data enlightenment.

The experience of pomelo is mainly embodied in the process of data collection and the implementation mechanism.

First, they use the power of technology to collect data (and possibly ensure that data analysis is carried out), which is the basic guarantee. Large data is the product of technology, and it cannot be implemented without technology.

Secondly, they use the form of interest, the use of people's pursuit of beauty and the psychological recognition, stimulated the participation of users, the initiative to send data to the data platform.

Thirdly, they set up the regular effect mechanism of data collection, combined with the mobile social strategy effectively, realized the automatic updating of data platform data, and let the data come to the platform continuously.

Above three points, indispensable.