We Are All Product Managers
Yu Jun's book was initially written for internet product managers, and it may seem unrelated to investments. However, upon closer examination, the definition of a product manager is quite broad and extends far beyond the scope of internet product management. It can encompass roles as diverse as a national leader, an all-powerful deity, or personal life planning. The difference lies in the specific domain each individual operates in, but there are many commonalities among them.
On another note, Yu Jun's book is worth reading because it delves into deep and foundational thinking, rather than merely providing a compilation of summaries like typical textbooks. This suggests that truly exceptional product managers must possess profound underlying thinking abilities. This rings true in the real world, where figures like Steve Jobs, Jeff Bezos, Jack Ma, and many great political and business leaders such as the founding fathers of the United States, Mao Zedong, Deng Xiaoping, Sam Walton, and Howard Schultz demonstrate outstanding product management with profound levels of thought.
When it comes to our investment industry, whether it is investment firms themselves or investment managers, they fit perfectly into the standard definition of product managers. The only difference lies in the nature of the products they manage.
Different Industries, Different Characteristics of Product Managers
Of course, the characteristics of product managers vary across different industries. For example, in the consumer goods era, the focus of product managers is on sales. With relatively certain demand and standardized production supported by mature industrial methodologies, products themselves tend to become homogeneous. However, the differentiation in brand positioning, marketing, and channel control can determine whether a company earns 1 billion or 10 billion. Therefore, the value created by product managers in the sales and marketing direction is greater in this context.
In the software era, product managers primarily focus on managing software production. In the early days, most software designs were for B2B purposes, and the requirements for B2B software were relatively straightforward. Iterations could be carried out based on customer demands. The scarcest resource at that time was qualified engineers capable of producing software, and the supply fell short of the demand. As a result, product managers could create more value through production management: communication coordination, version control, and timely delivery. Therefore, in the software era, product managers create greater value through coordination and production management. (This also explains why the long-term value of software significantly increased with the advent of SaaS/cloud computing. It reduced the significant gap between coordination and production, greatly enhancing stickiness, and lowering long-term sales and implementation difficulties and costs for software companies.)
In the internet era (or the digital age), we have obtained a kind of "cheat code," which is the ability to reduce dimensions.
The characteristics of the internet era are quite notable. First, the marginal cost of information replication and distribution is low, and there is a massive user base. When there is a large user base, products tend to have platform attributes to some extent. This requires a focus on product ecology and considerations in decision-making. This situation was relatively rare in the past. Second, digitalization has greatly facilitated production in comparison to traditional offline models. This has led to rapid iterations, data-driven decision-making, and AB testing. Rapid iterations themselves have already reduced the cost of trial and error, thus lowering the entry barrier for product managers. Years of industry experience or business expertise are no longer necessary, nor is technical knowledge. The rapid distribution of information in the internet era allows product managers to iterate more quickly and continuously improve their products. Furthermore, due to the interactive nature of information, these iterations can generate a large amount of feedback data and information, which helps product managers make informed decisions. In many physical product fields, it usually takes several months or even years to validate whether the design and decisions made during the requirements phase were correct by releasing a hardware product, completing the entire path of requirements, production, and sales, and then receiving user feedback. In contrast, completing one iteration of an internet product may only take a few days, and it can collect feedback on a large scale. As a result, AB testing, a classic scientific tool, has become the most commonly used product tool in the internet era due to its ability to quickly generate results and its relatively scientific experimental methods. AB testing is used to compare the effects of two different versions of a single variable. Typically, A and B are made identical except for one variable, and the differences in user reactions to A and B are measured to determine which is better. AB testing enables larger-scale and faster iterations, making product design and decision-making more scientifically rational.
