How Data Fusion Drives Retail Revival: Lessons from Suning’s Digital Transformation

Recently, the Central Committee of the Communist Party of China and the State Council issued the "Opinions on Building a More Perfect Market‑Based Allocation System for Data Factors," calling for accelerated development of a data factor market. According to the Ministry of Industry and Information Technology, China's digital economy exceeds 31 trillion yuan, accounting for 34.8% of GDP, highlighting the growing contribution of data to economic growth.

With the pandemic largely under control, the economy shows strong resilience and production is returning to normal. New industries and business models supported by big data and artificial intelligence are rapidly emerging, especially the digital transformation of traditional sectors.

Data Fusion: From Online and Offline Scenes

Traditional retail has been forced to shift online during the pandemic, adopting community marketing, data‑driven group buying, live‑stream sales, and industrial‑Internet solutions, creating a new ecosystem that blends online and offline operations.

Suning Carrefour upgraded its management system with the "Suning Store + Operation Workbench," enabling one‑click intelligent store management and real‑time sales and product data comparison. Store managers can instantly adjust procurement based on sales trends.

Leveraging Suning’s full‑industry ecosystem membership system, the company uses apps and mini‑programs to attract online traffic and digitize offline stores, collecting extensive member data. Big‑data analysis extracts and integrates massive user information to meet differentiated consumer needs, while a demand‑driven digital operation system supports the backend.

For retail enterprises, online‑offline omnichannel integration is essential for future growth. Suning’s comprehensive data across channels ranks among the top globally. Built on a big‑data and AI platform, Suning has deployed dozens of digital applications across multiple product lines, using the internet to bridge online and offline, consumer and production ends, and to manage the full customer lifecycle.

As the pandemic enters its later stage and offline retail recovers, it remains uncertain whether newly formed online shopping habits will persist, but those prepared can seize emerging opportunities.

Data Feedback: From Integration to User Operations

When massive data flows from both online and offline scenes, merely storing it is insufficient. Data must support business strategy adjustments and enhance user experience, fulfilling the entire user journey.

Traditional retail, even with data on traffic, conversion, and average spend, often only performs passive result analysis. Full‑chain user data analysis is crucial for acquiring customers, providing targeted services, driving conversion, and retaining users, especially as acquisition costs rise.

In June 2019, Suning’s Wuhu Plaza launched the "Little Lion Sister" IP, a popular WeChat account offering one‑stop services such as promotions, product recommendations, and customer interaction, strengthening the link between the plaza and consumers.

During the pandemic, the "Little Lion Sister" leveraged its large community to support merchants, creating group‑buying communities, offering free delivery for bulk orders, and organizing a "Pet Fan Festival" with over 40 merchants, providing affordable delivery services to the city.

By using data, Suning turned the IP into a private‑traffic operation tool, employing community marketing and mini‑programs to precisely analyze market demand, deliver personalized experiences, and continuously improve customer satisfaction and targeted marketing capabilities.

Data fusion originates from online and offline scenes and feeds back into user operations, illustrating how comprehensive data integration can drive retail innovation and support the broader digital economy.

As a leading smart‑retail enterprise, Suning’s full‑channel, full‑category, and full‑customer‑group strategy positions it to contribute significantly to domestic consumption upgrades and domestic demand stimulation under the national push to develop data factor markets.