A New Profit Formula: How Does User Behavior Data Guide Profit Growth?

1. Profit VS registration volume?

I recently saw a question: Company A has half as many registrations as Company B, but its profits are twice as much as Company B. Why are profits and registrations not necessarily proportional? This question may seem a bit naive, but it actually reflects a common cognitive bias in the current market : many people believe that if a lot of people are using my product and there is traffic, then there must be money to be made. However, think about it, suppose there is a shopping mall that is crowded with people every day, but no one spends money to buy things, how can this shopping mall make money? And suppose there is another small shop that is empty every day and only has one or two business deals a month. However, the profit from each business is enough to support the business for half a year. How could this seemingly unpopular small shop lose money?

In fact, many people are often attracted by more intuitive data such as registration volume, active user volume, click-through rate , retention rate , etc., but fail to understand the relationship between these numbers and profits. On the one hand, user behavior data and business data belong to two different dimensions and cannot be confused; on the other hand, there is indeed a certain logical relationship between the two. Only by understanding and correctly matching them can we effectively help us guide our business through data.

2. User Behavior Data Profit Formula

To calculate profit, we first need to know the factors that affect profit. In economics, the profit calculation formula for competitive markets has long been provided:

Profit = (P-ATC)*Q

Among them, P = unit price; ATC = TC/Q = average total cost; Q is quantity. Simply put, the profit of a single product multiplied by its sales volume is the company's total profit. If you want to judge a company's current profitability, you only need to understand the profit margin and sales volume of a single product. As for the user behavior data mentioned in the previous article, it needs to be matched with the profit margin and sales volume to guide the company's overall profitability.

Based on this premise, I propose the following assumptions:

If the user behavior data that affects the profit of a single product is P1, P2, P3..., and the user behavior data that affects sales is Q1, Q2, Q3...,

Then in actual situations, we can actually simply derive the following formula:

Profit = P1*P2*P3*…*Q1*Q2*Q3*…=∏Pi*∏Qi

3. Refine the formula to guide profit

So how do we match user behavior data to profits and refine this formula to a usable state? In simple terms, it can be summarized into the following 4 steps:

1. Identify the core conversion path
2. Find behavioral data that affects product profits/sales
3. Matching user behavior data to form a formula
4. Optimize growth points based on behavioral data profit formula

The above four steps can help us screen the data indicators that are most directly related to profits, and then identify the most effective optimization methods for increasing profits.

4. Case

Here I will tell you a very down-to-earth real case that happened to me when I went home for the Spring Festival this year. I have a friend who opened a small children's photography shop in his hometown. When I went back to chat with him during the Spring Festival this year, we happened to talk about a New Year promotion event he had done before the Spring Festival. The event was spread through an H5 page on WeChat . The content and rules were roughly like this: to give back to new and old customers during the Spring Festival, the store will take a set of family portraits for customers for free. To be eligible to participate, you need to forward it on WeChat Moments 3 times on different dates. After completing the task, you can go to the store to enjoy free shooting. If you don't want to forward it, you only need to pay 9.9 to shoot directly.

I asked him how to make a profit since it is a free activity? My friend told me that as long as someone comes to my house for photo shoots, they will basically pay to select photos and purchase albums. Currently, 100% of the customers who come to my house pay in full, and the average order value has reached the expected level.

"But the profit is still too little." When my friend said this, how could I, a product dog, just sit there and watch?

4.1 Clarify the core conversion path

Let’s first sort out the core conversion path of this activity as a whole:

Since the entire activity did not collect page behavior data in advance, only some server-side data of users participating in the activity, I simplified it into the following process for the feasibility of subsequent optimization:

Core conversion path of photography activities

However, in fact, this activity seems simple to say, but in order to convert a user into a revenue, it actually requires the following complex steps: the user opens the activity page - flips through the pages to browse the activity content (up to 3 screens, and important information about the activity is on the 2nd to 3rd screens) - choose to forward or pay 9.9 - click to complete the first forwarding - the next day click on your own forwarding record to enter the activity page - click to complete the second forwarding - the next day click on your own forwarding record to enter the activity page - click to complete the third forwarding - obtain free shooting qualifications, submit personal information - go to the physical store to accept the shooting - select paid products such as photos and albums - complete payment, and the order is completed.

We all know that every additional step means an additional loss, and every loss will exclude some users.

4.2 Find behavioral data that affects product profits/sales

In this activity, what is the core step that affects the profit/sales volume of a single product?

1) Profit per product

We all know that profit = revenue - cost . Obviously, the part of the whole process that directly affects revenue is to encourage users to choose paid services after completing the shooting . However, considering the industry level and customer positioning, after understanding the actual situation with my friend, I determined that his pricing for a set of photo shoots was relatively reasonable, and the current average customer price has reached the expected level. From this point of view, if you want to improve profitability, it is not appropriate to start with the profit of a single product.

2) Sales volume

Then the only way is to start by increasing sales. Sales volume = potential users * conversion rate . The number of people exposed to the event directly affects the number of potential users, which in turn affects sales; the conversion rate of the core path also directly affects sales, and the only background data shows that this conversion rate is very problematic.

