Game Data and analysis

I. About DATA

  data can be divided into two categories, one for operational metrics data. A class of business behavior data. 1. Operational indicators Data       For example, Dau,pcu,ltv,roi and other commonly used to represent the game's current operational status of some data indicators, with a single indicator or multiple indicator combinations to reflect the game's current online operation status, the indicators are generally related to each other, obtained by the correlation definition transformation calculation.       Example: Calculate metrics based on three common simple data about the number of users, revenue and advertising costs of the game to measure the quality of your ads (users). (similarly measurable channel quality)       2. Business behavior Data ① data acquisition:      user behavior data captured during the game experience. such as a user to fight, complete a purchase, to achieve a task, and so on. At the same time each goal is completed, there will be a lot of process data, the data in the filtered case, the useful data through the data logging, and stored in the database for query and analysis.       ETL----about behavioral data in the process of data being recorded to the query, most of the data ETL has been completed. Because the log requirements have been carried out before the execution of the business model of the behavior of the filter, as far as possible associated with the relevant system behavior model, so that the log data is not fragmented, not redundant, the purpose is to be able to query data in the later time with SQL more efficient (with the increase in the number of users, the promotion of operating time, The amount of behavioral data reaches a certain level, and data extraction is more convenient to allow more time to analyze the data. ② data Query:      in the behavior database that has been recorded, query with SQL.       In order to ensure the accuracy and timeliness of data, database query permissions should be a full data table. Because the data need to be flexible to extract, so in the non-essential case, generally do not bother the program classmate to help extract data (as if the computer process is suddenly suspended when executing).       Special cases: In addition to data warehousing, not in accordance with the regular structure, and the data is more scattered, in the case of the sub-database, the need to query large data and more complex correlation of target data, You may need bi-child shoes or a service-end child's shoe to assist in writing shell scripts or other scripts for data extraction, but this is generally a rare situation.  3. Market research Data       Some market research data can also be recorded and analyzed, and some conclusions are drawn, the validity of the findings of the research data depends on the validity of the research data.    second, on the analysis1. Analysis of operational indicators data through daily indicators data records, single-index horizontal comparison, or multi-index correlation difference, with practice, to find out the relatively obvious law, such as Saturday of user activity is generally the highest in a week, the most suitable to open pay activities. 2. Analysis of business behavior data ① game behavior data-the data that the player generates when participating in the relevant game system, is used to analyze the player's experience in the game and whether it is within the planned expectations. If desired or above expectations, be happy. If not below the expectations, then from the player's behavior data reflect the reasons for the departure from the planning expectations, analysis of the player's behavior tendencies, to estimate the reasons for deviation, data validation, objective to give planning a certain reference data and related recommendations (in the game design has a certain understanding of the situation), in order to improve the relevant game system. For example, in-game multi-career design is balanced, level difficulty is reasonable, PVP experience is standard, in-game economy (resources) system is normal and so on.     It is mainly used to improve the current game design situation, let the game through the data support to get better iterations, more closely match the needs of players and planning expectations. The premise of this part of the analysis is that the game itself has a deep understanding of the game, the game design has a certain understanding. ② Operational activity data-the behavioral data generated by the player's participation in the operations is used primarily to measure the quality of the operational activities. Before the event, the data can also provide relevant support, such as what the player needs more, and less need, in order to do targeted activities.     This part of the data on the game to help the commercialization of large. The bias in operational activities (La Nieu, pull-pay, pull-active) does not affect the effectiveness of data support.data analysis only to a certain extent to improve the existing game experience, in the operational activities in advance to avoid unnecessary risks, in the market research to give relevant data conclusions, always adhere to the data as a supplement, product-oriented philosophy.

Game Data and analysis