In addition to AB testing, there is now the concept of "personalization" in the internet era, where information shown to each user may differ based on their preferences. This further improves the efficiency of iterations and information distribution. Traditional offline giants like Walmart in the retail industry cannot obtain as much user data or behavioral data as platforms like Taobao. In the past, Walmart's data mainly came from offline interviews, surveys, or user bills, and within limited space, it optimized sales efficiency through optimizing product selection, product placement, and fixed promotions. These tools, compared to traditional offline products, feel like having a cheat code and the ability to reduce dimensions. It's like "what eliminates you is not your competitors, but the era" or the feeling of "winning the world but losing to the times." It is disheartening that Zhang Jindong won the offline retail market for home appliances, won the battle against GOME and Suning, but ultimately lost to the times. These tools are still being applied, and with the rise of O2O and the rapid digitalization of offline businesses, they are being continuously applied in offline industries that traditionally had advantages in the offline space. A recent example is Tang Binshen, the founder of the popular beverage brand "Yuan Qi Forest," who initially started in the gaming industry and deeply understands the application of internet tools. He quickly applied these tools to enter the traditional offline-dominated beverage market.
The relationship between enterprises, users, and products is as follows:
Enterprises use products as a medium to engage in value exchange with users, with the aim of creating business value. Essentially, what is being exchanged is not just the product itself, but the various user values behind the product. In this process, the product serves as the medium for the exchange of user value.
This raises an important point regarding the definition of users. We need to understand that users are not individual persons, but a collection of needs. Traditionally, users are often seen as individual users. For example, in the case of WeChat, general statistics may show that it has 1.1 billion "users." However, if we remove all other functions of WeChat and only leave the communication feature, it may still have 1.1 billion users, but its commercial valuation may drop from $200 billion to $20 billion. This approach of defining users as individual persons is clearly not applicable to internet products. From the perspective of a product manager, users are not individual persons, but a collection of needs.
From this perspective, it is absurd for many investment banks and institutions to compare the value of companies based on the number of users or the value of users per unit time. Even if the same users are considered, or even the same value of user time, the underlying user needs represented by those users can be completely different. Many trading platforms may have low user engagement, but their value is still high because they directly reflect specific user needs. Simple comparisons of users or user time overlook the fact that these users can engage in similar business forms on the platform or the future expansion of those business forms, but this may not necessarily be the case in reality.
From the perspective of a collection of needs, an individual person can be a user for hundreds or thousands of products, or they can be a user for different products of the same company. For example, in the case of WeChat, if the user base for the communication feature is 1.1 billion, WeChat Pay has 300 million users, and official accounts have 500 million users, then considering needs, the user base of WeChat exceeds the general statistical figure of 1.1 billion. Another example is when a company claims to have 10 apps with over 100 million registered users each. Registered users are not the real users; what matters is whether they use those apps to fulfill specific needs. Therefore, from this perspective, having 10 apps with over 100 million registered users does not necessarily mean having 10 apps with over 1 billion users.
Product user value = new experience - old experience - replacement cost
In fact, this formula is not only applicable to Internet products, it is applicable to any product.
The user of the product manager is the enterprise first. Product managers exchange value with the business. Product managers can only realize the value exchange between enterprises and users through enterprises.
The Essence of an Enterprise
The essence of an enterprise can be summarized in two points: firstly, identifying market profit opportunities; secondly, achieving production efficiency higher than that of the market. There are three ways to discover market profit opportunities: insight, trial and error, and serendipity. The sustainability of an enterprise relies on its production efficiency surpassing that of the market.
The market incurs transaction costs, and enterprises emerge as a means to save on these transaction costs. For an enterprise to sustain itself, its internal organizational efficiency in production must be higher than the market's efficiency in providing the same products. Enterprises achieve this by employing authority as a means to allocate resources and organize production (providing goods or services) more effectively. The operation of an enterprise does not rely on democratic voting, nor does it operate as a free market. The advantage of an enterprise lies in authoritative decision-making from top to bottom. Even if an enterprise's culture encourages dissent and equal disputes, it is ultimately to obtain more authoritative conclusions.
