Business Model

[Core Idea] At key business touchpoints, using physical or symbolic rituals can interrupt users' original decision-making paths, create a sense of scarcity and belonging, and thereby effectively lock in high-intent users on the spot. [Logic Chain] To prevent potential customers from being diverted by other low-priced ancillary products → directly establish a new exclusive community at the event site → design ritual elements such as "co-founders" and "ribbon-cutting" ceremonies → give early users a special sense of identity → achieve a psychological shift from mere audience members to project co-builders → thereby increasing the conversion rate of high-ticket products or locking in subsequent private-domain traffic. [Failure Conditions] When the product itself lacks solid value and is purely packaged through form, ritual is perceived as a tactic to exploit users, triggering aversion; or when the audience is extremely rational tech enthusiasts, excessive formalism can undermine the sense of professionalism. [Related Fields] Marketing and traffic, communication and social interaction

Insight: The higher the price, the higher the client's decision cost. The sales process must proactively manage and lower client expectations, guiding them toward controllable certainty—otherwise, clients may hesitate and abandon the purchase.

Logic Chain: As pricing rises from low to high, clients stop paying for "possibilities" and start demanding "certainty." If the sales side fails to clearly define delivery boundaries, outcome scope, and service processes, clients will imagine various risks and choose the conservative option.

Failure Condition: When clients have extremely high authority trust or emotional attachment to the provider, they are willing to overlook details, and decision costs naturally decrease.

Related Domains: Marketing & Traffic, Product & Operations

Viewpoint: The higher the price of a product, the higher the customer’s expectations, and the stricter the requirement for "certainty" in delivery outcomes. If the delivery structure lacks sufficient certainty, even occasional deals may close, but repeat purchases and referrals will be hard to generate.

Logic chain: High prices force customers to bear higher decision costs, leading them to repeatedly weigh "whether the expected value can be guaranteed." If the delivery content is vague, the process is uncertain, or the outcome is uncontrollable, customers will hesitate to pay a high price with peace of mind. Post-purchase satisfaction will also be hard to secure, rendering word-of-mouth propagation ineffective.

Limiting condition: If the product is an extremely scarce experience-based or relationship-based service, where what customers buy is emotional value or relational connection, the demand for practical certainty naturally decreases, and this judgment weakens under such circumstances.

Related domains: Product and operations; marketing and traffic

Viewpoint: When a product moves from a knowledge-payment model to high-ticket enterprise needs, both the sales strategy and the sales cycle change significantly; a longer decision process is the basic rule.

Logic chain: The higher the transaction value, the greater the customer's decision cost, and the more internal stakeholders need to be coordinated — which naturally extends the sales cycle. You cannot apply the same lightweight-decision sales playbook used in C-side consumer sales; instead, you need to build a strategy and sales-script system tailored to long-cycle conversion.

When it fails: If the product solves an extremely urgent and must-have business need, the decision chain can shorten considerably, but high-ticket purchases will always be slower than low-value consumer purchases.

Related areas: Sales strategy, business model, customer decision-making.

Opinion

Product price increases (such as raising a community membership from a few thousand yuan to over ten thousand) cannot be done arbitrarily. You must create a new, high-density narrative so that users perceive this year’s offering as fundamentally different from last year’s, making them subconsciously accept the premium.

Logic Chain

Consumers won’t pay more for something identical to last year. A price increase requires a new “prefix”—for example, introducing content on how AI is being implemented, or showing users a new story of resource integration (such as bringing in industry heavyweights for joint development). When the narrative structure shifts and information density clearly increases, users automatically rationalize the price rise. Similarly, to leave room for lower-priced products, one must also explore upward into higher price bands.

Failure Condition

If the new narrative is just old content in new packaging—and users find the deliverable unchanged from the past—it can trigger serious reputational backlash. A price increase must be backed by tangible delivery upgrades or additional resource investment.

Related Fields

Business models; knowledge payment; marketing and traffic.

Viewpoint: Design tiered pricing (e.g., 12,800 / 50,000 / 150,000) and, for clearly high-intent customers, directly recommend the top tier. Use the high price as an anchor to steer customers toward the middle tier, thereby increasing the average order value.

Logic chain: First introduce the high-priced product to establish a reference point → when customers find it too expensive, shift to the next-highest tier → the next-highest tier appears “more reasonable” and closes the deal → ultimately, most customers land on the 50,000 tier, a small number accept 150,000, and the low 12,800 threshold serves to attract and convert leads.

Failure conditions: If the value differences between tiers are unclear, delivery commitments are vague, or the salesperson themselves does not believe in the high price, the anchoring effect fails.

Related fields: Business model, marketing and traffic.

