Recently, I had a conversation with the marketing director of an FMCG brand. When we discussed consumer insights, he showed me a PPT, the first page of which read: Core consumer group, 25-40 years old, health-conscious, quality-seeking, mainly urban white-collar workers. I asked him: "Is this profile based on actual data you've obtained, or is it your own judgment?" He paused and said, "It's about right; everyone in the industry draws it this way." I didn't press further. But sitting there, I suddenly recalled: the annual marketing expenditure in China's FMCG industry is a massive number. A large portion of this money is spent based on "about right" consumer profiles. The cost of this is far higher than most people realize—much, much higher!
The Most Expensive Cost for FMCG Brands
Is Not Knowing Their Consumers
I've observed consumer profiles from many FMCG brands, and most look similar: age range, gender ratio, city tier, health/vitality/quality tags, all piled together and labeled as "core users." Where do these profiles come from?
Some come from third-party research firms, with sample sizes of a few hundred to a thousand, where questionnaires capture what consumers "think they would choose," not their actual purchasing behavior;
Some come from media industry reports, which are generalized descriptions of the entire category and do not point to any specific brand;
Others, frankly, are brainstormed by the marketing department—referencing competitors, combining brand tone, and writing it down.
This is not a criticism of anyone. The information chain in the FMCG industry is too long, from manufacturer to distributor, to retail stores, to consumers, with too many layers in between. Manufacturers find it difficult to know who walks into which small store today and takes your product off the shelf. But if this problem remains unanswered, two costs will persist:
- The first cost occurs on the product side. If you don't know who buys your product, you don't know where the next opportunity lies. Developing new products based on market feel and following competitors has an extremely low success rate.
- The second cost occurs on the expense side. Marketing budgets have no anchor, so they are spread broadly, like flooding fields. Half the money is wasted, but no one knows which half.
Consumer profiles are the battle map for a brand's C-end campaign—where to attack, whom to attack, and how to attack are all on this map. But most brands don't have this map at all. This is not an industry secret. Almost everyone who has worked in branding knows this problem exists. It's just that in the past, most people thought there was no better way.
It wasn't until I recently spoke with Dong Wenbo, founder of Ronghui Shuke, and he shared a case study that I gained a new perspective on this matter.
A Pop-up Questionnaire Led to a 3.2 Billion Product
Dong Wenbo was the 001st employee of Dongpeng Te Yin's IT department and worked at Dongpeng for 12 years. He was a direct participant in building Dongpeng's marketing digitalization system from scratch. In 2023, he left Dongpeng and founded Ronghui Shuke, specializing in marketing digitalization consulting and support for FMCG brands. He knows the logic and practical aspects behind Dongpeng's digitalization best.
Around 2019, Dongpeng Te Yin faced a problem: competition in the functional beverage market intensified, and relying solely on Dongpeng Te Yin as a single major product made the ceiling increasingly clear. Where was the next product opportunity?
The team did something seemingly insignificant at the time: during a scan-code activity at retail stores, they popped up a questionnaire for store owners. It didn't ask profound market questions, just some open-ended fill-in-the-blank questions related to consumer needs. Store owners interact with consumers daily and know what people who buy beverages like, dislike, want to drink, and have looked for. These people are the information nodes closest to consumers, but there had never been a systematic channel for brands to listen to their feedback.
It was through this B-end user research that Dongpeng discovered a real but unmet consumer need—Bushuila (Hydrate) was identified this way. After the product launched, within just over two years, sales reached 3.2 billion. The significance of this is that it turned a judgment that could only be made by feel into a decision based on real channel feedback. In the early stages of product development, the value of this data is far beyond what money can buy.
But the story of Bushuila is just beginning.
After Launch, More Important Things Happen
Bushuila followed Dongpeng's usual code-marketing logic—consumers scan codes to receive red packets, and stores scan codes for verification. Each time a consumer scans, a piece of real behavioral data is left: where it was bought, when, and by whom. Once data accumulates to a certain level, combined with a big data label library of consumers, Dongpeng obtained a real group profile. This profile told them: the core consumer group of Bushuila deviated from the initial prediction of "young office workers." Real purchasing behavior showed that this group was clearly more inclined toward sports scenarios, with keywords like mountain climbing, cycling, and badminton halls appearing frequently.