Enterprises constantly convert the tacit knowledge accumulated by individual employees into explicit knowledge and transform it into shared knowledge within the organization. This process is a common path to innovation. By forming internal customs and systems, some individual tacit knowledge can also be converted into shared knowledge within the enterprise. Subsequent employees can utilize this knowledge by following established customs and systems. The more shared knowledge an enterprise accumulates, the higher its organizational efficiency becomes. While authoritative decision-making allows enterprises to save on transaction costs compared to the market, the hierarchical structure within the enterprise also incurs information loss between levels and individuals, which can be understood as organizational costs within the enterprise. (In addition to information loss, another significant organizational cost arises from opportunism.) These organizational costs restrict the boundaries of an enterprise. An enterprise cannot infinitely expand; its boundaries can only expand until the organizational costs resulting from the increase in internal hierarchies equal the transaction costs of the external market. Therefore, shared knowledge is the foundation of an enterprise's efficiency and core competitiveness.
However, there will always be some individual tacit knowledge that cannot become shared knowledge within the enterprise. Each departing employee takes away their own proprietary knowledge, and when a new employee replaces them, the shared knowledge regarding work content, personal skills, and preferences decreases, requiring a period of reintegration and accumulation. These are all losses for the enterprise. In particular, when key employees leave and take away their proprietary knowledge, the loss of enterprise knowledge can be significant, potentially resulting in a loss of core competitiveness.
Enterprises rely on authoritative decision-making implemented through hierarchical systems from top to bottom, and these decisions must surpass the average level of the market. Therefore, if the key positions within the enterprise possess a greater amount of specialized knowledge and shared knowledge than the market average, the enterprise will have a greater efficiency advantage. However, if the turnover rate of these key positions is high, and the value of specialized knowledge and shared knowledge is low or even below the market average, it becomes a tragedy for the enterprise.
Organizational Efficiency
What is an organization? It is a group of people with common goals, shared beliefs, shared knowledge, and operating mechanisms. An enterprise is one of the most common forms of an organization and can be seen as a specific example, with the implicit goal of making money. However, this can only be an implicit goal, as explicitly stating it can lead to misunderstandings from employees and the market, resulting in disastrous consequences. People need meaningful work, and having a grand explicit goal that aligns with societal interests is essential for a good enterprise to be sustainable. An organization that deceives or harms its users will undoubtedly have a management team and employees with generally poor conduct, and its internal culture and efficiency will suffer. Common goals, shared beliefs, shared knowledge, and operating mechanisms all influence the efficiency of an organization. These four factors are not isolated but interact with each other. Common goals and shared beliefs are difficult to change, with high costs involved. Therefore, an enterprise must establish appropriate goals and beliefs, and generally select like-minded individuals during the recruitment process. Mission (ultimate goal), vision (intermediate and long-term goals), and values (shared beliefs and preferences) are important because they affect efficiency. Enterprises with deficiencies in these aspects naturally lack a lever to improve efficiency compared to others. Operating mechanisms involve institutional design. First and foremost, well-designed incentive (and subsequently, constraint) systems are necessary for an enterprise's long-term development. Similar to how non-market economies are unlikely to outcompete market economies with more optimal incentive systems in the long run. If an organization has poor goals, outdated beliefs, and flawed operating mechanisms (incentive and constraint systems), it cannot garner genuine recognition from individuals. Consequently, it will experience long-term negative talent selection. As the quality of talent decreases and mobility increases, the accumulation of shared knowledge is hindered, resulting in low organizational efficiency and core competitiveness. In summary, for an enterprise to effectively utilize authority and shared knowledge to improve efficiency, it is essential to have corresponding common goals, shared beliefs, and operating mechanisms (incentives, constraints, etc.) that complement each other. Three factors determine organizational culture: first, the founder's personality traits; second, the authentic behaviors of senior managers; and third, employee socialization, which involves daily communication to employees and integration into the organizational culture through systems and daily work.
The "value" that occurs in a transaction is subjective.
