Without Digitalization, How Long Can FMCG Companies Survive?

Source: New Retail Business Review (ID: xinlingshou1001) In the digital era, consumer demands change rapidly, market dynamics shift, decision-making accelerates, and the competitive landscape becomes unpredictable. The traditional enterprise-centric value chain (B2C) is gradually fading, and the consumer-centric new value chain (C2B) is becoming the new normal in the digital era. For companies that are currently small but innovative, digitalization presents a rare opportunity. For traditional FMCG companies, especially industry giants focused on offline operations, if they fail to complete transformation and innovation at critical junctures, their existing advantages may be caught up or even surpassed. What does digital transformation mean for the FMCG industry? Simply put, it requires companies to gain a deeper grasp of data, with the most important being consumer big data. By analyzing consumer big data, identifying core consumers, and segmenting them more personally—such as into dozens or even hundreds of "micro-segments"—companies can clarify consumer characteristics and personalized needs. Using customized leverage, they can improve attraction, conversion, and loyalty for different target micro-segments. This is a key consideration for all FMCG companies. Beyond consumer data, timely acquisition and application of other value chain and operational data—to enhance consumer service, improve operational efficiency, and support innovation in products, technology, and business models—are also critical components of digital transformation. Companies that move faster in digital transformation recognize earlier that data is the golden key to unlocking successful transformation. Therefore, these companies have actively collected massive consumer data through various channels (such as online and offline CRM/DMP systems, e-commerce platform data, smart stores, omnichannel layouts), channel data (such as distributor inventory and sales data, terminal retail data), and internal value chain operational data. Once effectively processed and applied, this data can quickly generate value. However, even leading companies are still in the stage of "crossing the river by feeling the stones" when it comes to effectively applying data, gradually enhancing their digital capabilities through continuous exploration, application, improvement, and re-application. On the path of digital transformation, companies face common questions: What are the quick-win levers? What are the key success factors? Without the former, digital transformation may not know where to start, and due to large investments and delayed performance, confidence may waver. Without the latter, digital transformation may not advance orderly or achieve comprehensive and far-reaching impact. To help companies stand firm, endure, and lead in the wave of digital transformation, Kearney has built a framework to support enterprise digital transformation: using business levers to drive business, and foundational elements to safeguard transformation. Against the backdrop of Chinese platform giants and FMCG companies actively experimenting with new retail, Kearney, starting from the acquisition and application of consumer data, combined with successful cases of beauty companies at the forefront of digital transformation, summarizes key success factors and quick-win levers for the reference of FMCG companies currently undergoing or considering digital transformation. Using Business Levers to Drive Business 1. Leverage new retail smart stores to further collect consumer data, more comprehensively promote online-offline integration, and create an omnichannel consumer experience. With the rise of online shopping, traditional store business and e-commerce business have gradually become fragmented, even antagonistic. The birth of smart stores has achieved the integration of online and offline consumer data, empowering brands to operate consumers across channels and blurring the boundaries between traditional store and e-commerce businesses. With strong promotion by platforms, many international and local beauty and apparel brands willing to try new business opportunities or expect to overtake on curves have actively cooperated. Meanwhile, consumers are curious about the smart store shopping experience, leading to rapid growth of smart stores in the past year or two. For brands, the charm of smart stores lies in their ability to collect deeper and broader consumer data than traditional stores.

For example, by scanning codes to identify consumers, sales associates can obtain more consumer information and experience preferences, including membership status and purchase history, enabling effective sales and more attentive service.

In-store smart hardware such as magic mirrors and skin testers not only provide consumers with fun, personalized shopping experiences but also help companies collect valuable data such as skin type and pain points, aiding future precision marketing and even product development.

