How to achieve refined operations at different stages of the product?

The job of operations is to "help products do things", focusing on attracting new customers, promoting activation, and recalling products, with the goal of making products live better and longer. Refined operations are the core thinking of operations in the current Internet environment. Simply put, this is a way of thinking based on data, which achieves better results with less cost and better user experience . So, how to achieve refined operations at different stages of the product? This article will sort out the following for students related to operations and products.

1. Primary stage of product

When an Internet product is in its initial stage, it is more focused on solving specific problems for a specific group of people and conducting market verification of its own business model . User experience is actually more important at this stage. After all, this is your "first close contact" with users. User experience consists of two parts:

1. Business model experience

Many times users are not aware of their own needs. Internet products do not provide products, but more of a way to solve user needs. Let’s take Taobao as an example. It not only moves products online to meet users’ greater shopping needs, but also provides a complete model from product selection, online payment to logistics. Imagine if it only supports you to buy something you can’t buy locally, but the logistics takes 1 month, would you still choose it? If Didi Taxi requires you to wave to stop a car with the Didi logo, even though it is still a shared private car, will you still choose it? Therefore, in addition to the product design itself, what is more important is the way to solve user needs, that is, the business model.

At this stage, the data you are looking at may not be how much revenue you have or how many users you have accumulated, but more about the feedback from vertical groups on the core functions. For example, for e-commerce products, you might look at how many people clicked Add to Cart:

Figure 1

Note: We define people who have at least seen the product details as the target group of the product. By comparison, we can find that among more than 1,500 people, more than 800 have clicked the "Add to Cart" button, which shows that the product meets the needs of the group.

For social products, pay attention to the number of users who use it more than 4 days a week.

Figure 2

Note: Social products require users to visit frequently. As can be seen from the figure, only 30% of users use them more than 2 days a week, which shows that the business model performance is not optimistic.

Financial products , see how many people look at financial products, how many people try to pay

Figure 3

Note: We define users who at least enter the product details page as vertical groups. As can be seen from the figure, 730 out of 1,589 people are willing to pay, which shows that the product meets the needs of the group.

2. Product design experience

An APP (Internet application) carries the company's business model. It can be said that all departments of the company revolve around one product. The design transformation (experience) of the product itself directly affects the operation and channel's assessment of their own work, and even affects the CEO's judgment of the project itself. Therefore, every product manager needs to know the basic conversion rate of the products he designs, so that if the conversion rate is low one day, he can quickly determine whether it is the product that is the cause? Or is it due to channel quality or operational strategy? You may need to filter out vertical groups of people, or define the basic conversion rate of a product during a period of stable traffic . for example:

(1) Registration conversion basic conversion rate

Figure 4

Note: Assuming that traffic is stable from September 1st to September 15th, the graph shows that the basic conversion rate is 69%. There is still room for improvement

(2) Purchase conversion base conversion rate

Figure 5

Note: We define all people who have seen the product as those who have the intention to buy, that is, the vertical group of the product. As can be seen from the figure, the conversion rate of a specific group is generally

Simply put, in the early stages of a product, the role of data operations is to help operations personnel conduct product market verification, provide direction for product operations , and promote product optimization and improvement.

2. Mid-term product stage

As the core functions of the product become more and more complete, the user base has become relatively stable and has accumulated a certain base. The goals of this stage are, first, to continue to expand the number of users, and second, to improve the ability to retain users. At this stage, the thinking and execution capabilities of refined operations are even more important. Usually we will extend the scenarios, from the core needs of the previous vertical groups to insights into the segmented needs of users around the core needs, so as to increase user frequency and stickiness.

For example, accounting tools add financial products, Internet finance products add gaming elements, and micro-loan products add consumer loan elements. The extension of these scenarios is more about promoting user retention or further improving core conversions. At this stage, what needs to be measured is whether these extensions have a promoting effect. In order to improve the user experience as much as possible, you need to understand the needs of vertical groups and even provide "one thousand faces for one thousand people" product design, rather than making it "bloated" and even affecting the core business conversion.

Let’s take the “Sign in to earn points” of mutual financial products as an example. Points can be exchanged for interest rate coupons. The original intention of product design may be to activate existing users to generate reinvestment and continuous activity, as follows:

Figure 6

Note: The usage rate of the sign-in function among "all investment users" is relatively high, which basically defines that the value of the function is reflected.

Figure 7

Note: Assuming that stickiness was launched on September 25 (vertical line in the figure), the number of repeat investors (i.e., successful investments more than once) did increase.

Of course, in addition to scenario extension, strategies similar to sign-in, membership points, and level privilege systems are also commonly used in the mid-term of the product, which will not be elaborated here.

3. Mid- and late-stage products

The user growth rate at this stage is relatively slow, and the product already has a relatively stable and large user base. If the early and middle stages of the product are looking for vertical groups and segmented user groups in order to meet the needs of different groups of people, then the later stages must introduce user stratification operational thinking and strategies, because at this stage, no matter the user size, the complexity of the business, and the company's core demands (which may be monetization or revenue expansion), you need to be able to operate in a holistic and efficient manner. You need to clearly define which ones contribute the most value to the platform, which ones need to be stimulated, and which ones are about to be lost. It is very necessary to provide different reach strategies for different levels of users. More data and smarter platforms may be essential. for example:

Figure 8

Taking mutual finance products as an example, for active users in the novice period, automatic operation actions and target measurement are completed through manual settings (users and trigger conditions): users with assets less than 50,000 and no investment behavior in the past 30 days are screened out, and cash coupons are accurately pushed to them. The effect is checked through automatic measurement: the number of users who have used cash coupons for investment within 3 days, and the absolute number/conversion rate/transaction amount are automatically analyzed.

*PS: The data involved in the figures in this article are all virtual data and are for display reference only

Summarize

Starting from the three major stages of product development, the core of stage operations and the data analysis thinking at different stages were explained and examples were given. Thinking and awareness are often more important than making some cool charts, because there are many ways to solve problems and verify ideas, just like the initial market verification stage of the product, you can get optimization guesses through data, or through user surveys or even user complaints.