Do data analysis like this and operations quarrels will be reduced by half

Operational work and data analysis are closely related. This article starts with an activity operation problem and analyzes how data analysis should be performed. I hope it will be helpful to you.

Students who do data analysis often serve operations, and they are also most afraid of operations entanglement. Because operations work is highly related to data analysis, six out of ten data analysis articles you see online are written by operations. Operations are so deeply involved in data analysis that they often argue with data analysts over analysis ideas, analysis methods, and analysis conclusions.

Today we will first look at the biggest problem. There are many types of operations (as shown below), among which event operations is the most strategic, most closely related to data analysis, and also the most criticized position. Let’s use it as an example today.

Please listen to the question: For a certain game APP, the user activity rate showed a slight decline in May. The activity operation team decided to hold a sign-in and clock-in activity to increase user activity (the specific increase was not specified). The data before and after the activity are shown in the figure below.

The activity operation team insisted that if there was no activity, the natural growth in May would have fallen. The boss thought this was nonsense. The activity operation team said that data analysts should use artificial intelligence and big data to accurately analyze the natural growth rate.

Q: You are a data analyst, what should you do?

1. Absurd things under the banner of science

First of all, what is the key point of this question?

A. Decreased user activity rate

B. Natural growth rate

C. Artificial Intelligence and Big Data

Think about it for a second.

Let's ask a question: One day, someone comes to you with a bow and asks you, "Please use artificial intelligence big data to accurately analyze how much higher my hit rate is than natural." What will you do? Will you pick up the keyboard and start writing code? - No! You will first ask him, "What are you shooting?"

If he says: I don't know what I'm shooting, can you help me analyze it? What would you do? Would you use artificial intelligence big data to analyze what he is going to shoot? ——Of course not! If you are polite, you will ask him to find the arrow he shot first; if you are impolite, you can just curse. Because even kindergarten children know: You have to set up a target before shooting. This is common sense.

So the overall point of the question is: it doesn't say how much it will increase. Even the question itself is problematic. Please note that the source of the problem is the decrease in the number of active users. As a result, when setting goals, the operation turned it into user activity . The difference of one word changes the meaning from clear to vague.

• What is a “degree”?
• It means the number of active users. Why not use it directly?
• What does it mean? Is the formula the same for everyone?
• The meaning is comprehensive calculation, what are the calculation formula and weights?

The indicators themselves are not clear, and there is no clear indication of how much to improve, which is a disaster for post-activity analysis . It is simply a replica of the archery story. The question is: why did such a weird thing happen?

2. The difficulties behind the absurdity

If you have actually worked in a company, you will know that not all decisions are highly rational, for example:

• This is a regular activity. The operation just modified the template and launched it online.
• This was done under the personal instruction of the boss. I don't understand it and I don't dare to ask.
• This is a business intuition: I feel there is a problem! It is too late to change it by the time you really observe it.
• This is a kind of superstition: Don’t you have artificial intelligence and big data? You should have it in no time.

In short, in real enterprises, probably:

• 30% of the activity plans were not clearly written, with only a vague statement: "Increase consumption/increase activity"
• 30% of the activity plans use imprecise terms, with a lot of fanciful concepts such as activity, activity value, and activity power.
• 30% of the activity plans have not been calculated, and are decided on the spur of the moment. Some even set a target of 100 million just to make the slogan catchy.
• Only about 10% of the plans can be written clearly: increase the number of active users, and maintain DAU above XX level in May

Of course, in large companies with standardized management, this kind of chaos is much less common. However, similar problems exist in most companies. They do not write clear goals in advance and rely on big data for analysis afterwards. They even try to get away with it by artificially creating a very low or negative natural growth rate . What should we do if we really encounter such a thing?

First, we must not talk about "natural growth rate". Especially in this kind of business with intensive short-term activities. If we must talk about it, we should adopt a buy-and-leave-it mechanism: everyone should agree on the natural growth rate in advance, and then we will look at this number afterwards and not adjust it. This is the same as refusing to regret a move when playing chess.

1. Make it clear in advance what your goal is, and increase it from X% to y%;
2. Find clear, intuitive goals and avoid fantasy/complex concepts;
3. Find goals related to core KPIs and avoid miscellaneous interference.

These are the three principles for solving the problem thoroughly.

Of course, there are two challenges in doing this:

Challenge 1: Some operations just don’t know how to set goals, can you help?

Challenge 2: Some activities simply don’t have goals set in advance, how can we remedy this?

3. Basic Methods of Setting Goals

There are three basic approaches to setting goals:

1. KPI Decomposition Method
2. KPI reverse calculation method
3. KPI Scenario Method

Corresponding to three scenarios:

1. Activity goals are KPI indicators
2. Activity goals are KPI process indicators
3. Activity goals are KPI-related indicators

Some students may ask: Why are they all linked to KPI? Answer: If what you do has nothing to do with KPI, then you know how important and urgent it is. Doing things that have nothing to do with KPI may affect KPI.

KPI decomposition method example:

KPI reverse calculation example:

KPI scenario method example:

It is very necessary to maintain good communication with operations at ordinary times, so that data analysts can intervene in the early planning. It can not only help operations to clarify their ideas, but also help operations to calculate their goals, and also prepare for post-launch monitoring and post-event review, killing three birds with one stone. The best state is to do the work in place beforehand and avoid quarrels afterwards. Everyone can cooperate and win together.

4. Basic methods of post-event remediation

If you don’t set a goal beforehand and you must make up for it afterwards, remember: the core is not the natural growth rate, but “what kind of indicators the business needs to achieve”. Especially in the situation at the beginning. When the overall goal has failed, worrying about the natural growth rate afterwards will often become a battle of scapegoating . At this time, you can do it in three steps:

Step 1: Set the direction

Step 2: Find a way

Step 3: Look at the details

Through such operations, we can at least end the confused state and clarify: what kind of curve we want to make, and determine which method to change this time. In the details, we can find the optimization direction for the next iteration.

Note that this is more based on the judgment that "it has failed so far". This is not a scientific way to evaluate the effectiveness of activities. If you want to scientifically evaluate activities, you must design experiments in advance, divide them into test groups and reference groups, and test the user response effect. Again, the more preparation you make in advance, the less you will worry about afterwards.

Many students will say: Even if we do this, our company's leaders are still superstitious, the operations are still brainless, and when problems arise, they still blame others. What should we do? Even so, Teacher Chen also recommends that everyone first understand: how to do this.

In this way, when we encounter problems, at least we can judge whether it is my problem or someone else's problem. At least we can know which direction to work towards. This is also the difference between real business scenarios and scientific laboratories: you have to dance with shackles, walking a tightrope between limited data, various types of colleagues, and too high or too low expectations.

Some students may ask: Huh? Why is there only half of the fight missing? What is the other half? Answer: This is another eternal question in the post-event analysis of activities: What if you do this! Why can't the number of active users be higher? What if it is higher? If one indicator is high, and the others are low, what should I do!

This is what we often call the comprehensive assessment problem.

Author: Down-to-earth Teacher Chen

Source: WeChat public account "Down-to-earth Teacher Chen"