When a new product comes out, when it is directly paid to promote it and put it on the market, the cost is usually relatively high, and the effect is usually not very satisfactory, and it is easy to fall into a dilemma.
What's the dilemma? The investment of the first or two times is often the feedback from the operator testing the market, which can also be understood as paying tuition fees. But the boss doesn't think so. He thinks that there should be output after investment. Seeing that the first or two productions have suffered serious losses, his confidence will be greatly affected.
When the operator has accumulated data, found out the market situation, and re-optimized the investment strategy, the boss is timid, and he is afraid of continuing to lose money; if he does not invest, the previous investment will be wasted.
But with torrent users, these situations can be greatly improved. Operators can set up a fission pull new process mechanism, which can allow seed users to fission pull new with very little cost. The new users who are pulled can be fissioned and pulled country email list again immediately, and then enjoy the same treatment as torrent users.
This operation method has become a standard routine in the education industry or knowledge payment industry, but the gameplay and concept have been changed, but the essence is still the same. Of course, the fission operation of seed users, in addition to the education industry, is also applicable to the e-commerce industry and the catering industry.
4. Seed User Operation
Since seed users are so important, how can we find and operate seed users? Here I present my initial mental model as follows:
1. User portrait
User portraits are believed to be familiar to anyone who is an e-commerce business. In other words, we need to be very clear about who our target users are.
But unfortunately, although we e-commerce merchants are familiar with user portraits, they are very unfamiliar. Familiar means that we know how to make user portraits, such as basic data such as gender, age, consumption level, and permanent residence; unfamiliar means that we don’t know what data we need apart from these basic data, and if we want these data, we have what use.
Then I give my user portrait model. Since there are many methods for user portrait, mine is for reference only, as shown in the following figure:
We make user portraits. The more detailed the data, the better, but the data is just data, and the data needs to be labeled (informatized) before it can be used.
There are two ways of so-called labeling, one is label classification; the other is informationization.
Labeling is easy to understand, that is, classifying those with the same and similar attributes into one label, and the relationship between labels and users is many-to-many; informatization is the informational description of user groups with detailed data and portrait tendencies.
For example, this set of data: female, 25~32 years old, company director, income 8000~12000, Guangzhou, has kittens, likes sports, and lives a positive life. Then we will describe this group of user data informatization as: urban white-collar workers, caring, like sports, and strong spending power.
Our operators can carry out targeted promotions during follow-up marketing. For example, for local users in Guangzhou, hold a badminton competition, and then promote badminton-related products once during the event.
2. Orientation catch dive
After the user portrait, combined with the seed user conditions and the big five personalities mentioned above, we can accurately select the seed user.
For example, if you want seed users of the Baoma category, then we can give away baby toys and baby supplies through certain thresholds, and obtain the first wave of Baoma users through joint promotion with offline mother and child stores. After doing this kind of activity to get the Baoma crowd a few more times, you can add to the WeChat of many Baoma, and then filter and screen out the seed users on this basis.