Why do merchants dare to advertise when the settlement rate in the Douyin women's apparel industrial belt is low?

Executive brief

Core judgment: Under the base case, settlement rates stabilize but have not seen a significant rebound. Current conditions do not support comprehensive mobilization for increased investment; instead, the focus should be on halting losses and rebuilding trust to replace scale expansion, deferring investment decisions until cash flow is restored.

Stance landscape: The vast majority of merchants and supply chain roles view improved settlement rates as an absolute prerequisite for increased investment. Even the few supporters only endorse a trust-based operating model, opposing blind additional investment under current conditions.

Maximum risk: Forcing investment based on traditional logic may trigger a negative ecological cycle involving cash flow rupture, deteriorating supply, and collapsing user experience, leading to accelerated clearance of industrial clusters rather than growth.

Turning-point signals: Closely monitor merchant closure rates and public sentiment regarding supplier payment arrears. Any signs of trust collapse indicate that the situation deviates from the base-case judgment, requiring an immediate halt to actions oriented toward transaction volume.

Recommended actions: Prioritize activating cost-reduction hedging mechanisms and launching special governance for abnormal returns to create a fair settlement environment for merchants, rather than directly pushing advertising placement.

This executive brief summarizes the report's conclusions; see corresponding chapters in the main text for the sources and basis of each judgment.

Distribution of key stakeholder stances: Settlement rates become the sole veto item for investment willingness.

The simulation centers on the proposition that garment sellers in industrial belts should increase advertising investment on Douyin E-commerce, covering 12 key stakeholders and 52 posts. Overall public opinion shows a highly consistent negative trend: 80.8% of posts oppose increased investment, while only 19.2% support it. The settlement rate has become the sole veto item for current willingness to invest; the vast majority of sellers and supply chain roles view "improvement in settlement rate" as an absolute prerequisite for increasing ad investment, rather than a negotiable optimization goal. Even platform-side roles and decision-makers explicitly acknowledged in the simulation that "if the settlement rate does not improve, forcing ad investment is killing the goose that lays the golden eggs," providing no substantive endorsement for increasing investment under current conditions. This consensus stems not from a denial of advertising value, but from survival rationality under cash flow rupture risks—when return rates are high, payment cycles are lengthened, and inventory backlog is severe, additional investment is seen as exacerbating losses rather than leveraging growth. Notably, the minority supportive voices do not unconditionally endorse increased investment; instead, they attach prerequisites such as "solving the settlement issue first" or "shifting to trust-based operations," which essentially remain critical responses to the status quo. Therefore, the core characteristic of the current stance distribution is not "opposition between support and dissent," but "all proposals for increased investment are systematically shelved until the settlement rate is resolved." (Source: simulation)

Garment sellers in industrial belts constitute the main body of the opposition camp, with highly unified stances and strong emotions. Sellers from Shahe and the Pearl River Delta, represented by Lao He, Lin Tao, and A Wen (Guangzhou), repeatedly emphasized that "the math doesn't work out" and "investing is like burning paper money," attributing low settlement rates to soaring return rates caused by platform shipping insurance and the seven-day no-reason return policy. They generally believe that under the triple squeeze of slow payments, high inventory, and thin profits, any new advertising expenditure is a fatal drain on cash flow. In the simulation, some sellers stated directly, "If the settlement rate does not improve, I will not spend one more cent on ads," reflecting that this group has completely tied investment decisions to settlement performance. (Source: simulation)

Supplier factories, as the upstream link in the industry chain, hold more radical stances than sellers. They not only oppose sellers' increased investment but also direct their criticism at the collapse of credit across the entire chain. Supplier roles in the simulation repeatedly pointed out, "Sellers owe Payment yet call for traffic investment; money is squeezed from our payment terms," and questioned, "If the settlement rate doesn't go up, who dares to supply goods again?" This indicates that the logic opposing increased investment has extended from individual seller operations to supply chain stability—if terminal sellers lose solvency due to low settlement rates, upstream factories face bad debt risks, and encouraging investment at this point is akin to amplifying systemic default probabilities. (Source: simulation)