Value arises from the subjective utility evaluation of individuals (users) engaging in the transaction. Utility refers to the extent to which a product satisfies a person's desires or needs, and can be understood as the benefits that the product brings to the user. The utility provided by a product to a user is generally not singular but a combination of utilities. Moreover, due to differences in user desires, beliefs, endowments, resources, preferences, and situational contexts, a product may have different combinations of utilities for different users or in different situations. Users make subjective judgments about value, and similarly, the value judgments made by enterprises are also subjective because ultimately, decisions are made by individuals within the organization, whether it be a single person or a group of people. Their subjective judgments and perceptions determine the value judgments of an enterprise, which is also part of what we commonly refer to as the "DNA" of a company.
Since it is a transaction, each party needs to ensure that they benefit from it. No one wants to engage in a loss-making business. The premise for users to choose a product is "utility - cost > 0," and this formula can be seen as another expression of "user value = new experience - old experience - switching costs."
Users will only choose a product if the utility provided by the product outweighs the costs they have to bear. Therefore, our products need to either enhance utility (for example, when various products tell you at the end of the year that they have collectively saved you x dollars/y minutes, it is to strengthen your perception of the product's value) or reduce costs (for example, simplifying product interactions to lower the barrier to product usage, allowing users unfamiliar with internet products to use the product).
Why do we need transactions?
During the exchange process, the total physical matter in the world does not increase, but the value perceived by individuals for the two products involved in the exchange completely changes. Their valuation of these two products increases, and thus the total value in the world increases. The products are transferred through the transaction to the hands of someone who can create more value. This is why transactions occur constantly in the world - because transactions create value. There is no equal exchange in the world; as long as there is no coercion or fraud, both parties subjectively judge that they will benefit in order to complete the transaction. If one party incurs a loss, they will not be willing to engage in the transaction. A product is a transaction, and as a product manager, it is important to help users create such exchanges. Product design should start with the end in mind, with the ultimate goal of designing for successful transactions. Therefore, the ultimate goal of a company should be to create transactions because transactions lead to users, which signifies value creation and the potential for profit. Discovering market opportunities means discovering opportunities to facilitate a transaction, to make users willing to pay a certain cost to buy your product. This cost could be monetary, time, physical effort, mental energy, or other forms of sacrifice.
What is utility?
Utility is the degree of satisfaction or fulfillment of desires. People satisfy their desires through the consumption of goods and services. There are two principles related to utility:
Law of Diminishing Marginal Utility: The more wealth a person possesses, the better, as indicated by a positive first derivative of the utility function. However, as wealth increases, the rate of increase in satisfaction diminishes, indicated by a negative second derivative of the utility function.
Principle of Maximum Utility: Under conditions of risk and uncertainty, individuals make decisions to maximize their expected utility rather than maximizing expected monetary value.
Maslow divided human needs into five hierarchical levels: physiological needs, safety needs, social needs, esteem needs, and self-actualization needs. The infinite nature of desires drives social progress, and each individual strives and struggles to fulfill their continuously arising and endless desires.
Examples of reducing transaction costs:
Standardization: Standardizing goods is a common method that greatly reduces transaction costs, particularly for transactions that are hindered by measurement and search costs. By transforming goods into standardized products, it reduces measurement costs and decreases decision-making and assurance costs associated with uncertainty. Emphasizing "certainty" in certain business areas is, in fact, an effective means of reducing various transaction costs through the analysis of transaction cost theory.
Popularization of smartphones: From an economic perspective, the cost of waiting in queues is high (in terms of time). However, the widespread use of smartphones has significantly changed this situation in many scenarios. The direct loss of waiting in queues is the waste of time, but the specific cost of wasting time needs to be compared to the opportunity cost anchored to that time. Nowadays, when waiting in a queue, people can use smartphones to read, watch videos, play games, communicate, and work. If users would spend the saved time doing the same activities, then queuing actually has no loss. The reduction in the cost of queuing due to the popularity of smartphones actually lowers the transaction costs associated with queuing, making certain new transactions (business opportunities) possible. Services like Didi Chuxing's queue function, HaiDiLao Hotpot, and HEYTEA benefit from the reduction in queue costs. Therefore, in a sense, businesses that prominently feature queues like HaiDiLao Hotpot and HEYTEA are heavy beneficiaries of smartphones.
