“ Attracting new customers is the first step in every industry and user growth strategy. ” In the user growth methodology, there are many user growth models. For example, the AARRR model is currently used more frequently, and there is also the user life cycle model and so on. Regardless of the model, the first step in user growth is to attract new users. Today I’d like to share some ideas and methods for acquiring new users. 01Project BackgroundWhen it comes to attracting new users , everyone is familiar with it. However, different industries and entities face quite different scenarios for attracting new customers. For example, when it comes to attracting new users on a platform (such as Taobao), the focus is on how to convert more potential users into Taobao users; the category operators in Taobao are focused on how to convert more users into users of the category I am responsible for; and the merchants on the platform are focused on how to convert more users into users of my store. Different people have different perspectives, and what they want to achieve in terms of “attracting new customers” is actually quite different. The scenario we will mainly share today is taking the e-commerce platform as an example to see how brands or sellers on the platform can attract new customers. 02 New customer acquisition direction and market analysisCurrently, most of the articles on the market about attracting new customers are centered around channels and methods for attracting new customers. In fact, before actually performing operations related to attracting new customers, you should first clearly understand the specific direction of attracting new customers. (1) Specific directions for attracting new customers For a brand on an e-commerce platform (let’s take Xiaomi as an example), the main directions for attracting new customers include:
(2) Evaluate the market size of each new customer acquisition direction For different new customer acquisition directions, the first step is to evaluate the specific market size and the possibility of new customer conversion in each direction. As shown below: The key metrics used here are migration rate (or conversion rate) and market size.
The joint analysis of the two indicators can effectively measure whether new customers can be attracted in each direction and from which direction to attract new customers. (3) Cross-category and cross-industry penetration How to achieve cross-category and cross-industry penetration? The analysis and measurement are mainly carried out through the following two aspects:
Through this analysis, we can understand which categories new customers of this brand prefer, which helps with cross-category selection.
(4) Penetration of brand competitors How to penetrate brand competitors? It mainly involves inflow and outflow analysis and competitiveness analysis.
The specific analysis content can be found in the figure below: 03 4W Analysis of Attracting New CustomersUnderstand which directions of attracting new customers have greater market and are easier to convert. So how do we attract new customers? We analyze through 4W. (1) Analysis of the rhythm of attracting new customers: WHEN Which node should we use to attract new users more effectively? First, determine the nodes with higher new customer acquisition effects based on the volume and proportion of new customers. Secondly, evaluate the quality of new customers based on their repurchase behavior in different periods. (2) Analysis of new customer acquisition targets: WHO Which user groups should we specifically target to attract new users? The following user analyses can be performed: (3) Product analysis: WHAT Which product is more effective in attracting new customers for a specific brand? You can analyze the product preferences of new customers of the brand: (4) Analysis of new customer acquisition points: WHERE The last step is to determine at which touchpoints it is better to reach users? Today I will share with you how to conduct analysis on attracting new users on your site. Author: Chief Data Scientist Source: Chief Data Scientist |
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