The article at the beginning of this year mentioned several marketing trends for 2024. In the second half of the year, the several projects mentioned at the beginning are evolving rapidly. These trends have not only changed the way of marketing, but also reshaped How to practice the interaction between brands and consumers has become extremely important.1. About the new retail market
In he second half of 2024, the new retail market will face many challenges and opportunities. As technology continues to advance, consumer shopping behaviors and preferences are changing rapidly. The core of the new retail market is to integrate online and offline shopping experiences to provide consumers with a more convenient and personalized shopping experience. However, achieving this goal requires overcoming many technical and operational difficulties.
First, the new retail market needs to establish a complete supply chain management system to ensure rapid distribution of goods and accurate inventory management. Secondly, brands need to use big data analysis and AI technology to deeply understand consumer needs and preferences, so as to provide more personalized services and products. Finally, how to effectively integrate online and offline data to achieve omni-channel data sharing and collaboration is an important challenge facing the new retail market.
2. New retail X AIGC
AIGC technology can help brands quickly generate high-quality marketing content, improve brand exposure and consumer participation. For example, through AIGC technology, brands can automatically generate product descriptions, advertising copy and social media posts, thereby saving a lot of labor and time costs.
In addition, AIGC technology can also be used to build a personalized recommendation system. By analyzing consumers' historical purchasing behavior and browsing records, it can automatically generate personalized recommendation content to improve consumers' shopping experience and conversion rate.
For example, a clothing retailer could use this technology to automatically recommend matching options and new products based on consumers' preferences, thereby attracting more repeat customers.
3. RMN development and practice
Retail Media Network (RMN) is a new marketing model that provides brands with efficient advertising channels by monetizing retailers’ online and offline traffic. The core of RMN is to use retailers' data resources to accurately locate target consumers and improve the effectiveness of advertising.
Retailers can attract advertisers to place ads by establishing their own RMN platform. Specifically, retailers can use in-store data, such as consumers’ shopping behavior, purchasing preferences, etc., to provide precise target audiences to improve conversion effectiveness.
For example, a large supermarket can build a digital screen (DOOH) on its e-commerce platform and physical stores to display advertising content for various brands and dynamically adjust it based on consumers' shopping behavior.
4. How to do OMOAIGC technology can help brands quickly generate high-quality marketing content, improve brand exposure and consumer participation. For example, through AIGC technology, brands can automatically generate product descriptions, advertising copy and social media posts, thereby saving a lot of labor and time costs.
In addition, AIGC technology can also be used to build a personalized recommendation system. By analyzing consumers' historical purchasing behavior and browsing records, it can automatically generate personalized recommendation content to improve consumers' shopping experience and conversion rate.
For example, a clothing retailer could use this technology to automatically recommend matching options and new products based on consumers' preferences, thereby attracting more repeat customers.
3. RMN development and practice
Retail Media Network (RMN) is a new marketing model that provides brands with efficient advertising channels by monetizing retailers’ online and offline traffic. The core of RMN is to use retailers' data resources to accurately locate target consumers and improve the effectiveness of advertising.
Retailers can attract advertisers to place ads by establishing their own RMN platform. Specifically, retailers can use in-store data, such as consumers’ shopping behavior, purchasing preferences, etc., to provide precise target audiences to improve conversion effectiveness.
For example, a large supermarket can build a digital screen (DOOH) on its e-commerce platform and physical stores to display advertising content for various brands and dynamically adjust it based on consumers' shopping behavior.
The goal of OMO's strategy is to integrate online and offline resources to provide consumers with a seamless shopping experience. Realizing the OMO strategy requires deep integration and collaboration of brands in technology and operations.
First, brands need to establish a unified data management platform (such as CDP) to achieve seamless connection between online and offline data. This includes establishing an all-channel membership system so that consumers can enjoy the same discounts and services whether shopping online or offline.
Secondly, brands need to strengthen the coordination of logistics and supply chains to ensure rapid delivery of goods and instant updates of inventory. For example, a supermarket chain can establish a smart warehousing system to implement an online ordering and store pick-up model to improve shopping convenience for consumers.
5. New retail applications of data analysis
Finally, data analysis is the cornerstone of realizing personalized services and precise marketing in the new retail market. Brands can use data analysis technology to gain an in-depth understanding of consumer needs and behaviors, thereby providing more accurate product recommendations and marketing strategies.
First, brands can use data analysis technology to conduct in-depth analysis of consumers’ shopping behavior and identify the needs and preferences of different consumers. This can help brands develop more precise marketing strategies and improve the effectiveness of advertising. For example, e-commerce platforms can use data analysis to identify which consumers are more interested in specific categories of products, so as to carry out targeted promotions for these consumers.
Secondly, data analytics can also be used for supply chain management and inventory optimization. By analyzing sales data, brands can predict which products will have higher demand in the future, thereby making inventory adjustments in advance to avoid inventory backlogs or out-of-stocks. Through data analysis, we can predict which styles of clothing will have higher sales in a certain season, so we can stock up in advance.
In the second half of 2024, the new retail market will usher in more opportunities and challenges. The application of AIGC, RMN, OMO and data analysis technology will become an important means for new retail brands to achieve growth and competitive advantage. By in-depth understanding and application of these technologies, brand owners can provide a more personalized and convenient shopping experience, improve consumer satisfaction and loyalty, and thus stand out in the fierce market competition.
