After finding the problem, a better way is to propose el salvador phone number library countermeasures. For example, if the DAU reported daily has dropped, and you find that it is related to a drop in natural traffic, can you find a corresponding solution based on this problem? If you can do this, congratulations, you can already jump out of this article.
But it is also reasonable if it cannot be done. To be able to propose solutions, it depends on the understanding of the company organization, business conditions, and external environment. It takes more time to correctly interpret and propose solutions. I will share more about this part later, but let’s first move on to the summary of this section.
Summary: Data sensitivity does not necessarily require all three to be achieved
Of the above 3 points, 1 and 2 are essential elements, your business hotline that never sleeps and I think 3 can only be achieved by accumulating enough experience. At work, I sometimes encounter situations where I can’t come up with a solution. So if you who are reading this article cannot do any of the above points yet, don’t worry. Just practice according to the following methods, and I believe you will gradually develop your own data sensitivity.
Ways to develop data sensitivity
Let’s go back to the question mentioned at the beginning of the article: As someone with no data-related background, how can I start to develop sensitivity to data?
Let me tell you another good news. When I first came into contact with data, I was a complete newbie. I had no idea about how the data changed, and I didn’t know what to do with it. But after several years of work training, I also developed a sensitivity to data and became a data analyst who can discover problems behind the data and further study business issues.
Here are 3 steps to develop your data sensitivity. I believe that it won’t take too much time for you to have a keen sense of data.
1. Know what the indicators represent
Knowing the meaning of indicators means that you have a deep understanding of the business and know which data indicators are truly important to the company. Taking the ratio of new and old paying customers of e-commerce as an example, what is the definition of a new customer? What is the definition of a returning customer? If the proportion of new customers decreases, what might we need to pay attention to? Do we need to compare other indicators to confirm whether there is a problem?
To put it simply, if you know what questions you should ask next after seeing the changes in the indicator, then you understand the meaning of the indicator.
2. How do I know if there is a problem with the data? Check the report every day
If you skip the first step and go directly to the second switzerland leads step of looking at the reports every day, it will be difficult to develop data sensitivity because you don’t know what you are looking at at all, and the results will definitely be poor. In fact, looking at the report every day is divided into 3 steps:
1. Integrate all data into one report
If the company does not have financial statements yet, then your first task is to compile a report of the important indicators of the company’s business and review it every day. The advantage of integrating all data into one report is that no data will be missed, and the data changes between indicators can be clearly seen.
There are many tools on the market that can create data reports.
For instructions on how to use Google Data Studio, you can refer to my course on Hahow, ” Data Studio Visual Reports | Easy to Use Data Analysis ,” and send me a private message to get a 20% discount coupon for the course. After the class, you can independently create a complete data report and develop your sensitivity to data as quickly as possible.
2. Observe changes in data indicators
The feelings that the human brain remembers are actually very unreliable, so in addition to looking at the data every day, you also need to observe the changes. The most typical changes include “How much has it increased/decreased compared to yesterday?” and “How much has it increased/decreased compared to last week?” Just observing these two percentages can greatly enhance your sensitivity to the data.
3. Catch the floating range
After you complete step 2-2, you will find that the data should have a floating range. When the data exceeds the floating range, it means something has gone wrong! The floating range is not certain, it may be 3 percentage points or 5 percentage. Solutions can be points, depending on the product scale, indicators, and user behavior, but if it does not exceed this floating range, it is basically normal. By observing for a long time like this, you will be able to improve your grasp of the data!
