How do foreign trade B2B companies play with data?

In the era of the barbaric growth of self-media and social networks, the data environment faced by B2B enterprises has undergone unprecedented changes.

Interactive topic: What kind of data do foreign trade B2B companies want most?

Big data allows every participant of the industrial ecology to fully participate in the production, sales and consumption of the entire industrial ecology. Enterprises are no longer a single product and service provider, but become a product and service platform.

How to use these different data to help B2B companies find potential business opportunities, discover new business highlights, and improve product competitiveness and customer satisfaction has become a top priority.

Listen to the voice of users

Now more and more mai companies hope that suppliers can provide unique products that can suit the local market and consumers. Therefore, listening to the market is increasingly important for B2B companies. The website of "CEConline" conducts export prospect research on foreign trade B2B enterprises every year. This year, "market development capability" has ranked second among many challenges faced by Chinese manufacturing. In the past, it only focused on product quality and delivery. Entrepreneurs of time are more and more urgent to grasp the changes in market demand.

Xiao Diwu, deputy editor-in-chief of "Tsinghua Management Review", believes that for 98% of enterprises, the word "big" in big data is not important, and analyzing customers' consumption behavior and characteristics is the key to the problem. .

However, how can SME manufacturers grasp the needs of different levels of consumer groups in more than 200 countries?

Social media can not only help B2B companies to understand and select mai companies, but also increasingly become the preferred channel for companies to communicate and interact with end users and understand changes in demand.

According to Peter Zapf, B2B/B2C marketing expert and CIO of Global Sources, "Suppliers should definitely look at user reviews of their own and competitors' products online. Keep close contact with end-consumer customers and understand their needs. , these people are very likely to comment on the products you manufacture on blogs, twitter, Facebook, expressing what they like or dislike about a certain product. Such comments can help suppliers understand the real needs of customers and provide information for future products. Design decisions provide a major reference.”

Xiaomi co-founder Huang Jiangji directly found the direction of product upgrades by watching users’ complaints. He said: "If the big data analysis shows that many users are particularly concerned about feature A, but feature B is the most scolded in Weibo, I will not hesitate to solve the feature requirements in the first time, and I believe in direct user feedback."

So, how do you listen to your users? Pei Kewei, the publisher of "CEConline", suggested that when selecting mai companies, look for retailers or e-commerce companies with big data systems and analysis capabilities for the target market, such as Walmart and Amazon.

In April 2011, after Walmart acquired Kosmix, which specializes in classified social networking sites, at a high price of US$300 million, it can not only collect and analyze massive data on the Internet, but also personalize the information. Provide purchasing advice to end consumers, from "mining" customer needs to being able to "create" consumer needs. Amazon, on the other hand, constantly designs some small experiments, pushes different versions of a new function or new product to different users, and uses various forms such as voting, selection, and prize participation to attract consumers to participate in interaction and obtain user feedback. Users' behavior habits, hobbies, shopping preferences, and potential needs are deeply excavated, and users' preferences are understood through data analysis to manage them in groups.

Change decision-making habits

Supply chain management expert Liu Baohong told reporters, "In company decision-making, we should always start with facts and data and end with judgment. But in fact, there are some manufacturers in China. The decision-making model of an enterprise is debatable. Often, the boss, without sufficient information and lack of necessary data support, shoots the arrow first, and then the subordinate draws the target at the place where the arrow falls. The lessons of decision-making mistakes are very important. Painful."

The basis of big data mining is the correlation between data, and most B2B enterprises in China fight each other independently. Otherwise, management decision-making will fall into the misunderstanding of finding the right answer for the wrong question, and it will be farther and farther away from the correct decision.

At Amazon, "Everything starts with data" is at the heart of the company's culture. Bezos always said, "The data will tell us what's right or wrong." This has also become an important decision-making basis for Amazon to continuously expand its own business areas.

In the early stage of B2B enterprise development, the market was relatively simple and the amount of information was not large. However, with the development of the enterprise, the amount of information has increased sharply, and the market has become more and more difficult. The boss has very limited information. Only by establishing a scientific data collection and evaluation system within the enterprise, and reasonably connecting with big data, we can master it as comprehensively as possible. information to improve the accuracy of decision-making.

Peter Zapf said: "I think data analysis is more important than big data. B2B companies already have a wealth of internal data, including marketing, sales and customer feedback data. The first step should be to track and use this internal data to improve the product. Quality or reduce business costs. This is supplemented by external data, including user ratings and reviews. In fact, most of this analysis can be done with Google Analytics or Microsoft Excel tools, and does not require big data tools like Hadoop. Enterprises should first think clearly about their business goals, and then think about how to strengthen their data analysis capabilities to achieve these goals.”

