How Much Longer Can Consumer Goods Companies Survive Without Going Digital?

What does digital transformation really mean for consumer goods companies?

At its core, it means gaining deeper command of data — and the most important data of all is consumer big data.

Analyzing consumer big data lets companies identify their core customers, segment them with far greater precision — into dozens or even hundreds of “micro-segments” — understand their distinct characteristics and individualized needs, and deploy tailored levers to attract, convert, and retain each target group. This is the challenge every consumer goods company must take seriously.

Beyond consumer data, the timely capture and application of a broader set of value-chain and operational data also drives digital transformation: it improves how companies serve customers, boosts operational efficiency, and fuels innovation in products, technology, and business models — ultimately strengthening competitive advantage.

Companies that have moved fastest on digital transformation recognized early on that data is the master key to unlocking a successful transition.

These leaders have proactively built up massive consumer datasets through every available channel — online and offline CRM and DMP systems, e-commerce platform data, smart stores, and omnichannel rollouts. They have also captured distributor sell-in/sell-out inventory data, retail point-of-sale data, and internal value-chain operational data.

Once this data is processed and applied effectively, it delivers results quickly. But figuring out how to apply it effectively is still uncharted territory — even for the most advanced companies. Progress comes through a continuous cycle of experimentation, application, learning, and iteration.

On the road to digital transformation, companies share a common set of questions: Where are the quick wins? And what are the critical success factors?

Without quick wins, transformation stalls before it builds momentum — too much investment, too little visible impact, and confidence erodes. Without the right success factors in place, transformation becomes fragmented and fails to generate lasting, broad-based change.

To help companies get their footing — and stay ahead — in the digital transformation wave, Kearney has developed a framework built around two dimensions: commercial levers to drive business impact, and foundational enablers to sustain the transformation.

Against the backdrop of China’s platform giants and consumer goods companies actively exploring New Retail, Kearney uses consumer data acquisition and utilization as its starting point. Drawing on best-practice case studies from leading beauty brands at the forefront of digital transformation, the framework distills the key success factors and quick wins that any consumer goods company — whether already in motion or still considering the leap — can put to use.

Using Commercial Levers to Drive Business Impact

1. Use New Retail smart stores to deepen consumer data collection, accelerate online-offline integration, and create a true omnichannel experience.

As online shopping has taken off, traditional brick-and-mortar and e-commerce operations have drifted apart — and in many cases become outright rivals.

Smart stores change that equation. By connecting consumers’ online and offline data, they give brands the foundation for genuine omnichannel consumer engagement, blurring the old boundary between in-store and digital commerce.

Driven by aggressive platform investment, smart stores have expanded rapidly over the past year or two. International and local brands in beauty and apparel — eager to capture new business opportunities or leapfrog competitors — have embraced the format, and consumers have responded with genuine curiosity and enthusiasm.

For brands, the real appeal of smart stores is their ability to collect richer, more comprehensive consumer data than traditional stores ever could.

For example, when customers scan a QR code to identify themselves, sales associates gain access to a wealth of information — membership status, purchase history, stated preferences — enabling more effective selling and more personalized service.

In-store smart hardware such as magic mirrors and skin-analysis stations does double duty: it creates an engaging, personalized shopping experience for the consumer while simultaneously generating valuable data — skin type, specific concerns, and more — that feeds future precision marketing and even product development.

One standout example is the smart shopping assistant developed jointly by Alibaba and Lin Qingxuan (Forest Cabin) on DingTalk. The tool enables sales associates to communicate directly with their assigned customers, auto-generates personalized daily task lists based on business priorities and individual customer profiles, helps associates deliver attentive service in a near-effortless way, and distributes promotional vouchers based on each associate’s sales performance — driving both customer satisfaction and marketing spend efficiency.

Successful smart store implementation requires top-down organizational commitment. The team responsible (such as a dedicated New Retail team) must be empowered with clear authority to mobilize resources across both online and offline channels.

Critically, the incentive structure for sales associates — and the broader sales team — must be thoughtfully designed to eliminate online-offline channel conflict and foster genuine collaboration. For instance, any online or offline purchase made within a defined window by a customer who has been matched to a specific associate through the smart shopping tool should count toward that associate’s incentive or commission.

Brands can also embed specific behavior targets — new customer acquisition, consumer data collection, and so on — directly into the incentive system, creating a multidimensional mechanism that aligns associate behavior with smart store objectives. Keeping incentive structures flexible and dynamic is equally important to optimize outcomes as conditions evolve.

While platforms continue to actively support smart stores, brands should take full advantage of the tools and resources on offer. Precision traffic-driving based on audience segmentation, paired with compelling promotions, is a particularly powerful tactic.