The DingTalk smart sales guide successfully developed by Alibaba and Lin Qingxuan is a tool for direct communication between sales associates and their served consumers. It can customize daily task bars based on business needs and different consumer characteristics, helping sales consultants provide attentive service in a "foolproof" manner while achieving business goals. It can also allocate promotional coupons based on different sales associates' performance, improving promotional expense efficiency. Successful implementation of smart stores requires top-down promotion, granting certain authority to the responsible team (such as the new retail team), and effectively mobilizing both online and offline resources. Among these, a reasonable incentive mechanism for sales associates and the sales team is key to eliminating online-offline conflicts and promoting synergy. For example, for consumers bound to sales associates through smart guide tools, any online or offline consumption within a certain period counts toward the associate's incentives or commissions. At the same time, companies can incorporate tasks they want sales associates to achieve (such as new customer acquisition, consumer information collection) into the incentive mechanism, facilitating the goals they hope to achieve through smart stores from multiple angles. Additionally, companies need to closely monitor the flexibility and dynamism of incentive mechanisms to optimize corporate interests. Taking advantage of the golden opportunity of platform support for smart stores, companies should appropriately use various tools provided by the platform to improve smart store operational efficiency. Besides the smart guide tools mentioned above, precise traffic diversion based on crowd characteristic analysis, combined with attractive promotions, is also an important means. For example, as one of the pilot companies for smart stores, a domestic beauty company received low-cost precise advertising support from the platform, where 5% of consumers who received the information entered the store, and their consumption conversion rate reached 60%, much higher than the usual 15%. Currently, during the platform support period, the platform may provide resources including low-cost precise traffic diversion, guide subsidies, and even some data support. As a brand-new attempt, all participants in smart stores are still in the exploratory stage, and its concept and operations are constantly evolving. There are also several pain points that brands and platforms need to overcome together. For example, current smart hardware technology is not yet mature enough to provide consumers with an ultimate experience. If new-generation smart hardware cannot keep up, consumer interest after novelty may not be sustained. Another example: data is a very valuable asset for brands and an important bargaining chip for exchanging new retail resources with platforms. However, the degree of data openness varies by corporate strategy, especially for leading companies, where data confidentiality concerns are the biggest obstacle. Furthermore, many brands operate stores through dealer models, and many brand counters are under unified cashiering by department stores. In such models, how to balance the interests of brands, dealers, department stores, and platforms will be a difficulty in the business model. 2. Use automatic sampling/vending machines to quickly increase consumer touchpoints Automatic sampling/vending machines are new retail touchpoints that are faster to implement and have lower customer acquisition costs compared to stores. This is very suitable for companies with few stores but hoping to quickly expand offline touchpoints in a relatively short time. By placing well-designed sampling/vending machines in cities, business districts, communities, and campuses where core consumers frequent, brands can generate widespread exposure and product trials while obtaining valid identity information and product preferences from scanning consumers, forming the basis for future precision marketing. If conditions allow, it is even better to launch unmanned sampling/vending machines in conjunction with major shopping festivals such as Double 11, Super Brand Day, and 618. Similar to the platform tools based on crowd characteristic analysis mentioned above, companies can use platform-provided data to identify advantageous locations for placing sampling/vending machines, enhancing traffic and conversion rates. Due to the high mobility of automatic sampling/vending machine placement and the high flexibility of sampling and selling products, risks are relatively controllable for companies, and they can adjust execution plans based on continuous performance monitoring to ensure input-output efficiency. 3. C2B (Consumer to Business) product development and new product launches targeting market and consumer needs Traditional product development often analyzes consumer preferences through sample surveys or focus groups, which takes a long time and relies on incomplete sample data. In today's world with abundant and diverse data, companies can leverage continuously updated big data from third-party e-commerce platforms, social platforms, DMPs, etc., combined with their own consumer data, to save research time, more accurately and timely target consumers, deeply understand their behavioral preferences, and achieve true C2B development and new product launches. The charm of these big data lies not only in providing information on what products to develop but also covering every step of the product development process—concept, ingredients, packaging, capacity, price, selling points, etc. In today's era where consumers highly value personalization, C2B development and new product launches completely overturn the old game rules, making immediate and more precise consumer micro-segmentation possible in terms of cost and time efficiency, ensuring that products launched truly meet the personalized requirements and expectations of core consumers, presenting a clearer picture of local consumers, and laying the foundation for localized development and new product launches. 4. Content marketing and KOL (Key Opinion Leader) selection that aligns with local trends In this era of saturated traffic, competing for traffic has become a core focus for major companies. The carrier of marketing—content marketing—is an important lever for acquiring traffic: Content should be precise—customized content types (unboxing posts, plot twists) for different reading preferences; content should be innovative—combining the hottest IPs to amplify brand influence exponentially; content should be unified—images, videos, and even product packaging are carriers of content, and the disseminated content should be consistent. The foundation for creating precise, innovative, and unified content is that companies need to use Social Listening to fully understand and even predict trends and core consumer habits and preferences in a timely manner, then translate these understandings into influential and attractive content. With strong content in place, the next element is finding suitable KOLs to help spread it. Key dimensions for KOL selection include: The match between KOL and brand tone; KOL's follower count and whether followers are the brand's core consumer group; KOL's influence on followers' purchasing behavior; the number of endorsements by the KOL—if too many, the endorsement effect may be diluted