Douyin E-commerce and decision-makers, although on the platform side, did not play the role of "pushing for increased investment" in the simulation; instead, they became co-confirmers of the "postponing increased investment" stance. Roles modeled after Douyin E-commerce explicitly stated, "If the settlement rate does not improve, forcing ad investment is killing the goose that lays the golden eggs," and acknowledged the boosting effect of the shipping insurance mechanism on return rates; decision-maker roles also admitted, "If the settlement mechanism does not improve, I will not force any seller to increase investment." Both sides decomposed the root causes into three factors: impulse consumption, insufficient quality control, and style homogenization, emphasizing the need for collaborative governance by sellers and platforms rather than unilaterally demanding sellers to increase investment. This posture of self-restraint reflects the platform's clear awareness of the current ecological health and further solidifies the public opinion tone of "fix the root cause first, then talk about investment." (Source: simulation)

Minority supportive voices mainly come from simulation roles modeled after Jili Yu Ma, MARIUS, and Mu'an, but their "support" comes with strict conditional limits. These roles do not advocate Additional investment (additional investment) under the existing model; instead, through their own practices, they demonstrate that when sellers shift towards content trust building, supply chain efficiency improvement, or differentiated style creation, return rates become controllable, settlement rates stabilize, and advertising investment achieves positive ROI. The role modeled after Jili Yu Ma emphasized in the simulation, "It relies on supply chain efficiency and not doubling markups, not on throwing money to buy traffic"; the role modeled after MARIUS pointed out, "By using principal trust and supply chain efficiency, return rates are significantly controllable." In other words, their "support" is In substance (essentially) an endorsement of "another operational paradigm," rather than an affirmation of increased investment behavior under current Dilemma (difficulties). This subtle difference is crucial—it indicates that the market is not rejecting advertising itself, but rejecting ineffective investment before the settlement rate is repaired. (Source: simulation)

Key divergences and uncertainties: Attribution disputes and breakout variables

The simulation reveals sharp disagreements among stakeholders regarding liability for low settlement rates, and the fact that several key variables remain undetermined directly impacts the feasibility of any breakthrough path.

Attribution Disagreement: The tug-of-war between platform mechanisms and merchant fundamentals. Simulation statistics show that 80.8% of posts oppose increasing investment at the current settlement rate, with the core issue being a failure to reach consensus on responsibility attribution. Merchants from industrial belts and their supplier camps point fingers directly at platform rules. Stakeholders modeled after Lao He and A Wen (Changshu) repeatedly emphasized that the combination of shipping insurance and the '7-day no-reason return' policy has led consumers to 'try on clothes at zero cost,' which is the direct driver behind the surge in return rates compared to pre-pandemic levels; they argue that asking merchants to increase investment without changing these mechanisms is 'avoiding the main issue.' (Source: simulation) The platform side and decision-makers, however, insist on a multi-causal explanation. While acknowledging that shipping insurance raises return thresholds, they also point out that impulse buying in live streams, shortcomings in merchants' own quality control, and homogenization of styles leading to price comparisons are the structural causes. Decision-makers explicitly stated in the simulation that under the same shipping insurance environment, merchants such as MARIUS, Jili & Ma have achieved controllable return rates through building content trust, proving that high return rates are not entirely a mechanism issue. (Source: simulation) Verified online data corroborates the complexity of this disagreement: online women's clothing return rates have indeed risen from 30% in 2019 to 65%-80% in 2025, reaching as high as 80%-90% in live e-commerce scenarios. However, studies also indicate that uneven product quality, excessive marketing, and loopholes in platform rules are all contributing factors, making single-cause attribution untenable. (Source: verified online, url: user.guancha.cn)

Key Uncertainty 1: Whether the shipping insurance mechanism can achieve 'fine-tuned balance'. Current shipping insurance faces a dilemma where 'not offering it means losing traffic, but offering it drains cash flow.' Its future trajectory depends on whether the platform can introduce differentiated solutions. Signals to watch: Observe whether the platform introduces tiered shipping insurance fee policies based on merchant return rates, category characteristics, or user credit scores, rather than maintaining a 'one-size-fits-all' model. If optimization remains merely verbal promises without concrete product iterations, merchant trust will be difficult to restore.

