In the live broadcast e-commerce industry, market analysis is the basis for companies to make strategic decisions. Through a comprehensive analysis of the overall performance of the market, analysis of core categories, and comparison of competing products, companies can understand industry development trends, tap market opportunities, explore core products, and enhance their competitiveness.
Business analysis and crowd analysis are important aids for companies to achieve their conversion goals. By analyzing core operating indicators, companies can understand their own business conditions and optimize operational and marketing strategies in a more granular manner. By classifying and analyzing target groups, companies can choose different strategic outputs to build mentalities and business conversions for different group segments.
In response to the pain points encountered by enterprises during live broadcast e-commerce, such as "lack of real-time data, incomplete interpretation and application, and lack of data visualization", Fanruan has launched a comprehensive solution - "Live Broadcast E-commerce Data Solution" to help enterprises Optimize operations, increase profits, and achieve higher business growth.
In this article, we will provide a more detailed interpretation of channel analysis and understand how to analyze the performance of different channels during live broadcasts to optimize promotion strategies and resource allocation.
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Channel analysis: From marketing planting to promotion and placement, find the best conversion of traffic
1. Pre-launch-traffic structure analysis
Before entering the launch, it is fundamental to understand the traffic structure. Live streaming e-commerce needs to analyze the audience characteristics, interests, spending power, etc. brought by different channels to determine the target audience and formulate more precise promotion strategies. Based on historical data and experience, we can predict which channels are likely to bring higher-quality users, making resources more targeted.
Taking the Douyin platform as an example, the live broadcast room mainly has three main traffic structures: natural traffic, video traffic, and paid traffic. And for different products, the distribution strategies are also different. For example, new products tend to focus on exposure, while hot products and mature products tend to combine product and effect. Enterprises need to find the main domain traffic through data analysis at a specific stage based on the level of the enterprise's people and goods.
2. Delivery in progress - traffic analysis
In the middle stage of channel launch, by monitoring the delivery effects of different channels in real time, the delivery strategy can be quickly adjusted to avoid waste of resources. For example, by comparing the click-through rate, viewing time, interaction status of different channels, and the conversion rate of viewers entering from different channels, we can discover which channels perform well and which areas are deficient, so that we can take timely measures and conduct more accurate Channel traffic.
Different from the complex paths of ordinary e-commerce, the conversion path of live broadcast e-commerce is usually relatively simple and clear. The path from planting to pulling out can quickly form a closed loop in Douyin. Traffic is only the first step. The next step is how to absorb so much traffic.
Taking products as an example, in the live broadcast room, through paid streams, natural traffic data, combined with product ranking changes, and continuous product ranking adjustments based on data feedback, it is possible to detect which products should be promoted and which products have the trend of becoming popular. Therefore, the products in the live broadcast room can be divided into traffic models, popular models, profitable models, and new models. Only by having different products in different dimensions can they effectively cooperate with the investment flow and generate greater benefits.
3. After launch - overall promotion review
The end of promotion does not mean the end of channel analysis. For review analysis, basic data analysis methods and principles still apply. No matter what type of e-commerce, channel analysis is to better understand the source and behavioral characteristics of the audience, thereby optimizing promotion strategies and improving business results.
But it’s worth noting that channel analysis is not just about numbers, but also needs to consider channel characteristics and user experience.
In addition to basic indicators such as ROI (return on investment), after a live broadcast, the analysis of click-through rate, conversion rate, outstanding payment and other data can guide the optimization direction of the next live broadcast. In addition, through comprehensive analysis of multiple data dimensions such as the number of product exposures, the number of product clicks, the transaction amount, the number of transactions, and the transaction amount in the live broadcast room, we can further understand the value of the product and guide subsequent live broadcast product selection to ensure good traffic acceptance. and transformation.
In such a fiercely competitive market for live streaming e-commerce, it is crucial to find the best conversion path for traffic. Channel analysis provides data support for each stage before, during and after launch, helping companies to guide traffic more targetedly and achieve higher conversion rates and business growth. Whether it is comparing and analyzing multiple channels to find the best traffic conversion, or optimizing promotion strategies, data analysis is an integral part of the success of live broadcast e-commerce.
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Solution summary
Combining multiple key scenarios such as market analysis, business analysis, crowd analysis, and channel analysis, we have constructed a comprehensive live broadcast solution designed to provide scientific guidance for data analysis of live broadcast e-commerce. The core of this methodology is to closely combine different scenarios to achieve a better overall effect.
In the vigorous development of live broadcast e-commerce, data analysis plays an indispensable role. Only with good data and good tools can we have good analysis. With the assistance of data analysis, what is more critical is whether we can extract meaningful and valuable information from massive data, apply it to live broadcast operations, and carry out strategies in the three directions of people, venues, and goods. Optimization.
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