Core path conversion rate

The absolute values ​​of friends’ stores are hidden, and only relative values ​​are displayed: among all users who saw the activity page, only 10% completed the first forwarding, and the number of users who completed three forwardings was less than 2%. However, almost all users who were able to complete three forwardings went to the physical store to complete the photo shoot, and the conversion rate from free activities to paid orders was 100%. Obviously, the biggest loss in the entire process occurs in the first two steps - most users may not necessarily participate in the event even if they see it; and even if they participate in the event, they are not eligible to get free photos.

To sum up, in this activity, there are three main user behavior data that directly affect profitability: ① Number of people exposed to the activity; ② First-time forwarding rate; ③ 3-time forwarding completion rate.

4.3 Matching User Behavior Data to Form Formula

Based on the above analysis, we have determined the user behavior data that directly affects profitability, so the profit formula for this activity is:

Profit = Number of people exposed to the activity * First forwarding rate * 3rd forwarding completion rate * Single product profit

4.4 Optimizing growth points based on behavioral data profit formula

Continue to dig deeper into these three data to find optimization methods to increase profits.

1) Number of people exposed to the activity (PV/UV)

The number of people exposed to an event is actually the PV/UV that everyone commonly uses. This is also the most headache-inducing problem for my friend: he feels that not enough people have seen the event. At that time, his activities were mainly spread through WeChat by him and his store employees, and the coverage was very limited.

Here are my suggestions:

① Obtain new free traffic through resource exchange. If you want to get more exposure without spending money, you can get new traffic by exchanging resources, such as asking some familiar customers or friends with more appeal to help forward, and quantitatively evaluate their forwarding results. In contrast, you can treat people to a meal or give them a set of free photo shoots.

②Pay to acquire new traffic sources. If there is a well-known local WeChat public account to help forward the content, the exposure can be increased by hundreds or thousands of times, so even if the existing conversion rate remains unchanged, the profit can be increased. Paying money will increase costs, but since the core path conversion rate is known, by agreeing in advance on the CPC (cost-per-click) billing method, we can roughly estimate whether the cost of placing an order is acceptable. In other words, we can directly adopt the CPS (cost-per-actual-sales) billing method and directly return commissions from orders coming to the WeChat official account to the official account, which can also help us control advertising costs.

Of course, for this case, if you want to increase profits in a short period of time, the more direct and cost-effective method is as follows.

2) First forwarding rate

In my friend's promotion, the activity page design had great flaws: First, the first screen of the entire H5 page was occupied by a huge poster, which only displayed pictures and did not convey any activity content (the activity rules were placed on the second and third screens). The common H5 page turning rate in the industry is only about 20% - that is, 80% of the users who entered the activity page did not know what the activity was about and left directly ;

Secondly, of the two buttons below, the one with color used to strongly guide users is "Pay 9.9". In fact, no user has ever made a payment. And he learned from his friends that this was not what he wanted to guide users. He still wanted to let more people see this activity by sharing.

Obviously, if you want to improve the first forwarding rate, you need to make two adjustments:

1. Adjust information display to intuitively tell users the content and rules of the event on the first screen;
2. Remove the button for paying to participate in the event and highlight the sharing function.

Schematic diagram of the activity page. The entire layout is very unreasonable.

3) 3-time forwarding completion rate

This is the activity design that I don’t understand the most: Why must users insist on forwarding it three times? My friend told me that the main reason was to get more exposure. However, the total amount of traffic that a person's circle of friends can cover is limited, and the number of people who are interested in this event among this traffic is also limited. Perhaps posting to the circle of friends several times may allow some people who missed it last time to see the event again, but there is no data to prove that this scenario improves the overall conversion rate. On the contrary, this complicated event process will, on the one hand, affect the user's enthusiasm for first-time participation (too troublesome, don't want to participate), and on the other hand, it will also affect the user's participation completion (only forwarding on the first day, then forgetting about it, resulting in no free qualification) - but in fact, for my friend's business, free photo qualification is not a problem at all. The more people who get it, the better, and the more people who come to take pictures, the better.

In view of this situation, the following adjustments need to be made:

① Reduce the difficulty of obtaining free photos and reduce the number of user operation steps : directly change it to only need to forward once to take free photos;

② Considering that reducing the difficulty of operation may make the users screened out less enthusiastic about the activity than before (they may just play around and forget about it afterwards), affecting the visit rate, it is necessary for store employees to call back users who have completed the forwarding, stimulate users to come and take pictures, and prepare sales strategies.

The original rule requiring three forwardings screened out users who were "eager to take photos." Naturally, this group of people had a stronger visit rate and willingness to pay, but it also excluded most users who "kind of wanted to take photos." The revised rule expanded the screening range of the conversion funnel and allowed more users to enter the step of taking photos at home. In addition to still being able to take the original orders, new orders can also be converted through the employees' recommendation capabilities - this is the new profit growth point .

Later, in view of time and technical limitations, my friend extracted the parts that could be adjusted quickly from the above suggestions and modified the page display effects and activity rules. Even though the activity effects were affected during the Spring Festival holiday, profits quickly doubled.

5. Conclusion

Today, the entire industry has left the era of traffic dividends. From investment and financing to the companies themselves, everything has become calm, and refined data is the general trend. The connection between user behavior data and business data can only become more meaningful if it can be effectively identified and utilized. After all, money is the most real thing.

Mobile application product promotion service: APP promotion service Qinggua Media advertising

This article was compiled and published by @莔莔有神 (Qinggua Media). Please indicate the author information and source when reprinting!