by other brands; analyzing KOL's commercial value through historical data, such as reach, reposts, interactions, etc. Beyond selecting individual KOLs, companies need to pay attention to using effective KOL combinations to cover core groups most comprehensively while maximizing input-output benefits. At the same time, companies need to monitor appropriate KPIs, scientifically track KOL performance and effectiveness, and adjust KOL choices in a timely manner. Traditional content marketing and fan marketing often rely on the experience and intuition of internal teams or marketing agencies. If combined appropriately with data analysis, decisions can be made more scientifically. Additionally, there are numerous specialized agencies in the market that can assist companies of all sizes. They often have stronger market trend analysis, sensitivity, and response speed than companies themselves. Digital marketing implementation can be outsourced, but companies need to lead the overall digital marketing direction and control strategy formulation to ensure marketing implementation aligns with corporate strategic goals and positioning. Using Foundational Elements to Safeguard Transformation 1. Clearly define the scenarios and purposes for consumer data analysis, and build capabilities through both internal and external efforts In the big data era, data availability, visibility, and usability are all indispensable. Data application scenarios mainly include: customer acquisition, operating existing consumers (such as improving repurchase rates, cross-selling rates, average order value), product innovation, and achieving borderless marketing. Different companies and brands at different development stages have different priorities for data application scenarios, which directly determine the data that companies need to acquire and analyze, as well as the data sources. In today's world where data comes from multiple sources—own, partner, and third-party—companies that can systematically select, integrate, analyze, and apply data from the vast data sources have already succeeded halfway. For companies not yet mature in data acquisition, integration, analysis, and use, besides accelerating internal capability building, they can also leverage external forces—DMP operators and CRM operators. DMP operators can help companies broadly cover potential customers and achieve customer acquisition, which is especially important for companies with limited own consumer data resources. CRM operators can systematically "re-operate" existing consumers, effectively enhancing their value. Although traditional offline CRM has become relatively mature today, with high penetration in industries like beauty and maternal and child products, how to extend offline CRM to online CRM (ECRM) and social CRM (SCRM), leverage synergies between offline CRM and ECRM/SCRM, and between CRM and DMP, maximize the integration of consumer data, and present a more complete consumer journey remains a strategic focus for many leading companies. 2. Establish a digital-first organizational structure Companies developed under traditional offline models often have large offline teams, and offline contributions to overall business are relatively high. Therefore, e-commerce teams and offline teams often work in isolation. Some companies experience channel conflicts due to different online and offline prices and resource allocation, affecting offline channel sales. Other companies have resolved channel conflicts, but insufficient channel synergy remains a common problem, causing some companies' online business contributions to be far lower than peers, missing important revenue sources, and more companies have significant cross-channel consumer experience gaps. At the same time, an offline-centric, centralized culture often cannot fully meet the agility requirements of e-commerce businesses and partners in digital ecosystems like e-commerce platforms, a problem particularly evident in multinational companies. To alleviate these issues, some companies with high online business proportions have gradually integrated online business into offline business units. For companies where online and offline businesses belong to different divisions, using incentive methods like dual performance recording to bind the interests of online and offline teams is also a common practice among leading companies. Furthermore, leading beauty companies have successively established Chief Digital Officer positions at the corporate level to balance and optimize both offline and e-commerce, and promote cross-departmental digital collaboration. 3. Establish an effective digital ecosystem partner strategy In the digital era where consumer demands change rapidly and market changes are faster, companies need to introduce professional service providers from different fields to help them quickly seize market opportunities and achieve successful digital transformation. This requires companies to plan their digital business models more comprehensively, objectively assess their existing capabilities, and seek the most suitable external partners for capability gaps. Taking e-commerce platform digital operations as an example, most companies' online business digital operations and partners still mainly rely on TP (e-commerce business operators). TP's business advantages remain focused on e-commerce platform operations. Although some TPs are trying to expand their digital operation capabilities, high-quality data analysis, new retail, and other value-added services are not their strengths. Therefore, in some specialized digital fields, such as smart store setup, data acquisition, integration and analysis, and digital marketing, companies can consider leveraging professional third parties. Other areas mentioned earlier, such as social listening, content marketing, and KOL selection, also have corresponding third parties available. Of course, merely selecting appropriate third parties is far from enough. How to establish appropriate cooperation models and effectively manage third parties, and how to make different third parties cooperate effectively, are key to the effective operation of the digital ecosystem partners. Choosing a wide range of third parties can help companies quickly seize market opportunities. Of course, as their own capabilities gradually build, companies should consider gradually reducing dependence on third parties, transitioning some businesses, especially those related to core capabilities, from outsourcing to in-house operations. Conclusion In today's era where online and digital businesses have brought significant changes and impacts to Chinese companies, digital transformation is urgent. However, for most companies, digital transformation is still a brand-new topic. The experience, resources, and core advantages accumulated by companies in the past may become obstacles to transformation in the current era. To complete a new understanding of products, markets, consumers, and the industry in the short term, the urgent task is to set aside traditional thinking and use a forward-looking perspective to determine the goals, scope, and priorities of digital transformation. In execution, companies must not only build core capabilities internally but also actively and effectively use external professional service providers in various fields to quickly fill gaps and help companies stand at the forefront of the digital era. Tips will be paid 400-2000 yuan once adopted.