Testing the waters of e-commerce

According to the latest survey of "CEConline", More than 30% of Chinese suppliers have used cross-border online retail (ie B2C foreign trade websites) to sell sou products to overseas markets. Among them, more than 80% of the suppliers' investment has accounted for 25% of their total annual investment.

Shenzhen Jinfeng Cosmetics Co., Ltd. has tried to sell its own brand products on an e-commerce platform in the United States. They divide customer data into two categories: basic attributes and dynamic data. The basic attributes include customer age , income, occupation, gender, etc., and dynamic data includes transaction process, transaction records, transaction behavior, etc. After grouping, we will provide customers with personalized services as much as possible. Through the comparative analysis of the effect of the AB marketing experiment, find the most efficient marketing method. After the company has obtained user feedback, it will try to develop and iteratively develop innovative products with the help of big data analysis.

General Manager Gao Zhihong said that this new business not only helped them understand the needs of local consumers, but also obtained orders for some new mai homes. Of course, the premise is that logistics, warehousing, after-sou services and even unconditional returns must be done in place in the local market.

C&A Marketing in New Jersey, USA has more than 1,000 different brands, products ranging from camera equipment, speakers, beach products to kitchen supplies, mainly on online stores such as Amazon and EBAY. This company has more than 100 mai hands, and they go to Amazon's website every day to see user reviews of products, and they will look for inspiration from user reviews of products.

For example, a user commented on the speaker product: "If this speaker can be waterproof, without plugging in the power supply, I can listen to the radio even in the shower." At the same time, they use some big data analysis tools to analyze such information. If they think it is a business opportunity, they will design samples, find Chinese suppliers to produce a few samples and put them on Amazon soumai, and then continue to improve through feedback from buyers. If a product sells well, mass-produce it, and if it doesn't sell well, cut off the product. In this way, they continue to mine user reviews, find inspiration and design new products with micro-innovation, and then add new brands. The annual revenue reaches hundreds of millions of dollars, with an annual growth rate of more than 30%.

However, Xiao Diwu reminded: "E-commerce companies must live within their means. After all, B2C online shopping is small in volume and complicated in procedures, and it is difficult to become a new profit growth point for manufacturers. If the expectations for this business are too high , it is very likely that the bamboo basket is empty.”

Smart production under data

At present, many manufacturing companies can obtain daily or even hourly inventory, scrap volume, production volume, sales volume, order status, and on-time delivery through software rate and the fulfillment of product quality assurance.

Manager Liu Shilan of Nanjing Luculent Software said: "Tongliao Power Plant uses Luculent Liems (intelligent software management system) for equipment asset management. The software automatically collects production and operation data and helps enterprises calculate equipment maintenance requirements. .If the power generation equipment needs to be maintained after running 10,000 batches, the software will pop up a message after 9,000 batches to remind the maintenance personnel to perform maintenance on the equipment in advance, and at the same time remind the maintenance supervisor to check whether to deal with it, so as to avoid safety accidents. "

Although the implementation of big data technology has effectively shortened the response speed and problem solving time of enterprises, it is possible to respond to problems that originally took days or even months to respond in a few seconds. However, in order to fully and fully utilize the advantages of data, a very detailed and rigorous development process is required.

In the future, the manufacturing industry will no longer focus on the production and sales of the industry itself, but will integrate social resource platforms to produce, sell and operate together. Enterprise operation information and analysis software is rapidly becoming an indispensable tool for most employees of manufacturing enterprises. This software displays the production and operation indicator system and specific key indicators in an intuitive way, and the performance schedule is more dynamic. It needs to be adjusted individually according to the different application positions.

The latest foreign survey results show that the main reason for enterprises to invest in big data is to make decisions quickly and improve user experience satisfaction according to the actual situation. Seeing that many companies are flocking to big data and launching related projects, Peter Zapf disagrees. He said: "First, entrepreneurs need to determine what they want and how to do it. If they can't use big data tools and big data analysis to provide effective Information that can help business decision-making still cannot create value.”

In fact, big data platforms are gradually evolving into irreplaceable data ecosystems, constantly learning from known users, markets, products and risks. Discover new business opportunities. Nowadays, the relationship between traditional analysis and big data is getting closer and closer. How to effectively open up the boundaries between IT departments and business departments and establish a close cooperative relationship is a key link for B2B companies to successfully establish a big data strategy, and it is also the future development of the company. important direction.