So Dongpeng adjusted its advertising strategy. Instead of spending money on broad audience ads, it focused resources on terminal channels in these sports scenarios—small stores near sports venues, convenience stores at gym entrances, and areas with dense outdoor sports populations. The money was spent in front of people who would actually buy.
Looking back, this path is actually a chain of three actions:
B-end questionnaires unearthed real demand from the channel side, giving product direction a basis;
Code marketing turned consumers' real purchasing behavior into data, giving the profile factual support;
With a real profile, spending shifted from broad casting to precise targeting.
Without any one of these three, the chain wouldn't hold. Dong Wenbo told me a sentence that I think is accurate: "Many brands don't know where half of their marketing spend goes. This is not an ability problem; it's an information problem. Without data in hand, no matter how smart you are, you're feeling your way in the dark."
Most Brands
Are Still Where Dongpeng Was in 2015
Dongpeng took nearly ten years to complete this path. From initiating code marketing in 2015, accumulating C-end data, to building the capability to output consumer profiles, and then feeding profiles back into advertising decisions, the pitfalls encountered and system rebuilds are hard for outsiders to fully know. Dong Wenbo was a firsthand witness.
In 2023, he left Dongpeng and founded Ronghui Shuke. He said that after starting his own business, he came into contact with many FMCG brands and discovered that the difficulties these brands face today are almost identical to Dongpeng's in 2015. They know consumer profiles are inaccurate but don't know how to obtain real data. They know advertising is wasteful but don't know where the waste is. This is not a resource problem; it's a path problem.
Dongpeng's success had an unreplicable prerequisite: the boss personally led the charge, the whole company cooperated, and invested ten years in this endeavor. This is unrealistic for most brands. But the path can be replicated.
Dong Wenbo defines what Ronghui Shuke does as helping brands build a "C-end command center"—a consumer-centric decision-making system that bases product direction, advertising spend, and channel operations on real data rather than intuition. He knows what to build at each stage, how to allocate resources, how to prioritize, and where the pitfalls Dongpeng encountered over nearly ten years are. This is the core of his entrepreneurial venture: not just a system, but more importantly, a proven path.
In the entire system, consumer profile insight services are the most fundamental and critical link. Its working logic is not complicated, but every step requires solid data infrastructure support:
- Step 1: Data collection. Through code marketing, scan-code activities, and other methods, obtain first-party behavioral data during consumers' natural purchasing process—who bought, where, and how many times. This comes from real transactions, not post-hoc questionnaires.
- Step 2: Profile construction. Match and fuse behavioral data with third-party big data label libraries to generate multi-dimensional group profiles. Behind every label is a real purchase record.
- Step 3: Insight output. Profiles are not the goal; decisions are. Ronghui Shuke's delivery is not just a report; more importantly, it converts conclusions into actionable operational recommendations—which groups to focus on maintaining, which channels have low efficiency, and which seed users new products should reach first.
- Step 4: Closed-loop validation. After strategy execution, continuously monitor data and optimize the profile model in return. It's not a one-time delivery but a living system of continuous iteration.
In essence, Ronghui Shuke is turning the consumer insight capability that leading companies took nearly a decade to develop into an external brain that most brands can directly use. In the two years since its founding, Ronghui Shuke has gained the trust of many leading brands due to its deep accumulation in FMCG marketing digitalization. Current clients include Baixiang, Mengniu, Jianlibao, Master Kong, and Wanglaoji.
Final Thoughts
In March this year, at the CFC Conference, we proposed "Advancing Toward the C-End," a judgment that received widespread recognition from brand decision-makers. Building a C-end command center has become an important common topic for the FMCG industry. The core of building this command center is to draw the consumer profile accurately. Dongpeng took ten years to truly understand who buys its products. But more brands are still guessing today. It's not that there's no way; it's that they haven't realized that guessing itself is the most expensive cost. In reality, truly knowing your consumers will no longer be a bonus but a fundamental skill for brands. The next round of competition in the FMCG industry is essentially information competition. Whoever holds real consumer data will truly grasp the initiative in product direction and advertising efficiency.