"Lianjia Genuine Listings"
In real estate transactions, intermediaries often falsely label property information and prices in order to attract more customers. The uncertainty surrounding property listings significantly increases the transaction costs for consumers. For example, to identify genuine listings and determine their corresponding prices, users may need to visit multiple intermediaries, view properties multiple times, and engage in numerous communications. Lianjia and Beike's solution is to employ a large workforce to ensure the authenticity and effectiveness of property listings. They have dedicated offline personnel to establish and regularly maintain accurate information about real estate developments, investing nearly 600 million yuan in building a "property dictionary" system and providing a "hundred-fold compensation for fake listings" service guarantee.
In a sense, Lianjia and Beike's measures help users reduce many transaction costs in the process of selecting and purchasing properties, enabling transactions that were previously impossible. Of course, in this process, Lianjia has incurred significant costs and additional transaction costs to ensure the authenticity of property listings. These costs include establishing internal governance systems and teams, conducting on-site inspections and verification, and handling responsibilities and compensation in case of issues. These costs can be seen as implementation and safeguarding (rights, breaches, accidents, supervision, etc.) costs incurred to facilitate genuine property transactions.
Over time, consumers have realized that choosing Lianjia can greatly reduce their transaction costs. Based on rationality, consumers ultimately return to Lianjia. The savings in transaction costs gradually translate into Lianjia's reputation, which, in turn, helps Lianjia save a significant amount of customer acquisition costs. Branding and reputation, in a sense, represent substantial savings in transaction costs for both businesses and consumers.
Similarly, one major challenge in the early development of e-commerce was the issue of transaction security. Alipay, born out of the Taobao ecosystem, greatly reduced transaction costs by providing robust transaction security, which significantly promoted the growth of e-commerce.
Digitalization
In the past, the restaurant industry faced difficulties in obtaining investment in the capital market, primarily due to the challenge of verifying the authenticity of its revenue. The entire transaction chain, from upstream procurement and wage settlement to downstream consumer payments, often involved offline cash transactions, making it extremely difficult and costly for investors to verify, supervise, and safeguard their rights. However, with the digitalization of transactions and payments, every income generated by restaurants becomes traceable and verifiable. For shareholders, the transaction costs of confirming the authenticity of performance are significantly reduced, leading to subsequent waves of financing and initial public offerings (IPOs) in the restaurant industry.
The process of digitalization in the restaurant industry is ongoing. The introduction of restaurant empowerment tools like Er Wei Huo enables online and data-driven processes, including online ordering and customer profiling. This allows restaurants to analyze which dishes are more popular and even identify target customers. Restaurant managers can make more convenient and informed decisions as a result. Compared to the pre-digitalization era, where designing a research mechanism and conducting extensive user surveys were necessary to draw conclusions based on offline statistical data, digitalization significantly saves substantial transaction costs.
Human decision-making is inherently irrational.
Decision-making refers to the process of collecting and processing information, utilizing tools and methods to analyze, calculate, and make judgments, and arriving at conclusions. However, human beings have limited energy and capabilities, and there are inherent limitations, biases, and uncertainties in the various stages of information acquisition, processing, analysis, and judgment. These limitations and biases can be observed in several aspects.
Firstly, there are limitations in information acquisition. For example, the search for information is constrained by costs. Acquiring more comprehensive information often requires higher costs, and the pursuit of absolute comprehensive information may have infinitely high costs. Individuals are also subject to cognitive biases, selectively obtaining and interpreting information, leading to non-objective and irrational judgments. Information overload, where non-essential information becomes excessive, can complicate decision-making. Third parties may intentionally or unintentionally mislead individuals through the processing and interpretation of information, deviating from objective facts.
Secondly, there are limitations in information processing. The human brain has limited computational capacity, and memory can be subject to biases. Human cognition also has its flaws, and relying on instinctive algorithms and heuristic algorithms can lead to various biases.