Viewpoint: AI products need to remain non-standardized and scarce, avoiding homogenization that dilutes value.

Logic Chain: Standardization leads to homogeneous competition and declining value; while fewer, refined personalized products sustain higher pricing and customer loyalty, forming competitive barriers.

Failure Conditions: The market accepts standardized products, or the cost of non-standardization becomes unsustainably high.

Related Areas: Product & Operations, Business Models

Key Point: When packaging professional capabilities into marketable products, one should start from a customer acquisition angle to match potential customers' pain points, and design the product funnel from an overall business perspective, clearly identifying the acquisition portfolio and the profit portfolio.

Logic Chain: A product is easy to sell only when it hits customers' real needs, so it is necessary to first define the customer profile and pain points. Systematic design breaks the single-point mindset by planning an acquisition portfolio (traffic-generating products) and a profit portfolio (revenue-generating products), and by identifying cost and profit points at each stage. This optimizes overall profit margins and delivery costs, making the product scalable.

Failure Conditions: When customers already have a market-validated standard product and smooth sales channels, the return on investment from redesign may not be worthwhile. For fully innovative products lacking market benchmarks, the effectiveness of systematic design is reduced.

Related Areas: Product and Operations

Viewpoint The essence of a franchise business is no different from buying stocks: the franchisee only contributes money and local connections, while the brand handles all operations. Don’t mistake it for running your own independent business. A store earning over 10,000 yuan per month is already a very good one—the upside is extremely limited.

Logic Chain The brand controls supply chain, operations, and marketing, leaving franchisees without independent management capability. Profits are eroded by the brand’s revenue share, raw material costs, and operating expenses. Therefore, the return ceiling for a single-store model is low and should be assessed based on return on investment rather than “entrepreneurial” expectations.

When It Fails In rare cases, a strong brand paired with a franchisee possessing exceptional local resources or operational ability may break through the general ceiling. But these are exceptions and cannot serve as a universal expectation.

Related Fields Entrepreneurship, business models, consumption and lifestyle.

【Viewpoint】 The essence of a franchise business is the same as buying stocks: the franchisee only provides capital and local connections, while the brand handles all operations. Don't mistake it for running your own independent business—recognize its investment nature and avoid unrealistic expectations.

【Logic Chain】 In the franchise model, the brand controls core areas such as supply chain, operations, and marketing. The franchisee's only controllable variables are capital and local resources. The returns are essentially compensation for capital and resource input, not a reward for operational capability.

【Failure Conditions】 If the franchisor only licenses its brand while the franchisee makes all operational decisions independently, or if the franchisee possesses the ability to transform offline operations, then the arrangement partially diverges from its investment nature.

【Related Fields】 Business models, franchise business, investment nature, cognitive risk

【Viewpoint】Franchising is essentially a form of financial investment, similar to "trading stocks"; it should not be treated as running a physical business of your own.

【Logic Chain】Franchisees purchase the right to use a brand and the franchisor's proven model, without owning the core products, supply chain, or brand equity. Their returns depend mainly on the franchisor's system capabilities and market conditions, which is no different in nature from investors making decisions based on external variables in the stock market.

【Invalidation Condition】If franchisees are deeply involved in localized operations, possess unique resources, or have strong bargaining power over the franchisor, allowing them to materially influence business outcomes, then the arrangement may be closer to physical business operation.

【Related Fields】Business models, franchise entrepreneurship, investment awareness.

Viewpoint: For a high-ticket B2B data service in the cold-start phase, you must first accumulate case studies you can share externally; case studies are the foundation for charging higher prices.

Logic chain: When brands purchase high-priced services, they look for proof from comparable customers; having no case studies signals risk and low credibility. Start with a low-priced basic tier and a small number of seed customers to generate implementation results, creating the demonstration effect of “already in use by brand X.” Only then do the group tier and customized tier have room for pricing negotiation.

Failure condition: If customers are willing to pay directly for exclusive data resources without seeing case studies, or if deals can be closed through senior relationships, the importance of case studies as a prerequisite declines.

Related fields: B2B sales trust, customer case study development, cold start.

Viewpoint: Subscription-based data services should be tiered according to customer size and depth of need, rather than using one product to sell to everyone.

Logic: Single-brand customers have smaller budgets and shorter decision chains. The basic tier can cover them with 12 monthly trend reports plus 1–2 ad hoc deep-dive insights; in China, there are roughly several hundred single-brand customers with budgets above RMB 25 million. Group customers have multiple sub-brands and plan their data budgets centrally, so they require bundled pricing; this corresponds to groups with budgets above RMB 100 million, and the number of such customers is smaller. Specialized deep data capability delivery has no comparable market price and must be negotiated separately. After tiering, the target customer count and delivery cost for each tier can be aligned.

