China E-commerce Performance Analyst

Author: user_ryugdo

Business & operations

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Pricing options

Pay per useCN¥6.99 / task

Input example

Public example

Raw operating data (CSV/TSV text): date,sku,impressions,product_uv,pay_buyers,pay_orders,pay_amount,promotion_spend,promotion_pay_amount,refund_amount,unit_cost,platform_fee,shipping_cost,ending_inventory 2026-08-01,SKU-A,18600,820,41,44,3275.90,420.00,1360.00,98.00,31.00,112.50,176.00,560 2026-08-01,SKU-B,9200,430,12,13,955.20,260.00,410.00,76.00,28.00,35.80,52.00,95 2026-08-02,SKU-A,17900,790,38,40,3034.10,405.00,1285.00,120.00,31.00,105.20,160.00,522 2026-08-02,SKU-B,9700,455,10,11,796.00,275.00,360.00,0.00,28.00,29.60,44.00,85
Field dictionary and formula caliber: date = natural day, Beijing time; impressions = number of product exposures in the Pinduoduo merchant backend; product_uv = number of product visitors, deduplicated by platform; pay_buyers = number of paying buyers; pay_orders = number of paid orders; pay_amount = payment amount, CNY, including platform subsidy display caliber, which cannot be directly regarded as actual receipts by the merchant; promotion_spend = promotion cash consumption, CNY; promotion_ pay_amount = platform backend attribution payment amount, CNY, attribution window to be confirmed based on rules; refund_amount = refund amount registered on the day, CNY, may be reversed across payment days; unit_cost = single piece purchase cost, CNY; platform_fee = platform technical service fee that can be collected on the day, CNY; shipping_cost = merchant bears freight, CNY; ending_inventory = number of inventory items available for sale at the end of the day. A null value means missing and not equal to 0.
Domestic platform, store scope and statistical period: Pinduoduo; Mainland China; CNY; Asia/Shanghai; 2026-08-01 to 2026-08-31; SKU-A and SKU-B in the store. The example only shows part of the data, real operation should paste the complete cycle.
The goal of this analysis: Determine whether the payment amount and profit contribution pressure comes from traffic, payment conversion, promotion consumption, refunds, or SKU structure, and give priority actions for the next month.
Business background and restrictions (optional): Domestic spot merchants; the upper limit of the promotion budget for next month is 12,000 CNY; the goal is to increase contribution profits under the premise of controllable cash flow. The master commission, coupon merchant liability, freight insurance and taxes are not provided, so the complete net profit cannot be calculated.
Platform caliber, cost and delivery rule basis (optional): The data is exported from the merchant backend using the same caliber; the promoted product name and attribution window, the separation of platform subsidies and merchant discounts, the latest rates and settlement rules are not provided, and relevant conclusions must be marked as pending.
Compare to cycle or business goals (optional): The merchant's internal goals: the payment conversion rate is not less than 5.0%, and the promotion to production ratio is not less than 3.0; the goals are internal management thresholds and do not represent platform or industry benchmarks.
Text model (optional, leave blank to use GPT-5.6 Sol): openai/gpt-5.6-sol

Instructions and workflow details

What to prepare

Audit data fields and metric definitions across Taobao/Tmall, Pinduoduo, JD, Douyin, Kuaishou and Xiaohongshu. Analyze traffic, conversion, ads, SKUs, refunds, profit, inventory and trends, with reproducible metrics, missing-data lists, confidence levels, budget limits and priority actions. Each row covers a platform, store or business unit and reporting period. Calculations are explicitly marked unavailable when settlement data, costs or platform rules are missing; displayed payments and attributed sales are not treated as actual receipts or incremental profit.

Each row submits CSV/TSV data and field calibers for a domestic platform, a store or business unit, and a statistical period.

Raw operating data (CSV/TSV text)Required: The table header must be included; each row only contains data for one domestic platform, one store or business unit, and one statistical period.
Field dictionary and formula caliberRequired: Explain the original name of the platform field, statistical granularity, unit, RMB caliber, payment/settlement definition, delivery attribution, refund backlash, cost range and the meaning of missing values.
Domestic platform, store scope and statistical periodRequired: For example, Pinduoduo; Mainland China; CNY; Asia/Shanghai; 2026-08-01 to 2026-08-31; the entire store or designated products.
The goal of this analysisRequired: For example, locate the reasons for profit decline, advertising waste, inventory risk or next cycle growth opportunities.
Business background and restrictions (optional)Optional: You can fill in budget, cash flow, fulfillment method, activities, price adjustment, out of stock, gross profit bottom line and inventory target.
Platform caliber, cost and delivery rule basis (optional)Optional: Paste the platform background field description or the latest official rate, payment/settlement, refund, activity, promotion attribution and deduction rules original text.
Compare to cycle or business goals (optional)Optional: Fill in the previous data, budget target or merchant-defined threshold, and explain whether the caliber is consistent.
Text model (optional, leave blank to use GPT-5.6 Sol)Optional: Follow the field instructions to enter your content.

Generation instructions

Each row is submitted as a separate task. Required fields are marked with *.

Each row represents a domestic platform, a store or business unit, and a statistical period. Taobao/Tmall, Pinduoduo, JD.com, Douyin E-commerce, Kuaishou and Xiaohongshu data should be analyzed separately and not directly mixed.
Please paste the CSV or TSV text with headers for the original operating data; the current version does not directly parse the uploaded Excel/CSV files.
The field dictionary must retain the original names of the platform's backend fields, and explain the statistical granularity, CNY caliber, payment and settlement definitions, product placement and attribution window, refund backlash, platform fees, commissions, logistics costs and the meaning of missing values.
Do not upload customer names, phone numbers, addresses, account passwords, payment information, or personal data not relevant to analytics.
When cost, platform fee, advertising or inventory fields are missing, the results will be clearly marked as uncalculatable and will not be automatically rebuilt.
The analysis results are used for business review and decision-making assistance, and do not replace financial auditing, taxation, legal or official settlement of the platform.

Each card is one task. Fill in its fields below.

	Raw operating data (CSV/TSV text)*	Field dictionary and formula caliber*	Domestic platform, store scope and statistical period*	The goal of this analysis*	Business background and restrictions (optional)	Platform caliber, cost and delivery rule basis (optional)	Compare to cycle or business goals (optional)	Text model (optional, leave blank to use GPT-5.6 Sol)	Actions
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