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The Way to Break the GameFi Circle: How to In-depth Insight into GameFi Players?
Original author: SunnyZ Translation: Planet Daily
Summary
background
Following the last growth experiment, in the past month or so, I started a growth experiment for the GameFi segment.
Why choose GameFi as the target track?
First of all, GameFi is the field that everyone thinks can best achieve user massive adoption. It is an important entry point to dig out the overlapping users of Web3 native users and Web2 game players, that is, Web3 players.
Secondly, GameFi has a relatively large number of active users, and there are many projects that are still operating in the bear market. Data on the chain shows that the number of active addresses in the past 24 hours is about 200,000, and the number of active GameFi project parties is currently more than 900.
Although compared to the entire cryptocurrency market, the overall size of GameFi is still relatively small. As of the first half of 2023, the size of the global GameFi market is about 6 billion US dollars, but the gameplay and revenue mechanism of the GameFi market are attracting more and more players participate.
Understanding the behavioral preferences of Web3 players is critical for optimizing the operation of game project parties and adjusting the design of games and revenue mechanisms.
Segment track samples
The entire GameFi subdivision has many fields, mainly composed of 8 parts - client aggregator, game, multi-game platform/publisher, liquidity provider/financial instrument, blockchain solution provider, game engine, development merchants/studios and chains.
In order to further understand the real user portraits of Web3 players, the sample project parties selected for this activity belong to the game field. Here, IOSG’s classification of Web3 games (based on Steam’s classification and the highest-grossing mobile game types) is cited here. Web3 games Mainly divided into 5 categories:
According to the above classification, the 10 game projects on the right side of the figure are selected as key analysis objects.
GameFi Activity Data Mining
In addition to the regular activity indicators, purchasing power indicators, and influence indicators, for this GameFi event, data on player behavior preferences in Steam has been added, as follows:
Steam Stats Metrics
Among them, there are 5 game styles, 22 game themes, and 30 game types.
Breakdown of Steam game types, themes, and genres
Explanation of various indicators
3-General Game Category
5-Play Style
22-Game Theme
30-Game Genre
Note: Interest-related — all data in this article comes from Clique
Web3 Player Profile Overview
Generally speaking, there are usually two logics for GameFi to acquire customers. One is: the traditional release and purchase method is the main method + Web3 community promotion is supplemented. Relatively fixed, and the ROI is controllable, if a part of the budget is used to promote the Web3 market, it is not bad if there are hundreds of conversions from real players;
The second is: Alpha community promotion and Launchpad/task platform focus on customer acquisition + supplemented by traditional social media promotion. This type of route is a relatively original approach, and the idea is similar to that of white bills. This method belongs to casting a wide net to catch more fish. The target users are not precise and the quality is low, the cost is uncontrollable, and it is difficult to achieve very good results in a bear market.
For most GameFi project parties, whether it is path 1 or path 2, the first step is to accurately find Web3 players.
Judging from the sampling data this time, the number of real players covered is about 2,000 (here, the real player standard is that the wallet balance and Steam game time are both greater than 0), of which Web3 players account for about 20%. The per capita ETH holdings of Web3 players is 16.5, the average fans of TW is in the order of 500, and the per capita game time on the Steam platform is 1,784 hours. Compared with ordinary users, the purchasing power of Web3 players is about 4 times, social influence is 1.2 times, and the average total game time is about 4 times.
The next step is to convert this part of Web3 players to games.
Game Behavior Preferences
Overall, the Web3 players participating in this activity will spend more than 2,000 hours on average on their preferred game types, and they prefer to play hardcore multiplayer and action games.
The above data shows that the playability of the game is still high enough to attract real gamers. The current Web3 game can be understood as Fi+Game instead of Game+Fi. The gameplay is obviously insufficient, and players lack the motivation for long-term interaction. .
Many Web3 games are trying to use Tokenomics to extend the user's interaction time and the life cycle of the game, but in fact, from the perspective of data, it is more likely to solve this problem from the perspective of playability.