Invalidation conditions: The tiered pricing will fail if customers do not accept that the basic tier excludes deep insights, or if group customers insist on purchasing separately by sub-brand.

Related areas: Product tiering, target customer segments, subscription-based data services.

Viewpoint: When selling data services to brand owners, a reasonable pricing range is for data service fees to account for 0.5%–1% of the brand’s marketing budget, and then work backward to define product tiers and customer thresholds.

Logic chain: Brand owners will treat data services as part of marketing costs; a fee accounting for 0.5%–1% of the marketing budget feels substantial enough without triggering a separate large procurement process for decision-support services. Working backward from this: a single brand with a budget of 25 million corresponds to a basic tier of 100,000–150,000, while a group with a budget above 100 million corresponds to a packaged tier of 500,000–800,000.

Failure conditions: If a brand owner still perceives the value of data services as merely “buying reports,” or if the company has already classified data services under IT budget rather than marketing budget, this ratio does not apply.

Related domains: B2B service pricing, marketing budget allocation, customer value assessment.

Viewpoint: For premium credit card institutions selling data services, the real moat is high-net-worth customer segment labels, complete real consumption transaction data, and cross-border consumption data.

Logic chain: Ordinary consulting firms can obtain survey and sample data, but they cannot obtain the full picture of actual consumption by certain high-net-worth groups. Brands especially need to see cross-border scenarios such as Chinese customers’ overseas luxury purchases and overseas customers’ domestic consumption. High-net-worth card users have strong loyalty and concentrated large-amount spending; the scarcer and more authentic these data are, the more willing brands are to pay for subscriptions.

Conditions under which the thesis fails: If data compliance regulation tightens, or if brands themselves can obtain equivalent transaction data through acquiring or payment channels, the differentiation advantage will be weakened.

Related areas: High-net-worth customer insights, cross-border consumption data, data compliance.

Viewpoint: The BD contact for external commercialization should be someone who understands the business, not someone who only understands technology or data.

Logic chain: People who understand the business can grasp customers' real needs and translate data capabilities into business value that customers can perceive. BD requires business language and business insight; a purely technical background tends to remain at the functional level.

Failure conditions: When the customer is a highly technical buyer, technical experts need to be deeply involved.

Related fields: Business models, BD contact, business understanding.

Viewpoint: The data department can commercialize by providing external data services. Securing orders first and then resolving compliance issues is a pragmatic way to enhance the department’s value.

Logic chain: External commercialization generates direct revenue, proves the data department’s value, and helps it gain higher organizational status (such as being upgraded to a Tier-1 department). Validating market demand before investing in compliance costs is more aligned with business cadence.

Failure conditions: In heavily regulated industries, acting first and remediating compliance later may expose the business to heavy fines or brand risk; this should be assessed in advance.

Related fields: Business models, data commercialization, organizational development.

Viewpoint: When a company’s financial results fall short, scaling back peripheral business lines is a normal business decision. It should be guided by business health rather than by an emotional insistence on preserving teams.

Logic chain: Under financial pressure, redundant headcount and investment in ineffective demand continue to drain resources. Scaling back, removing redundancy, and reducing ineffective investment can make the organization healthier and strengthen its long-term competitiveness.

Invalidation condition: If scaling back would harm core strategic capabilities or key talent, the trade-offs need to be weighed carefully.

Related areas: Business models, organizational change, business decision-making.

Position: For a data department to become a first-tier department and commercialize externally, it must own customer relationships and demonstrate value directly to brands/merchants, rather than being isolated by the existing business development system.

Logic chain: Data services require client understanding → intermediary channels do not understand data → message distortion → business negotiations are hindered → direct engagement → precise demonstration of value → cooperation advances.

Failure conditions: When the organization has strong channel-control policies, bypassing the intermediary system may trigger organizational conflict; in that case, internal coordination should come first.

Related areas: Organizational structure, commercialization, data department.

Viewpoint: For brand clients with large marketing budgets, data services can optimize marketing performance, and charging an annual fee ranging from several hundred thousand to over a million is reasonable. The key is to prove value, and compliance issues can be addressed after the order is secured.

Logic chain: Brands have marketing budgets and care about performance → data services provide quantifiable optimization → case studies prove ROI → clients trust and pay → compliance issues are progressively resolved during delivery.

Failure conditions: In heavily regulated sectors (such as core financial data) or when clients have strict internal compliance requirements, addressing compliance only after the fact creates legal and reputational risks.

Related areas: Data services, value demonstration, commercialization