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E-Commerce Sales Master Table Reconstruction and Cross-Table Cleaning icon

E-Commerce Sales Master Table Reconstruction and Cross-Table Cleaning

Data Analysis Updated 2026.08.30

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About this skill

Problem

Sales master tables often contain formula prefixes, wrapped quotes, administrative suffixes, ethnic or autonomous region terms, and inconsistent channel labels. For JD orders, the customer field may also require a lookup from a buyer-name mapping table using the order ID. Manual cleanup can miss fields, break formulas, create inconsistent sorting, and make it hard to preserve auditable taxable amount and tax-exclusive amount calculations.

How It Works

The skill rebuilds the input into a fixed 16-column Excel workbook: date, province, region, customer, catering ingredients, direct sales, variety, specification, flavor, quantity, tax-inclusive unit price, tax-inclusive amount, tax-exclusive amount, remarks, order ID, and company. Key steps include:

  • Global shell cleaning: remove leading = and surrounding quotes before any field logic.
  • Province and region mapping: normalize receiving areas using the provided mapping rules rather than general geographic assumptions.
  • Customer assembly: non-JD rows use geo prefix + order ID; JD rows look up buyer names from the reference table.
  • Variety, specification, and flavor: derive values from the combo source field using priority rules and strip specification tokens.
  • Formulas and styling: write =J{row}*K{row} for the tax-inclusive amount and =L{row}/1.13 for the tax-exclusive amount; center all cells, use 12pt by default, and apply 11pt to specified columns.
  • Sorting and coloring: group rows by Taobao, Tmall, JD, Pinduoduo, and Douyin; within each block, place seasoning first and ethyl last; apply channel-specific row fills.

Boundaries

This is best for teams with a stable sales master table, the required lookup table, and fixed business definitions. It depends on expected field names and the rules defined in the skill. Missing source values must remain blank; the skill should not invent data. The channel, company, variety, and specification mappings are business-specific and should not be treated as general geographic or financial accounting logic.

Use Cases

  • Clean a sales master table with formula prefixes and address suffixes into a fixed 16-column Excel workbook.
  • Join JD order IDs to a buyer-name lookup table and build customer values as geo prefix plus name.
  • Map messy combo fields into standardized variety and specification values using the defined priority rules.
  • Group and sort rows by channel, then fill each row with the channel-specific background color.

Best For

  • E-commerce operations staff who need to consolidate multi-channel sales master tables into one standard Excel file.
  • Finance assistants who need to keep tax-inclusive and tax-exclusive amount formulas with two decimals.
  • Customer service leads who want to link JD order IDs to buyer names from a lookup table.
  • Analysts handling spice-industry business data who need rule-based variety, specification, and channel standardization.