Furthermore, individual differences arise from endowment preferences. Differences in endowments, resources, preferences, contexts, desires, emotions, beliefs, and more can lead to individual differences in utility and value judgments, as well as differences and biases in assessing the needs and attitudes of others. Environmental uncertainties can also contribute to decision-making biases.
The complexity of various relationships and the ever-changing environment, coupled with the inherent uncertainties, can also lead to judgment biases. The limitations of human capabilities and the uncertainties of external factors mentioned above all contribute to irrational decision-making.
Overall, human decision-making is intrinsically irrational. Limited information acquisition and processing capabilities, coupled with individual differences and environmental uncertainties, contribute to non-rational decision-making.
Decision-making is synonymous with choice.
It involves selecting the best option among multiple viable alternatives. There can be conflicts between the interests of users and businesses. Products that are biased towards one side are not sustainable. As internet products grow and become platforms, they involve the interests of numerous third parties in the product ecosystem, making conflicts even more complex. Even within the same group of users, there can be conflicting demands. How can we make choices that satisfy them? These are the questions we must answer. The core of a product manager's work is ultimately about balancing these factors.
The goal of decision-making: Maximizing value
User value = New experience - Old experience - Switching costs. Product managers can use this formula to guide their decision-making. Product managers should seek to maximize new experiences by introducing new elements into existing production or lifestyle methods. If effectively applied, this can create a significant amount of new value, which is the essence of innovation. New elements are not limited to new technologies; they also include new user groups (such as products targeting third or fourth-tier users), new channels (such as public accounts, mini-programs, TikTok), new methods (such as A/B testing, product-driven approaches, data centers, etc.), and new tools (such as productivity tools used in work, iPhones, DingTalk, Wikipedia, Google, etc., which can create better new experiences). The influence of new elements can be cumulative. For example, after the introduction of the new method of "assembly line," the efficiency of car production greatly increased, leading to a decrease in car prices. Users' price sensitivity follows a pyramid distribution, with a larger user base as we move towards the bottom. The introduction of the "assembly line" as a new element significantly increased the number of car users. This wave of "car popularization" subsequently became a new element, making business models like Walmart in suburban areas possible (a significant portion of the prices of goods in downtown department stores is rent, while rent is cheaper in suburban areas, resulting in correspondingly cheaper goods in suburban Walmart stores, but this model was not feasible before car popularization). Businesses can provide users with better cost-effective products by employing various cost reduction methods, thereby creating a better new experience. New experiences are not limited to the combination of new and old elements but can also be created through the combination of existing elements in new ways.
Product managers should minimize the old experience.
The old experience refers to historical experiences that have already occurred or experiences with other products. Product managers do not have the ability to change the old experience. Therefore, product managers minimize the user's old experience by selecting specific user scenarios and reference points. Users are not individuals but a collection of needs. Needs can be infinitely subdivided from various perspectives. Minimizing the old experience essentially means selecting users who have the worst old experience with the substitute product.
One extreme case is when a product is targeted at "perfect new users" in the entire industry. These new users have not used similar competing products before, so their old experience with similar products is zero. Finding such new scenarios and new users provides the highest cost-effectiveness. In this case, even if your product experience is worse than the competitors, it doesn't matter because the difference between the old and new experiences is too significant.
For example, let's say during the competition between search engines A and B in the early days, A gained 2 million new users in a month. Among them, 1 million had used B or other search engines before, while the other 1 million had never used a search engine, but only the latter are considered "perfect new users." The performance and financial reports of these two types of new users for the company would show the same growth of 1 million users or increased transaction amount. However, the user value created by the product for these two types of users would be vastly different.
For new users who have used other search engines, the perceived difference between the new and old experiences is limited (in a highly competitive industry, the technology and products of competitors generally gradually converge, and the gap is not particularly significant unless it is in the early stages of applying new technologies). Their level of identification with Company A's product and brand would not be significantly higher.