Key Uncertainty 2: The replicability of the 'trust-based operation' paradigm in industrial belts. In the simulation, stakeholders modeled after Jili & Ma and MARIUS demonstrated paths to reducing return rates through owner IPs and supply chain efficiency. However, it remains questionable whether this model is applicable to merchants in industrial belts like Guangzhou Shahe, which primarily rely on small profits and quick turnover and copying/following popular styles. Signals to watch: Observe whether there are successful cases of a second batch of non-top-tier industrial belt merchants successfully completing the 'content + quality control' transformation, and whether the platform provides low-barrier content tools or supply chain empowerment services specifically for SMEs, rather than just setting up a few benchmarks.

Key Uncertainty 3: The speed of linked repair between settlement cycles and cash flow. Supplier factory roles in the simulation bluntly stated that merchants delay payments due to slow platform settlements, causing the entire chain to be stuck. Even if return rates drop, if payment terms do not shorten accordingly, merchants will still lack the surplus to invest in advertising. Signals to watch: Pay attention to whether the platform dynamically links settlement cycles to merchant operational health indicators (such as return rates and positive review rates), and launches fast-payment channels for high-quality merchants, rather than only adjusting front-end traffic distribution.

Key Uncertainty 4: The governance boundaries of cross-platform price comparison behavior. The simulation frequently mentioned that consumers' 'buy three, return two' behavior is driven by arbitrage activities fueled by real-time cross-platform price comparisons, but the platforms' ability to identify and intervene in such behaviors remains unclear. Signals to watch: Observe whether the platforms launch risk control models targeting abnormal price-comparison returns, or transparently display price differences for the same products across different channels, thereby reducing speculative returns caused by information asymmetry.

Risk warning: Forced recommendation may trigger a negative ecological cycle

In the absence of a structural improvement in settlement rates, if the platform or service providers continue to aggressively push industrial belt women's apparel merchants to increase advertising spending based on traditional logic, it is highly likely to trigger an ecological negative cycle of 'cash flow rupture—supply deterioration—experience collapse'. This risk is not a theoretical deduction but a realistic warning based on the current fragile state of the industry chain. Simulation statistics show that 80.8% of posts explicitly oppose increasing investment under the current conditions, with the core concern being that additional spending would accelerate rather than alleviate operational crises. (Source: simulation)

Merchant-side cash flow exhaustion and supply chain trust collapse. Industrial belt women's apparel merchants are generally in a tight balance characterized by thin margins, high return rates, and long payment cycles. Simulation characters modeled after Lao He and A Wen (Guangzhou) repeatedly emphasized that high return rates combined with extended platform settlement periods have led to tight or even broken cash flows; supplier factory roles stated more bluntly that 'payment arrears' are common, and the entire chain is stuck. Pushing advertising spending in this context is equivalent to requiring merchants to continue transfusing blood to the traffic end while they are already bleeding. Verified online materials indicate that since 2024, dozens of women's apparel online stores with over a million followers have closed or stopped launching new products, mostly pointing to 'thin profits, high returns, and high costs'. Some top stores, such as 'Shaonv Kaila', were exposed for absconding with funds and owing payments to hundreds of suppliers (this data could not be traced to original sources). These cases show that when settlement rates cannot support basic reproduction, additional spending will not only fail to leverage growth but also become the last straw that crushes merchants, further destroying upstream factories' trust in e-commerce channels. (Source: verified online, cbndata.com)

