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Data analysis methodology There is a comparison to be effective

Data Analysis Methodology: Comparison is Effective

In the era of big data, if you just bury your head in the sand, can not stand in the environment, only have a big picture view, in order to make their own road to the electricity business to go farther, this time, learn to analyze data analysis Comparison method is particularly important.

The last article briefly explains the 5 ways to get started with data analytics ( see "5 ways to get started with data analytics, you get it?"). The last article was a brief explanation of the 5 ways to get started in data analytics. In this article, we will first talk to you in the e-commerce circle operating the most, but also very practical and simple first thinking - comparison.

There is a reference, there is a comparison, only in knowing the good and bad high and low. If only a single look, the understanding of the information is bound to be not comprehensive enough to come up with really useful information. So in the end, what is the use of comparison in general?

First of all, to give you a popularization of two basic concepts.

Contrastive analysis, generally divided into two kinds, one is called static comparison, one is called dynamic comparison.

Static comparison is a comparison of different overall indicators under the same time conditions, also called horizontal comparison. For example, it can be their own single product with the peer comparison of other single products. Can also be their own situation, in the same period of time with the same industry a comparison of the situation.

Dynamic comparison is in the same overall conditions of different periods of comparison of the value of indicators, also called vertical comparison.

This method is more often used in the observation of a trend, there is a comparison to see the development of a good or bad. Then a single look at the day or month, simply can not see whether it is on the uphill or downhill. Comparison can look at a trend in the categories made, in the end, whether or not it is still popular, found the first signs of early risk avoidance, minimize losses, or expand the advantages as much as possible, for the front end.

With a detailed case to see. For example, need to look at a store's current traffic layout including whether the structure is scientific.

This data source can be downloaded from the business staff - traffic map.

Downloaded from the traffic map. Then we all perspective, make a map ( specific details see " " ").

What exactly is the advantage of the comparison method? First up a chart:

If you just see this, you may just understand what has been done alone. But if the following chart so:

It can be seen, what they are doing, peers in what they are doing, this peer is a peer excellent a data, that can be seen peers have which action is more effective, such as the Amoy outside the flow, but if they are in this area is not to do, the data show that peers are currently in the use of this piece of good results, the seller can also consider is not to be will their own Will this piece of follow-up. And then for example:

Look at a paid promotion channels, because it was peers, basically the same category, so you can look at peers with their own paid promotion of a difference. Look at the specific which way is the effect is better, but their own did not make good use of, did not take advantage of the reason is the activity can not report or that the input-output ratio is too low? Some of these reasons need to be based on their own store to think about, and then you can carry out a planning, to do which some, to get which some of the role, etc., for the store can be set in the direction of power.

Only after the correct use of comparative data analysis, many things will have a clear idea. This is the only look at itself and can not get the results.

The above is what I shared with you about the data analysis methodology There is a comparison to have the effect of the relevant content, more information can be concerned about the Global Green Ivy to share more dry goods