Speaking with data and use the facts is two different concepts, talking with the facts and talking with all the facts. In the actual market insight, all data is defined, based on a quantitative indicator of some standard dimension or statistical standard. Therefore, the objectivity of the data is only reflected above the statistical standards, not the fact that it is not true. So, when we ask the market analyst to talk by data, we are not necessarily the market. If the decision maker blindly uses these data on the basis of the statistical standard itself, the insight is not only reliable, but the action based on insight is inevitably hiring. However, speaking with data is another program of action for our truth for many years, or at least a certain political correct.

To give an example, in the process of today’s research on automotive product innovation, “scene” finally became a consensus of everyone. However, in order to continuing with data, we must do a variety of quantities. The following may have the following description scenario: We have survived 10,000 users, of which 8,500 have fixed up-off routes, and workdays must be self-driving. Among these 8,500 people, there are 4,000 people with a radius of more than 20 kilometers, and 60% of them will involve a segment combined with elevated roads and open roads. For those who have more than 20 kilometers of the upper and lower classes, there are 2,500 people in the average one-way commuter time of more than 30 minutes, 1,000 people in more than 60 minutes. More than 30 minutes, 900 people have breakfast in the car every day. After having breakfast, there are 500 people complaining that garbage is not placed …

It seems that this is a quantitative scene description of the fact that the data is complete, the logic is strict. At least in most people who are accustomed to speaking with data. However, how do we apply such a scene insight (statistically to product definition and development? No urgent, we can also compare other scenes. For example, in the above 10,000 studies, 1,500 people often drive to the surrounding scenic spots with the whole family weekends. Obviously, the coverage of the upper and lower scenes is 85%, and the frequency is about 5 times a week. The coverage of the weekend self-driving tour scene is 15%, and the frequency of use is about 1 time per month … From the indicator, this conclusion is determined, but this is explained? We can’t put the resource allocation of a car according to this frequency simple correspondence? For another example, in the above 10,000 research samples, there were 2 people who had a serious car accident and experienced the situation of the airbag pop-up. So what is the meaning of this 20,000 coverage?

Obviously, indicators such as covering and use frequency are not sufficient to describe scenes, more insufficient to guide the resource allocation problem of vehicle development. So someone thinks of adding dimensions solutions. For example, we can ask the user to pay attention to all the comments of all Russen, or these usage scenarios for the extent to which the user is buying a decision. Of course, in the operation of market research, it is indeed possible, and there must be a set of data that can return to the statistical report, and these data is very structured, and if it is displayed, it can definitely in accordance with most people. ” Clear, data is complete and logical strict “this evaluation criteria. But do you really think this is the truth? This can be applied to market forecasts or product definitions need to be in line with user lifestyle, caucasi-style and car standard predictions?

In the change cycle, when the integral reference is disappears, or at least become blurred, the user’s cognitive standards and cognitive power are rapidly changing, and the classic, with strong scribe color. Market cognitive logic must change. So what kind of cognitive logic is more likely to help us make more insights to the market? Contradictory is the best answer to the way out in the market in the market, and quickly iteratively.

Still about the case of the scene library, we are not more than the absolute quantization relationship of each scene, behind the scene reservoir is a change in lifestyle and vehicle. Therefore, we are looking for the direction of each scene itself, a new scenario that may occur, and various issues that users need to face on various scenarios. Simple frequency comparison or importance between scenes does not matter, meaningful is the similarities and differences of users in different scenarios, and users use the main contradictions that the currently found solution (existing product) and Contradictory main aspects. If superimposed on future lifestyle, the change of the car is used, the main contradictions faced by the user use the existing solution … In the above insights, we have to pay attention to the problem itself, not the quantification of problems. It is more than a simple quantization statistical comparison of quantization abstraction.

Looking at the problem with contradictions, we need to leave the facts and conclusions, static “shape”. Because only when we put all, at least the main energy is put on the problem itself, we can use the main aspects of the contradiction, define the main contradictions and contradictions. In order to find a resolution of contradictory answers more accurately.

By admin

Leave a Reply

Your email address will not be published. Required fields are marked *