Game Type Preference
Web3 players have a very obvious preference for game types, and they like fast-paced, operation-heavy games. Although I will try many different game types, I will only spend more time on specific types.
Traditional players have become accustomed to high-complexity games, such as PlayerUnknown’s Battlegrounds, PUBG, RDR 2, etc. When designing the gameplay of the project, you can refer to the game genres preferred by users and what types of games are most popular with players. It is welcome and suitable for superimposing Web3 elements and gameplay. The core logic is that the game itself must have asset trading needs. At the same time, it is best to mobilize the subjective initiative of the community and transfer part of the operational difficulty, so that it can run more naturally. Here is a quote from GallonLabs (TW@gallonwang):
And some games are not suitable for "Web3ization" at this stage, such as MOBA games, which have high development costs, difficult operations, and long life cycles. They are completely uncompetitive in the current GameFi segmented game field.
Game theme preference
Web3 Player Classification
In the traditional game player classification model, players are divided into killer type, achievement type, social type and exploratory type according to different interaction objects (Player/World) and interaction methods (Acting/Interacting). This classification also applies to Web3 players.
Due to the limitation of data types, the classification of players in this event is mainly based on the preferred game type, style, duration and other information. 67% of the players are social players, 16% are killer players, and 11% are achievement players , 6% are explorers.
1. Social players【 67% 】
Basic information: style preference Multiplayer and Co-op games, type preference Action (action), MMORPG (massively multiplayer online role-playing), MOBA (multiplayer online tactical arena), Strategy (strategy) games, etc.;
Player portraits: Social players are interested in interacting with other players and getting to know different players. They are usually used to the guild battle mode and are also very familiar with who to turn to for off-market transactions, like water groups, and second creation Player overlap is relatively high;
Strategy reference: More social elements can be superimposed on the game mechanism. In terms of operation strategy, these players can be given the role of community administrators to drive other players to participate in the game, and these players can also be used to contact core players or Big family.
2. Killer players【 16% 】
Basic information: style preference Multiplayer and PVP games, type preference Action (action), Shooter (shooting), Battle Royale (battle royale), Arcade (arcade) games, etc.;
Player portrait: Killer players are keen on winning. Competitiveness is their first requirement for the game. They will learn various skills in order to win or climb the leaderboard. Unlike achievement players, they only care about winning or not, and don’t care about the means , usually krypton gold or explode a certain game, or even use bugs or plug-ins;
Strategy reference: The game mechanism can be optimized on the player rankings, or the competitive nature of the battle can be increased to moderately arouse the players’ competitive spirit. The operation strategy can guide such users to krypton gold to upgrade props to satisfy their desire to win Refreshing.
3. Achievement players【 11% 】
Basic information: Style preference for Singleplayer and PVP games, type preference for Action (action), Adventure (adventure), Simulation (simulation), Survival (survival), Puzzle (puzzle) games, etc.;
Player portraits: accomplished players will take the initiative to complete the tasks and goals of the game, customs clearance is a basic requirement, and some will set their own goals for customs clearance, and they are more sensitive to customs clearance incentives, and they will be very happy to get some rare rewards;
Strategy reference: In terms of game mechanism, you can work hard on the balance between the complexity of tasks and the rarity of rewards. When players start to feel impatient, giving more special rewards can mobilize these players to the greatest extent. enthusiasm, operational strategy
4. Exploring players【 6% 】
Basic information: Style preference for Singleplayer and PVE games, type preference for Action (action), Sandbox (sandbox), Adventure (adventure), Indie (independent) games, etc.
Player portrait: Exploring players have a strong interest in the game world itself, especially those extreme surprises, hidden plots, and strange bugs. The purpose of their games is to understand the entire game mechanism and become polymaths of the game world. He is also keen to answer questions for newcomers and share his discoveries.
Strategy reference: More easter eggs and hidden plots can be placed on the game mechanism, and a game feedback group can be established on the operation strategy to allow them to deeply participate in the gameplay design of the game, encourage them to output more content, and at the same time give them game evangelists The role is to answer questions for newcomers.