One domestic beauty brand operating as a smart store pilot received low-cost precision ad placements from the platform: 5% of consumers who saw the ads walked into the store, and of those, 60% made a purchase — dramatically higher than the typical 15% walk-in conversion rate.

Platform support at this stage may include low-cost precision traffic acquisition, sales associate subsidies, and data access, among other resources.

It bears noting that smart stores are still a work in progress for all parties involved. The concept and its operations continue to evolve, and there are real pain points that brands and platforms must work through together.

Smart hardware technology is not yet mature enough to consistently deliver a seamless consumer experience. If next-generation hardware fails to keep pace, consumer novelty may not translate into lasting engagement.

Data ownership is another sensitive issue. Consumer data is a precious brand asset and a key bargaining chip for accessing platform New Retail resources — but the degree of data sharing varies by brand strategy. For market leaders, concerns about data confidentiality remain one of the biggest obstacles.

Finally, many brands operate their stores through distributors, and in department stores, checkout is often handled centrally by the property. Aligning the interests of the brand, the distributor, the department store, and the platform in this kind of multi-party arrangement presents a genuine business model challenge.

2. Use automated sampling machines and vending machines to rapidly expand consumer touchpoints.

Automated sampling and vending machines offer a faster, more cost-efficient way to reach consumers compared with traditional retail locations — making them an ideal solution for brands with limited brick-and-mortar presence that want to scale up offline touchpoints quickly.

By placing eye-catching sampling and vending units in urban centers, shopping districts, residential communities, and university campuses frequented by core consumers, brands can generate mass brand exposure and product trial at scale. Each interaction also yields verified identity information and product preference data from consumers who scan to engage — creating a foundation for precision marketing downstream.

The impact is amplified when deployments are timed to coincide with major shopping events such as Double 11, Super Brand Day, or 618.

Similar to the platform audience segmentation tools mentioned earlier, brands can leverage platform data exports to identify optimal placement locations and maximize traffic and conversion.

Because the units are highly mobile and the products offered can be adjusted with ease, this format carries relatively manageable risk. Continuous performance monitoring allows brands to refine their deployment strategy and ensure strong return on investment.

3. Leverage C2B (Consumer to Business) product development and launch strategies driven by real market and consumer data.

Traditional product development has long relied on small-sample consumer surveys or focus groups — a process that is both time-consuming and inherently incomplete.

In today’s data-rich environment, brands can tap into continuously updated big data from third-party e-commerce and social platforms, DMP providers, and their own consumer databases. This allows them to shorten research timelines, identify target consumers with greater accuracy and timeliness, and develop a deep understanding of behavioral preferences — enabling genuinely consumer-driven development and launch processes.

The power of big data lies in its breadth. It doesn’t just inform what products to develop — it provides intelligence across every stage of the development process: concept, ingredients, packaging, size, price point, key claims, and beyond.

In an era where consumers place enormous value on personalization, C2B development and launch fundamentally rewrites the rulebook. It makes real-time, highly precise micro-segmentation economically and operationally viable, ensuring that the products brands bring to market genuinely meet the individualized needs and expectations of core consumers. It also reveals a clearer picture of the local consumer, laying the groundwork for localized R&D and market launches.

4. Invest in locally resonant content marketing and choose KOLs strategically.

In a landscape where attention is increasingly scarce, winning traffic has become a top priority for every major brand. Content marketing is the vehicle that delivers it — and the following principles define what effective content looks like:

Content must be targeted — tailored to different reading preferences, with formats (unboxing posts, surprising twists, tutorials) matched to specific audience segments.

Content must be innovative — leveraging the hottest IP and cultural moments to multiply brand reach and resonance.

Content must be consistent — whether expressed through written posts, video, or product packaging, the brand message must remain cohesive across every medium.

Underpinning all of this is social listening: brands need to monitor trends and deeply understand — even anticipate — the habits and preferences of their core consumers, then translate those insights into compelling, influential content.

Once you have powerful content, the next step is finding the right KOLs to amplify it. The key dimensions for KOL selection include:

• Alignment between the KOL’s persona and the brand’s identity
• The KOL’s follower count and whether those followers overlap with the brand’s core consumer base
• The KOL’s demonstrated ability to influence actual purchase decisions
• The number of brand partnerships the KOL has — too many dilutes impact
• Historical performance data: reach, shares, engagement rates, and commercial value

Beyond selecting individual KOLs, brands need to think in terms of portfolio — assembling a mix that achieves maximum coverage of core audiences while optimizing return on investment. The right KPIs must also be defined upfront to track performance scientifically and enable timely adjustments.

Traditional content and influencer marketing has long been driven by the experience and intuition of internal teams or agencies. Integrating data analysis makes decision-making more rigorous and results more predictable.

