How can data analysts help companies generate revenue?
Very good question! ! !
Some people often have questions. You, a data analyst, have a very loud title as a data scientist. Isn't what you do just a few graphs and tables? Why take so much money? Isn't the threshold low for more money and less?
Then I'm going too.
Haha, this may be a common bias of most people. The job of a data analyst is not what you make, but what you can think of based on what you make.
How to understand this sentence? That is to say, your final result may only be a few tables, but you explain these tables and give conclusions that ordinary people can't think of. This is the value of data analysts. The powerful big guys I know spend most of their time in Turn business problems into technical problems, technical problems are not problems.
Ordinary people really can't do this.
The one I mentioned above is a way for data analysts to help companies generate revenue, which is the kind that everyone often knows. department manager.
Say a few common items:
- The click-through rate of advertisements is increased by 1%, do not underestimate this 1%, because the base is large
- 5% increase in open rate of a feature
- 20% faster data processing and 25% savings in staff resources allocated for data processing and data presentation
For another example, I used to use FineBI to regularly extract data from the database, which directly saves the time for employees to make daily reports and weekly reports, and can continue to track data.
Of course, these are all within the company.
There is another way, that is external.
When my company grows and grows, my data department can directly serve the outside world. It is directly a small data company. It can incubate its own products and then sell them to others. For example, a product that is very popular now is made by a certain It was hatched by a group and then sold, but I didn’t see profit margins back then, so I can’t say too much.
There are two types of external income:
1. Data products
Is BI a product? Can we do it?
Is the reporting system a product? Can we do it?
To exaggerate a little bit, I will give you an entire big data company on the spot, but it is much more difficult. Otherwise, what do you think data product managers are doing?
These are all things that can generate revenue for the company.
2. Data service
There are many processes of data analysis: data collection, data processing, data analysis, data visualization, and each subdivision field has great achievements.
For example, FanRuan, which does data analysis and data visualization, has also grown into a domestic leader?
Of course, it is only limited to China, there are many similar companies, and different tracks have something that can be learned from, and everyone can grasp it by themselves.
I'm just giving an example here. There is also data consulting. It's not feasible to sell products alone. You have to tell your boss on the opposite side how data generates value. Otherwise, where is the competitiveness?
The last one is lectures.
Haha, I didn't expect it, now that data analysis is so popular, and packaging and packaging is casual, then the income will come. I feel a little distressed about the paying crowd.
How does data analysis generate value?
Judgment and decision-making can certainly be of great value.
However, in addition to conventional data analysis techniques (SQL, statistics, algorithms, data products, etc.) to make judgments and decisions, you also need to have other capabilities, such as knowledge of operations, products, business strategies, etc. (in fact, these knowledge are also It’s not difficult, but it’s just like separated mountains, too many people don’t want to learn, they just want to stick to their own ability circle).
I take the current C-end operation in the mobile Internet as an example. A regular analyst just looks at the new, retained, and lost C-side, combined with relevant data such as channels, do cross-analysis, output statistical reports, and tell the business side the status quo, so from the boss's point of view, you will definitely not be able to see yours. value.
The core value of the C-side must be to increase the scale of users (operations, products, technology, whoever has output to this goal, whoever has value, will fight, and the boss will support you).
Then you have to analyze, in the stage of your user life cycle, which link has a problem (one is to compare with yourself, the other is to compare with the competition), after knowing the problem, tell the operation how to change the activity, tell the How to modify the product (don't know?
Hehe, you must not know, you should consciously accumulate this knowledge, such as how the competition is organized, how the product is designed, why is it different from us, and what is the logic behind it? A lot of communication with operations, products, communication with core users, and data verification logic).
Enough said, let's stop here.
But for personal data analysts, don't think about the above, do business well and then talk to me about other things.