Analysis by project
Since most of the games on the Steam platform are client-side games, the selected data samples have limited data reference for mobile game projects. However, we can still clearly see from the current data that the number of users attracted by different ways of acquiring customers is very high. Differently, two typical cases are CounterFire (Ex CEBG) and BLOCKLORDS.
CounterFire(Ex CEBG)
BLOCKLORDS
Speaking of which, don’t be in a hurry to scroll down, first observe the data below, and you can guess which one of the above-mentioned customer acquisition paths of CounterFire (Ex CEBG) and BLOCKLORDS corresponds to?
Note: There is a certain deviation in the data of a single event, please refer to the actual operation data
CounterFire (Ex CEBG) is the first one: the traditional distribution and purchase method is the main + Web3 community promotion is supplemented; BLOCKLORDS is the second one: Alpha community promotion and Launchpad/task platform are the main customer acquisition + traditional social media promotion is auxiliary.
From a data point of view, I a priori believe that CEBG chose the native growth method of Web3, because user portraits are similar to many task platforms, with low purchasing power but high activity. After the interview, it was found that it was not. CEBG converted twice as many Web2 users from Facebook and other channels as Web3 users, which is why these players do not have too many assets on the chain.
Contrary to common sense, if we do not refer to the player data of traditional platforms such as Steam and Epic Game, we often directly classify users with small wallet balances as wool parties, and ignore the conversion of these players, because it is easy to fall into experience Fortunately, multi-dimensional information can help us avoid misunderstandings, and data will never lie.
Interestingly, in terms of the choice of growth strategy, BLOCKLORDS and CEBG, which are both from the background of the original game manufacturer, choose very different methods.
BLOCKLORDS’ customer acquisition is mainly due to more Web3 channels, because whether it is NFT sales on IMX and Polygon or community beta testing, they have deliberately set the threshold for Web3, and basically do not engage in activities to attract Web3 speculative users. The content of the product and the core assets of the game is used to acquire customers. After the time period is prolonged, this method is easier to accumulate OG members.
The only way for GameFi to break the circle
This event made me have some thoughts on GameFi's customer acquisition and breaking the circle. Let’s talk about retreat here. It’s quite interesting to see a meme recently:
It's a bit ironic, but it's true. GameFi is mostly Ponzi with game shells, not many real players.
Once upon a time, GameFi had high hopes on the issue of users' massive adoption, and the prosperity of Axie and Stepn brought unlimited imagination to the industry.
However, it seems that the game experience at the product level is not good, the economic mechanism lacks stability and sustainability, and the ecology is relatively fragile; the lack of real players at the user level limits the rapid development of GameFi, and it is unknown when GameFi Summer will come.
If you want to break the circle, you have to make some changes.
In addition to optimizing products and economic mechanisms, understanding Web3 players and attracting Web2 players to enter the market is a hurdle that must be overcome.
Among the game projects involved in this event, there are not many project owners who understand the growth strategy and know how to gain insights into Web3 players. They are still relatively blind. Know what type of players are in this community.
The first step in doing a project is to figure out who the target users are and whose money they are earning. This determines whether to convert users from Web2 or mine users from Web3, and also determines what elements should be emphasized in the game’s economic mechanism and gameplay design. The development cost of a good game is very high. When the playability is sufficient, the life cycle of the game will be extended passively, and the number of experienced players will increase. It can also transfer part of the operating costs to the community to support the self-production of the product. This can also balance the impossible triangle of development cost, operational difficulty, and life cycle to a certain extent.
Fortunately, I have observed a very positive phenomenon. The game projects that the bear market is still actively building now have a lot of playability, and they no longer blindly rely on financial products. After all, games are still consumer goods, and there must be real consumers (players) ).
Whether it is digging a small number of core users from Web3, or converting gamers from Web2 with more traffic, there is no standard answer to this matter. Black cats and white cats, the cat that can catch mice is a good cat. No matter what the method is, it is exploration, and pioneers are needed to open up the way for later generations.
After all, from a certain point of view, GameFi seems to be the only hope for the whole village on the road of breaking the circle of Web3.