There is also a well-developed market of specialized agencies that can provide substantial support to brands of all sizes — often with sharper trend-sensing capabilities and faster response times than in-house teams. Digital execution can be outsourced, but the brand must retain ownership of its overall digital marketing direction and strategic guardrails to ensure alignment with broader business objectives and positioning.

Building the Foundational Enablers

1. Define clear use cases and goals for consumer data analytics — then build capability through both internal development and external partnerships.

In the big data era, data needs to be accessible, visible, and actionable. Core use cases include: new customer acquisition, retention and development of existing consumers (increasing repurchase rates, basket size, average transaction value, etc.), product innovation, and seamless omnichannel marketing.

Different brands at different stages of development will prioritize these use cases differently — and those priorities directly determine which data to collect, how to analyze it, and which data sources to tap.

With data now flowing from proprietary systems, partner platforms, and third-party providers, the companies that can systematically select, integrate, analyze, and apply data from this fragmented landscape have already won half the battle.

For brands still building their data capabilities, the path forward involves accelerating internal development while simultaneously leveraging external partners — DMP operators and CRM operators in particular.

DMP operators help brands achieve broad reach among prospective customers and drive new customer acquisition. They are especially valuable for brands with limited first-party data assets.

CRM operators enable systematic re-engagement of existing consumers, maximizing the lifetime value of the current customer base.

Offline CRM is relatively mature for categories like beauty and mother-and-baby — penetration is already high. The strategic frontier now lies in extending offline CRM to online CRM (eCRM) and social CRM (SCRM), unlocking synergies between offline CRM, eCRM, and SCRM, and bridging CRM with DMP to achieve a more complete view of the consumer journey. This remains a top strategic priority for many leading brands.

2. Build a digital-first organizational structure.

Companies that grew up in a traditional offline model tend to have large legacy offline teams, with offline channels accounting for the majority of total business contribution.

As a result, e-commerce and offline teams frequently operate in silos. In some cases, pricing disparities and resource allocation decisions create active channel conflict — undermining offline sales performance.

Even where channel conflict has been resolved, insufficient cross-channel coordination remains widespread. This leaves many companies with online revenue contributions far below industry peers, resulting in meaningful lost revenue. More broadly, the consumer experience across channels is often inconsistent and disjointed.

Compounding this, the centralized, offline-first culture that characterizes many traditional companies is poorly suited to the agility demands of e-commerce and platform ecosystems. This tension is particularly acute in multinational organizations.

To address these challenges, some companies with higher online revenue concentration have begun integrating online operations into their offline business units.

For companies where online and offline still sit in separate divisions, tying the incentives of both teams together — for example through shared performance credit — is a common practice among leaders.

Several leading beauty companies have also appointed a Chief Digital Officer (CDO) at the corporate level to balance and optimize both channels, and to drive cross-functional digital collaboration across the organization.

3. Build an effective digital ecosystem partner strategy.

In a digital era defined by rapidly shifting consumer needs and accelerating market change, brands must bring in specialized external service providers across multiple domains to help them move quickly, seize opportunities, and sustain successful digital transformation.

This requires companies to take a comprehensive view of their digital operating model, honestly assess their existing capabilities, and identify the right external partners to address their capability gaps.

E-commerce platform operations offer a useful illustration. Most companies still rely primarily on TPs (third-party e-commerce agency operators) for their digital platform operations. TPs remain strong at core e-commerce platform management, but while some are working to expand their capabilities, high-quality data analytics, New Retail, and other value-added services are generally not their strengths.

In more specialized areas — smart store setup, data integration and analytics, digital marketing — companies should consider engaging dedicated third-party specialists. The same applies to social listening, content marketing, KOL management, and other disciplines mentioned earlier.

Selecting the right partners is necessary but not sufficient. The real challenge lies in designing the right collaboration models, managing those partners effectively, and ensuring that different third parties work in sync rather than at cross purposes.

Working with a broad range of third-party specialists enables brands to capture market opportunities quickly. Over time, as internal capabilities mature, companies should look to reduce their dependency on external providers — bringing key functions, especially those tied to core competencies, back in-house.

Conclusion

For Chinese businesses, the rise of digital and e-commerce has already been transformative — and the pace of change shows no sign of slowing. Digital transformation is no longer optional.

Yet for most companies, it remains largely unfamiliar terrain. The accumulated experience, established resources, and entrenched strengths that once defined their competitive position can easily become liabilities in the digital age.

Developing a fundamentally new understanding of products, markets, consumers, and the competitive landscape in a compressed timeframe demands one thing above all else: the willingness to let go of traditional assumptions, adopt a forward-looking perspective, and make clear decisions about the goals, scope, and priorities of digital transformation.

On the execution side, success requires building critical capabilities internally while actively and intelligently engaging external specialists across relevant domains — to close gaps quickly and position the company at the leading edge of the digital era.