Backlash from consumer experience and erosion of the platform's traffic foundation. Aggressive promotion may also exacerbate the vicious cycle where 'bad money drives out good' in terms of user experience. In the simulation, consumer roles explicitly expressed their strongest dislike for 'merchants using money to bombard ads for impulse purchases, resulting in poor clothing quality and troublesome returns'; if merchants compress quality control or raise markups to cover advertising costs, it will directly stimulate higher return and negative review rates. Simulation characters modeled after Douyin Ecommerce also admitted that although shipping insurance lowers the decision threshold, it has pushed return rates to high levels, with gains being offset by losses. Verified online information points out that high return rates in women's apparel e-commerce have become an industry-wide problem, with some stores seeing return rates exceeding 80%, and cross-platform price comparison behaviors intensifying speculative returns (Source: verified online, lanjinger.com). If GMV-oriented encouragement of spending continues at this time, it is no different from exchanging long-term user trust for short-term transaction volume, ultimately damaging the platform's own traffic foundation and ecological sustainability.

Resource misalignment risk due to the non-replicability of benchmark paths. Although simulation characters modeled after Ji Li Yu Ma and MARIUS demonstrated paths to low returns and stable settlements through trust building and supply chain efficiency, their success heavily relies on scarce capabilities such as founder IP, flexible supply chains, or differentiated styles. Decision-makers in the simulation also acknowledged that these merchants are exceptions rather than the rule. If the platform packages such individual cases as universal solutions and uses them to drive increased spending across all merchants, it Very easy leads to resource misallocation: a large number of SMEs lacking internal strength will blindly follow suit, failing to replicate the low-return model while worsening losses due to advertising expenditures. This 'survivorship bias'-driven spending mobilization will not only fail to improve overall settlement rates but will also amplify systemic risks, accelerating the clearance of the already fragile industrial belt ecosystem. (Source: simulation)

Recommended actions: Scenario-based action paths based on the degree of settlement rate recovery

Regarding the proposition that 'apparel merchants in industrial belts should increase advertising investment on Douyin E-commerce,' given the 80.8% opposition in the Simulation and the settlement rate acting as the sole veto item, recommended actions must abandon a 'one-size-fits-all' push for increased spending and instead adopt scenario-based action paths contingent on the degree of settlement rate recovery. The following recommendations are formulated based on publicly disclosed platform support measures from 2025 (Source: verified online, url: guancha.cn) and consensus among stakeholders in the Simulation, to be executed under three scenarios.

Scenario 1: Base Case (Settlement rate stabilizes but has not significantly recovered)

This scenario corresponds to the initial phase of platform governance measures taking effect, where return rates stop rising and promotion fee refund policies take hold, but merchant cash flow remains tight. The core objective is stopping losses and rebuilding trust, rather than scaling up.

1. Fully activate the 'cost reduction offset' mechanism, replacing direct investment increases. The platform should ensure that the 'automatic refund of promotion fees' and 'reduced shipping insurance costs' introduced in 2025 cover the apparel category in industrial belts without blind spots. Verified online data shows the platform has explicitly committed to automatically refunding promotion orders that meet conditions and result in full refunds, and reducing shipping insurance costs by 10%-40% for eligible merchants (Source: verified online, url: pai.com.cn). In the current stage, these two policies should be transparently calculated for merchants as 'quasi-advertising subsidies,' allowing them to perceive that 'advertising risks are covered,' rather than simply demanding additional budgets.
2. Establish a 'settlement rate - advertising' linked whitelist. Stakeholders modeled after Douyin E-commerce in the Simulation explicitly stated, 'If the settlement rate does not improve, forcing advertising expansion is killing the goose that lays the golden eggs' (Source: simulation). It is recommended that the platform side set dynamic thresholds: only grant incremental advertising rights to merchants whose settlement rate improved month-on-month month-on-month over the past 30 days or whose return rate is below the industry average; for non-compliant merchants, forcibly guide them to use free content tools or commission-free shelf traffic, avoiding ineffective burning of funds that exacerbates losses.
3. Signals to watch: Focus on monitoring the actual receipt rate of promotion fee refunds and the return rate trend curve after shipping insurance cost reductions. If refunds are delayed or return rates do not converge after cost reductions, it indicates that basic experience issues remain unresolved, and any advertising incentives under this scenario should be suspended immediately.