On the other hand, the "perfect new users" experience a particularly large difference between the new and old experiences. They are often grateful and have a high level of identification with the product and the company's brand. They have a higher probability of becoming loyal users and actively spreading word-of-mouth. They also have a high likelihood of trusting and accepting new products from the company in the future. They are an important source of the company's brand value and long-term market competitiveness. Moreover, once someone becomes a "perfect new user" of search engine A, their perception of user value when they have the opportunity to use search engine B is based on the old experience of search engine A. For most people, it is difficult to perceive the difference between the new and old experiences in everyday simple search applications. Therefore, it becomes challenging for these new users to switch to another search engine. A search engine can also make targeted optimizations in various product details, making users perceive a significantly better experience with A when searching for certain keywords compared to B.
Another important impact is that the understanding of what a search engine is among the general public is market-driven and does not necessarily adhere to engineer standards or media expert standards. If the general public first uses A and experiences a series of vertical searches and product experience optimizations, and establishes the standard concept of a search engine based on A, when they later use B, they will only perceive B as a poor search engine and feel that everything about it is inferior.
One method that the concept of "perfect new users" brings to product development paths is that in the early stages of a completely new type of product, it may not only be limited to being a pioneer or innovator. Even imitators or latecomers have opportunities. Once the user value of the product is verified (without pursuing major versions and perfect features), market penetration should be rapidly increased so that all "perfect new users" experience becomes old experience. After that, it becomes difficult for competitors to grab market share because they will face the problem of making the "difference between new and old experiences" greater than the "switching costs."
A colleague once raised a product direction decision issue. He found a potential opportunity in a new direction but couldn't leverage the existing mature and advantageous business. The company's resources and energy were limited. Should he choose to expand the business around the mature advantage or choose the new direction and new product? This question can be explained using the theory of "new experience - old experience." If there is a significant potential demand and a new element (whether it reduces certain costs or improves certain utilities) that indicates future market growth, then it doesn't matter if the company has an advantage or not. As long as they take action, being the first to enter the market becomes the biggest advantage, and they can turn themselves into the old experience. Another extreme case is a monopoly. Users have no other choices, which means the old experience is zero. Even if everyone complains about the product being difficult to use, they will still use it. Monopoly does not only refer to exclusive or oligopoly market shares (for the sake of public understanding, I still use the pseudo-monopoly definition based on market share here, but those who have studied economics would understand that true monopolies only exist with compulsory access restrictions in addition to monopoly behavior). Because products have situational characteristics, in any scenario where users have no choice, a local monopoly is formed, creating a situation where the old experience is zero.
For example, when you have the option to choose between Coca-Cola and Pepsi on a store shelf, the difference in experience is psychological. However, when a gas station convenience store or a chain restaurant only sells Pepsi and not Coca-Cola, a local monopoly is formed. At this point, you can only choose to drink Pepsi or not to drink any cola, and the difference in user value is significant, making it difficult for users to refuse.
Product managers should minimize switching costs.
The most common switching costs include cognitive costs, acquisition costs, usage costs, and, broadly speaking, price and transaction costs. Generally, product managers either reduce the switching costs for their users or increase the churn costs for their competitors (which is equivalent to increasing the switching costs for the competitors). Cognitive costs include category awareness costs (e.g., understanding touchscreen phones), brand awareness costs (e.g., knowing Apple, Huawei, Xiaomi), reputation awareness costs (e.g., word-of-mouth evaluation), and more. Acquisition costs include channel acquisition costs (e.g., public accounts, mini-programs, apps, QR codes), download costs (e.g., reducing the size of the installation package), and so on. One extreme example is bundling installation, which significantly reduces switching costs but is still influenced by the difference in the old and new experiences (if the product is too bad and has a negative experience relative to the market average, users will still leave). Interaction and visual costs belong to usage costs. The simpler and more user-friendly the product is, the lower the usage costs. The more it follows the habits of existing users, the lower the usage costs. In extreme cases, some products directly replicate the industry's existing interactions, resulting in almost zero usage costs. For example, some products improve over time as users continue to use them (e.g., personalized recommendation products), which increases the cost for users to switch to other products.
