Car services -

Snack Brand

Through Whale's store digital management solution, the overall data management and control of the store is improved, the store management efficiency is greatly improved, and the management cost is reduced.

Background

The snack brand focuses on providing consumers with high-end snacks, and has an omni-channel sales network with a well-balanced online and offline structure and a high degree of integration. At present, the brand has opened more than 2,900 offline stores and operated 99 sub-channel entrances online, making it one of the most popular national snack brands.
Needs

In the process of seeking new offline stores, the brand lacks the support of relevant data such as passenger flow conversion rate.
In the process of actual store operation improvement, brands lack support for store user behavior data.

Solutions & Value

By obtaining data such as the customer flow, customer staying time, customer flow line, etc. at the entrance and exit, it can analyze more store operation status such as the conversion rate of customer flow out of the store.

Capture and analyze real-time store dynamic data and user behavior data after customers enter the store.

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"As the competition in the casual retail industry intensifies, we hope to use the store digital management solution to greatly improve the data management efficiency of the store for the snack brand."

—— Whale

Store data management

With the development of China's economy, casual snacks have changed from optional consumer goods to popular and high-frequency essential consumer goods, with a market size of over trillion.

As an all-around player in the casual snack industry, L Brand is an online and online enterprise with balanced development. With L brand increasing the layout of its offline stores, the digital transformation and upgrading of offline stores and improving the efficiency of digital management of stores have become the general trend. But how to obtain and analyze the real-time passenger flow data of offline stores, realize customer store behavior data analysis and store operation data related analysis through the data platform, so as to improve the upgrade of store operation efficiency?

This is the part of the brand that urgently needs to be transformed. Under such a market background, Whale, which has a very strong data algorithm development team and development capabilities, and L brand, through the analysis of the passenger flow and user behavior data of its more than 2,900 stores, as well as the data of store business conditions, Help brands improve data management and control over their operations.

For the L brand with many offline stores, it is necessary to analyze data such as user behavior in major stores, obtain data such as daily store inbound and outbound passenger flow, and improve store management efficiency based on data and algorithms.

Whale is developed through AI recognition algorithms, and uses AI cameras to count the daily inbound and outbound passenger flow of the store to assist in monitoring the daily operation status of more than 2,900 L brand stores. Whale's functional modules in the spatial data platform can analyze various data indicators such as store user behavior data, greatly enhance the value of data, and help offline stores improve operation and management efficiency.

The cooperation between Whale and L brand has greatly improved L brand's data management and control of store operations, and has great data management and promotion value for the entire food retail chain industry. In the future, Whale will assist L brand to carry out follow-up cooperation around the digitization of the offline space of 2,000 stores across the country, and comprehensively upgrade the store data (such as customer group portraits, etc.) management system.