As a consumer asset platform, the brand data bank effectively integrates consumer data from all channels and provides strong support for the refined and hierarchical operation of the brand. This article will discuss the capabilities and applications of the Ali brand data bank, starting from the first acquaintance with the brand data bank, and gradually reveal the functions and characteristics of its four modules: integration, analysis, activation and application.
In the last series of "Ali Dharma Disk: Master the 6 Capabilities of Ali Dharma Disk!", we introduced the Dharma Disk DMP, and then we will explore the capabilities of Ali's brand data bank.
1. Acquaintance with brand data banks
Brand Data Bank is a consumer asset platform launched by Alibaba, which integrates consumer data from Alibaba's global channels and brand-owned data to help brands carry out refined and hierarchical operations.
The data of the brand data bank includes Alibaba's consumer data, such as Alipay, Alimama, Tmall, Cainiao Station, Ele.me, etc., as well as the brand's own consumer data, such as off-site media exposure, brand fan members, etc.
As shown in the figure below, look at the comparison of Ali's merchant tools, including brand data bank, Dharma disk, customer operation platform, and business consultant. In addition, the data bank capability includes the return of consumer data on the whole network of the brand, and the scope of data and application is wider than that of Dharma Pan and Business Advisor.
The brand data bank is developed from the 4A model, namely Aggregation, Analysis, Activation, and Application, and provides functional modules such as link flow analysis, custom analysis, and member fan analysis to help brands quickly and conveniently carry out consumer operations and precipitate brand consumer assets.
As shown in the figure below, the Alibaba-branded data bank mainly includes four modules: fusion precipitation, analysis and diagnosis, data activation, and application customization.
Next, let's unravel the mystery of each module of the data bank.
二、Aggregation融合
1. Consumer assets
In order to help brands continue to accumulate consumer data, restore the consumer journey, gain insight into the intimate relationship between brands and consumers, and continue to deepen the relationship with consumers, Brand Data Bank provides an AIPL method to divide consumer stratification.
The consumer asset module includes consumer analysis, end-to-end analysis, and link flow analysis.
Consumer Analysis: Divided into active consumers, consumer assets, active consumer benchmarking, consumer weekly growth rate, potential customer-to-customer ratio, and relationship weekly deepening rate.
Full-link analysis: Divide A cognition - I interest - P purchase - L loyalty to see the overall change trend of consumer groups at different stages.
Link flow analysis: divides the flow of cognition, interest, purchase, and loyal users at the beginning and end stages.
The consumer asset module is an early capability of the brand data bank, and its core lies in the AIPL model. Choosing the right user tiers and developing a conversion strategy around them is critical for consumer asset platforms. For example, Alibaba has an AIPL user layering model, JD.com has a 4A model, and Byte has an O-5A model, which is relatively simple and easy to understand, and the corresponding marketing conversion strategies behind them will be more complex and important. Interested friends can join the data exchange group to discuss.
2. Data fusion
In the process of development, the brand will accumulate multi-party member data, etc., which can be processed through the data fusion module. The data fusion module includes upload population, upload tags, party crowds, and party tags.
This module can better help merchants make good use of their own data.
III. Analysis
The analysis and diagnosis module conducts in-depth analysis from multiple perspectives such as fan membership, product analysis, scene operation, activity precipitation analysis, and brand growth analysis.
1. Scenario operation
Scenario operation is divided into new customer expansion, high-potential group to promote conversion, old customer operation to promote repurchase, member recruitment and operation, event group remarketing, new product operation strategy, etc. Scenario-based scenarios for some core operation methods can intuitively empower operation personnel.
Scenario operation is a new capability, and on the basis of analysis, more operation strategy templates are added to improve the ease of use of the product, which has great reference significance for us to recommend the crowd for portraits.
2. Fan member analysis
Fan member analysis, mainly including brand members, store members, active members, inactive members, purchased members, active unpurchased members.
3. Product analysis
Commodity analysis, constructing the relationship between people and commodities, and analyzing consumer behavior on a single product. And further analyze the total number of interactions, new brand awareness, interest, purchase, and loyalty of the item.
In the process of user segmentation, the more groups we divide, the more operators do not know how to use them, and it is difficult to form a more systematic strategy. What the brand data bank does better is that it uses the AIPL model and runs it through the entire product system, analysis system, and operation system, so as to maximize the value of data products.
4. Activity precipitation analysis
Activity precipitation analysis, precipitating consumer activity data, analyzing the total number of consumers, category purchasing power, consumer conversion power data 1 day before the event and the day after the event, as well as the analysis of the new acquisition and retention effect of the activity.
Marketing activities are very widely used in the promotion of major brands, and in order to count the effect of activities, it is necessary to do a good job in the return of activity data and channel data attribution. This is the key point and the difficulty, and the follow-up article will further study it.
5. Custom crowd analysis
There is also a more basic module is custom crowd analysis, which is mainly a crowd circle selection module, which is divided into several ways: field circle people, cargo circle people, attribute circle people, and IP fandom people. This is similar to the construction method of "Ali Dharma Plate: Circle Selection Crowd, Channel Precipitation Crowd, Intelligent Iterative Crowd...".
For example, in the e-commerce scenario, the model based on people-goods-field can be expanded to be used to circle people and people. In the long-term rental scenario, based on the tenant-tenant model, it is based on the housing circle.
四、Activation激活
Data activation is mainly a data application, which pushes the target group to multiple channels such as diamond exhibitions according to brand needs.
The docking here is divided into many channels, including Alimama, CRM, Strategy Center, Tmall Marketing Platform, AutoNavi, Alipay, Local Life and so on.
五、Application应用
The application module mainly includes the application marketplace and the data factory. For example, in terms of application market capabilities, brands can order complete solutions packaged by service providers according to different marketing scenarios.
The scenario operation strategy requires a certain amount of data analysis and marketing experience, and the service provider can sell it for commercial realization. This also shows the importance of marketing strategies in consumer asset platforms.
Columnist
Straw hat boy, public account: a data person's own place, everyone is a product manager columnist. Author of the book "The Road to Big Data Practice: Data Middle Platform + Data Analysis + Product Application", focusing on the field of user portraits.
This article was originally published on Everyone is a Product Manager. Reproduction without permission is prohibited
The title image is from Unsplash and is licensed under CC0.
The views in this article only represent the author's own, everyone is a product manager, and the platform only provides information storage space services.