Scenario 2: Best Case (Structural improvement in settlement rate, enhanced operational health)

The trigger condition for this scenario is: industrial belt merchants restore the settlement rate to a sustainable level through quality upgrades or differentiated transformation, and replicable low-return samples appear. The core objective is precisely amplifying high-quality supply to achieve positive ROI.

1. Targeted support for the advertising leverage of 'trust-based' benchmarks. Stakeholders modeled after Jili Yu Ma and MARIUS in the Simulation proved that 'founder trust + supply chain efficiency' can reduce return rates (Source: simulation). Under this scenario, advertising investment should shift from 'buying traffic' to 'buying audience assets.' It is recommended that the platform provide combined advertising packages of 'content seeding + shelf repurchase' for such merchants with validated low-return models, and match them with algorithm-side preferential mechanisms for high-quality content (Source: verified online, url: guancha.cn), making their advertising ROI significantly higher than pure bidding merchants, thereby creating a demonstration effect.
2. Open a 'operational health' for traffic exchange channel. For merchants whose settlement rate consistently outperforms industry levels, allow them to exchange metrics such as 'positive review rate' and 'repurchase rate' for discounts on paid traffic. This responds to the decision-maker's logic proposed in the Simulation of 'breaking the deadlock before discussing growth' (Source: simulation), and concretizes the platform's 2025 traffic mechanism of 'tilting toward high-quality content and products' into an executable incentive tool.
3. Signals to watch: Observe whether the advertising ROI of benchmark merchants remains continuously positive and whether their model is effectively imitated by other merchants in the same industrial belt. If only individual top-tier merchants benefit while mid-tier merchants cannot follow, caution against resource misallocation risks and adjust support strategies in time.

Scenario 3: Worst Case (Continued deterioration or stagnation in settlement rate recovery)

If platform governance measures fail to curb return rates, or if product quality control and homogenization issues on the merchant side see no substantial improvement, the settlement rate continues to bottom out. The core objective is circuit-breaking advertising to preserve ecological bottom lines.

1. Mandatory freezing of paid advertising entry points for high-risk merchants. When the settlement rate drops below the warning line, continuing to encourage advertising is equivalent to accelerating merchant death. At this point, the platform's commitment to the 'ecological sustainability' bottom line promised in the Simulation must be strictly enforced (Source: simulation), actively limiting the advertising consumption cap for high-return, low-settlement merchants, and guiding them instead into a green channel for free operations supported by the 'small merchant assistance fund' (Source: verified online, url: pai.com.cn), prioritizing survival issues.
2. Launch special governance for cross-platform price comparison and abnormal returns. The Simulation repeatedly mentioned that 'buy three, return two' is driven by cross-platform arbitrage (Source: simulation). Under this scenario, the platform needs to shift its governance focus from front-end traffic allocation to back-end risk control, launch identification models for abnormal price-comparison returns, and strictly handle malicious after-sales behavior, creating a fair settlement environment for merchants.
3. Signals to watch: Closely monitor merchant store closure rates and public opinion on supplier payment arrears. If signs of industrial belt trust collapse similar to those mentioned in materials appear (Note: The incident of 'Shaonv Kaila' owing 35 million yuan could not be traced to its original source and serves only as a reference for risk type), indicating the ecosystem has entered a negative cycle, all GMV-oriented operational actions must be stopped immediately, and a comprehensive transition to crisis intervention mode is required.

Materials and sources

Verified online sources

• Research on the Causes and Countermeasures of High Return Rates in Women's Wear E-commerce
• Women's wear e-commerce falls into a "return death spiral": When 7-day no-reason returns become mandatory, how to break this industry storm? - Guancha
• Multiple women's wear online stores with over 10 years of operation close successively; even Zhang Daying says "profits are thin" - Lanjing Finance
• 80% return rate, running away with millions in funds: Internet celebrity women's wear faces a "wave of bankruptcies" | CBNData
• Douyin E-commerce launches its most substantial merchant support plan in history, 9 measures to help merchants reduce costs and increase income
• Douyin E-commerce announces 2025 merchant support measures - E-commerce Post

Source materials

• cbndata.com
• user.guancha.cn