After experiencing all kinds of data-based entrepreneurship, the author deeply feels that entrepreneurship with the theme of big data is Gao Fushuai's behavior. For entrepreneurs, we should not only have the thinking of big data to help customers create value, but also better understand the ecosystem of big data. They should not consider becoming a platform, or even imagine becoming an important infrastructure provider in the data ecosystem and a leader in an industry. More importantly, they should first consider how to become one of the beneficiaries of the data age.
According to the observation, the author combed the viewpoint of big data and wrote it for entrepreneurs' reference.
1. About making money with big data
The value of big data is no problem, but its commercial value depends on the number of users;
Simple example: 100 yuan has found the value of 10 yuan. If you sell it to 8 people, you will lose 20, and if you sell it to 80 people, you will earn 700. The profit is extremely high.
In other words, the data-driven business value density is relatively low, and building a business system by relying on the number of users will be very violent once it gets bigger, because the cost of value replication approaches zero.
2. About the big data business model
At present, big data is still in the initial stage of conceptual system construction, which solves the problems of increasing the existing data volume and fast processing speed. Few big data platforms really use their big data to complete real product innovation rather than channel expansion.
In terms of technical benefits, marketing:
Commodity recommendation, advertising recommendation, reading recommendation, talent recommendation and travel recommendation search optimization are all profitable; As far as safety is concerned: compliance, early warning and intelligent inspection can save costs and improve efficiency; As far as product innovation is concerned, there is no case of product innovation in kind; UGP (user-created product) platform will be even cooler.
At present, the search business, security business, public opinion, intelligence and marketing business that make money are all successful cases, and there are many more. It is up to everyone to cut in, remember to provide applications, and don't engage in systems. Big companies are like this.
3. About the universal value of big data
Discovering the value of big data is like discovering a new civilization!
Data is the wisdom of the masses and will help individuals make scientific decisions!
Compared with the previous data science, today's DT can be online in real time to predict future trends!
At the enterprise level, it will be more scientific to force the enterprise's human, financial, production, supply and sales system.
Open data is the greatest progress in human history!
The value perception of data should not stay in the business field. All walks of life need data-driven, and so do all disciplines. We humans constantly quantify the universe through data.
4. Big data and marketing
The organic combination of science and art
The data is faster and more accurate, and the art is more infectious!
Science is promoted within the scope of rationality, while art is irrational!
The biggest contribution of big data is still in marketing!
Artistic value > data mechanism
The effect of data on marketing has increased by N%, and art has increased by dozens, hundreds and thousands. In the data age, a good marketing is the result of the combination of data and art.
5. The greatest value of big data: big data+object = intelligence.
Knowing in the heart is wisdom, and knowing in things is wisdom!
Data provides human beings with creative materials and enables them to learn the skills created by God.
Big data permeates all scenes, making objects intelligent and behaviors intelligent. Whoever learns the benefits, please use big data to help XX change and make sentences (big data helps to speak, help cure diseases, help eat, help travel and help quarrel);
This is the core value of big data. What kind of data hardware needs, how to meet this data demand, how to save resources, how to improve data utilization, and how to consider data exchange and flow between hardware are the most important. The terminal decides the background, and the consumer decides the market! Intelligent hardware is the ultimate use of big data.
6. There can be big data without data.
Wisdom is higher than knowledge, and wisdom is dynamic. Can be generated at any time (real-time calculation): your mentality, initial heart, courage, innovative thinking and interpersonal relationships in the work environment are all conditions. We are all the result of big data processing from data, information, knowledge to wisdom. The ancients had no data but produced wisdom, so big data thinking should not be limited to the data level.
7. The best business model of big data
Will free data and charging api be the best business model of big data?
Perhaps the best business model of big data is big data trading.
8. The value of big data to enterprises
Auxiliary business lifecycle management:
All walks of life have big data-driven business changes, any industry.
From social customers-original lead customers-leads-opportunities-
Order-product design-service-word of mouth-socialized customers,
The closed loop of the whole business needs data to participate.
Auxiliary data lifecycle management:
From data generation-data collection-data transmission-data storage-data processing-data analysis-data release, display and application-generating new data "is the closed loop of the whole data efficiency value. Need data to participate.
9. When big data intelligent PK is logical.
The post-big data era may be natural science. Now the summit must talk about big data, but after big data, the author thinks that talking about natural science and creating everything naturally, data is only one of the products of nature;
10. Big Data and the Book of Changes
Thinking: reasoning VS deduction, using 0 1 computer technology to collect some data, applying some mathematical algorithms, choosing an empirical scenario, and deducing a conclusion. The collection is incomplete, the algorithm is inaccurate, the scenario is wrong, and the reasoning is wrong.
The study is that one gives birth to two, two gives birth to three, and three gives birth to everything. The ancients who mastered the Book of Changes could pinch, calculate, predict and deduce. This is the ancestor's Yijing civilization, and deduction may predict everything;
The Book of Changes says that two sports at a time, three geomantics, four products and five books are big data conclusions for society. Yijing is big data thinking.
The above ten viewpoints are some thoughts of the author and friends who are interested in starting a business with data themes. What I want to communicate with you is to understand the market demand of big data. From the perspective of value, data can be divided into three categories: first-party data, second-party data and third-party data. At present, the first-party data processing of enterprises (hadoop and other ecosystems will be a great demand, the strategy of the United States is open source, the strategy of China is data opening and OEM follow-up, and many manufacturers have their own technologies) is the most urgent demand at present. The second requirement is first-party data analysis (tools such as BI), and the third requirement is to improve security control. Secondly, the application of second-party data. This demand is to integrate the enterprise's own business, accelerate business cooperation, and integrate the application and technology of business partner data. The last type of demand is the need to purchase third-party data to expand business, either to enhance product experience or to expand customers. This demand promotes the flow of big data, which is the main driving force to promote the liquidity of big data and improve the industrial chain.
These are the top ten data ideas about entrepreneurs shared by Bian Xiao. For more information, you can pay attention to Global Ivy and share more dry goods.