Common decision-making methods and pitfalls
Data-driven decision-making
Data is the most powerful tool of this era. The value of data for product development is generally the lowest-cost tool for making correct decisions and achieving consensus. Strategies or designs in life are often determined beforehand (based on reasoning), but with A/B testing, we can choose the validated and better strategies after the fact. For suitable types of problems, conducting A/B testing is like peeking at the answers before solving the problem. It is the "cheating" weapon of product managers. However, there are still types of problems, especially open-ended questions and additional questions, that are not suitable for A/B testing.
Online products with a large number of controlled experiments have low cost and high controllability, making them suitable for A/B testing. However, for products with significant offline components, the usability of A/B testing is low, relying more on the deep thinking, accurate judgment, and trade-off capabilities of product managers, requiring experienced product managers to take responsibility. Furthermore, there are even more challenging scenarios for conducting A/B testing, such as hardware products like smartphones that have almost yearly iterations. Conducting A/B testing for such products is difficult due to the high overall costs.
Even for products suitable for A/B testing, we should remain vigilant. On the surface, data-driven decision-making may seem easy even for elementary school students, but data itself cannot explain problems or draw conclusions. It requires subjective analysis and judgment based on personal experience and knowledge. Humans are inherently subjective, and combined with the limitations of modeling and the uncertainty of information, it is challenging for people to always make the most correct and rational judgments and decisions based on data.
There are many cases that demonstrate the limitations of data-driven decision-making. For example, in the early stages of exploring blue ocean businesses, excessive emphasis on data-driven decision-making can actually slow down organizational efficiency. Another example is when there is insufficient basic data or when the costs of data acquisition and utilization are too high, emphasizing data-driven decision-making becomes unrealistic.
Logical decision-making
Behavioral science research has concluded that approximately 5% of a person's daily behavior is non-habitual, while the remaining 95% of behavior stems from habits. This essentially means that our lives are determined by habits rather than logic. We may think we are rational, we may think that our actions are logical and reasonable. But in reality, most of our daily behaviors are the result of hidden motives that we ourselves are unaware of. Rationality refers to prioritizing logical thinking, knowledge, and reasoning to make decisions and maximize expected benefits when conditions are suitable (rationality is not always superior to instinct and habit), rather than being driven by instincts and habits. Logical decision-making is also referred to as "reasoned decision-making," where conclusions are derived through logical deduction. However, it requires the counterpart to have a corresponding level of cognitive ability; otherwise, it will be like talking to a duck. To make someone understand and accept a truth, it must be achieved within their preferences and cognitive framework. If the other person does not have the corresponding preferences and cognitive framework, it would require a high cost to help them acquire it. Therefore, the cost of logical decision-making is much higher than that of data-driven decision-making. Product managers need to recognize that there are no objective facts in this world. What you perceive as facts are only facts in your own perception. Whether another person understands and accepts these facts is subject to the rigid constraints of their cognitive framework. You can only make them understand and accept what they consider as facts within their cognitive constraints. You can only design communication goals, content, and methods based on their cognitive framework.
Agenda setting
Product managers may not be able to influence the thoughts of their bosses or decision-makers directly, but they can influence what their bosses or decision-makers think. This is the primary source of "informal power" in the expert department.
Agenda setting is one of the important social functions and effects of mass communication. This theory suggests that mass media often cannot determine people's specific views on a particular event or opinion. However, they can effectively influence people's attention to certain facts and opinions, as well as the order in which they discuss them, by providing information and arranging relevant topics. The media provides the agenda to the public. The emphasis that mass media places on events and opinions is directly proportional to the attention given by the audience. This theory emphasizes that the audience will change their perception of the importance of things based on the agenda provided by the media and take action on events that the media considers important. (No wonder the Central Office, as the central hub of agenda setting, has significant influence.)
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