Phase 1 covers the full cycle: from clean Line List at season start, through to ongoing price updates throughout the season. Clean data in = clean data out. No more drift from manual edits.
Steps 1-2 (Season Setup): ~1.5-2 weeks — Line List → Panda file transformation (194 columns), image mapping, translations
Steps 3-6 (Pricing Engine): ~1-1.5 weeks — Currency conversions, territory logic, output generation
Testing & UAT: ~1 week — Validation against live uploads, Tradebyte/Shopify testing, iteration with client
Step 7: Manual upload in Phase 1, API automation potential in future
Note: This is complex multi-platform, multi-currency data transformation currently handled by multiple team members. Timeline reflects the depth of testing required to ensure output files work correctly with Tradebyte, Shopify, and other platforms.
When: Once per season, at the start.
The Line List is your master data for the season. It contains style codes, EANs, colours, pricing, and supplier info.
This step captures that data and prepares it for transformation into the Panda file.
| Field | Maps To (Panda) | Status |
|---|---|---|
| OPTION CODE | p_nr (Product Number) | ✓ Have |
| SKU CODE | a_nr (Article Number) | ✓ Have |
| EAN (from GS1) | a_ean | ✓ Have |
| ITEM DESCRIPTION | p_name_proper | ✓ Have |
| ZALANDO COLOUR | a_comp[color] | ✓ Have |
| COLOUR DESCRIPTION | a_comp[supplier color] | ✓ Have |
| HS CODE | a_intrastat | ✓ Have |
| M/W (Gender) | p_tag[gender] | ✓ Have |
| DELIVERY SEASON | p_tag[season] | ✓ Have |
| GBP RRP | Base for all pricing | ✓ Have |
| SHELL FABRIC / LINING / FILL | p_comp[composition] etc | ✓ Have |
| Product Descriptions (EN) | p_text | ⚠️ Where does this live? |
| Product Descriptions (DE) | <DE>p_text | ✗ Need source |
| Bullet Points (EN) | p_bullet{0-7} | ⚠️ Where does this live? |
| Bullet Points (DE) | <DE>p_bullet{0-7} | ✗ Need source |
| Care Instructions | p_comp[care instructions] | ⚠️ In Line List? |
| Certifications (RDS etc) | p_comp[Certification number] etc | ⚠️ Where? |
When: Once per season, after Line List is finalised.
This is the "huge task" — transforming your clean Line List into the 194-column Panda file format required by Tradebyte.
Currently manual and error-prone. Once automated, it runs in seconds.
| Section | Columns | Automation Status |
|---|---|---|
| Product Identity | p_nr, p_name_keyword, p_name_proper (EN + DE) | ✓ Can map from Line List |
| Descriptions | p_text (EN + DE), p_bullet{0-7} (EN + DE) | ⚠️ Need source |
| Attributes | p_brand, p_cluster, p_comp[*] (~30 fields) | ⚠️ Partially in Line List |
| Tags | p_tag[agegroup], p_tag[gender], p_tag[season], p_tag[sizegrid], p_tag[style] | ✓ Can derive from Line List |
| Article/SKU Data | a_nr, a_prodnr, a_ean, a_comp[color], a_comp[size] | ✓ Can map from Line List |
| Imagery | a_media[Frontview], a_media[Backview], a_media[Details]{0-14}, a_media[aboutyoumedia]{1-8} | ⚠️ Need Google Drive access |
| Pricing (All Territories) | a_vk[zafd], a_vk_old[zafd], ... (30 columns for Zalando + About You) | ✓ From currency conversion |
| Activation Flags | a_active, a_active[zafd], a_active[ayde], ... (17 flags) | ✓ Default to 1, override as needed |
| Logistics | a_delivery, a_stock, a_shipping_type, a_org_country, a_pieces, dimensions | ⚠️ Some in Line List, some static |
The Panda file requires specific image URLs for each view. We need to match SKU codes to image filenames in Google Drive.
| Panda Field | Expected Image | Naming Convention |
|---|---|---|
| a_media[Frontview]{0} | Model front shot | ✗ Need pattern |
| a_media[Backview]{1} | Model back shot | ✗ Need pattern |
| a_media[Details]{0-14} | Detail/flatlay shots | ✗ Need pattern |
| a_media[aboutyoumedia]{1-8} | About You specific (with -JACK1T suffix) | ⚠️ Seems to be same images with suffix |
When: Throughout the season, as needed for markdowns/promotions.
Users enter pricing at the option level (style + colour), not SKU level.
The master data from Steps 1-2 feeds this, ensuring consistency.
| Field | Source | Status |
|---|---|---|
| Option Code | Line List | ✓ Have |
| SKU Codes (all sizes) | Line List / Panda File | ✓ Have |
| EAN Numbers | Line List | ✓ Have |
| Article Name | Line List | ✓ Have |
| Colour | Line List | ✓ Have |
| GBP RRP (Black Price) | Line List | ✓ Have |
| Product Images | Google Drive | ✗ Need access |
| Master SKU List (complete) | To be provided | ✗ Need file |
User selects which territories to include in the price update. Allows for territory-specific exclusions (e.g. "All territories except Italy") and different discount levels per region.
| Code | Territory | Currency | Status |
|---|---|---|---|
| zafd | Germany | EUR | ✓ Confirmed |
| zaff | France | EUR | ✓ Confirmed |
| zafa | Austria | EUR | ✓ Confirmed |
| zafb | Belgium | EUR | ✓ Confirmed |
| zafn | Netherlands | EUR | ✓ Confirmed |
| zafe | Spain | EUR | ✓ Confirmed |
| zazi | Italy | EUR | ✓ Confirmed |
| zafh | ??? | ??? | ✗ Need confirmation |
| zazfsfi | Finland | EUR | ⚠ Verify |
| zazfscf | Switzerland (FR) | CHF | ⚠ Verify |
| zazfscd | Switzerland (DE) | CHF | ⚠ Verify |
| zazfspl | Poland | PLN | ⚠ Verify |
| zazfsse | Sweden | SEK | ⚠ Verify |
| zazfsdk | Denmark | DKK | ⚠ Verify |
| zazfscz | Czech Republic | CZK | ⚠ Verify |
| Code | Territory | Currency | Status |
|---|---|---|---|
| ayde | Germany | EUR | ⚠ Verify |
| ayat | Austria | EUR | ⚠ Verify |
| ayfr | France | EUR | ⚠ Verify |
| aynl | Netherlands | EUR | ⚠ Verify |
| aybe | Belgium | EUR | ⚠ Verify |
| ayit | Italy | EUR | ⚠ Verify |
The core engine. Expands option-level pricing to all SKUs, applies currency conversions, and validates against business rules before generating output files.
For each option code, system looks up all associated SKUs (sizes) and applies the same pricing. This ensures no sizes are missed.
| Input | Output |
|---|---|
| W110SUA20077B00 @ €256.75 |
W110SUA20077B00XS @ €256.75 W110SUA20077B00S @ €256.75 W110SUA20077B00M @ €256.75 W110SUA20077B00L @ €256.75 W110SUA20077B00XL @ €256.75 |
Each territory has a specific conversion formula. This is NOT just exchange rates - may include tariffs, landed costs, rounding rules.
| Currency | Territories | Conversion Formula | Status |
|---|---|---|---|
| EUR | DE, FR, AT, BE, NL, ES, IT, FI | ??? | ✗ Need formula |
| CHF | Switzerland (FR + DE) | ??? | ✗ Need formula |
| PLN | Poland | ??? | ✗ Need formula |
| SEK | Sweden | ??? | ✗ Need formula |
| DKK | Denmark | ??? | ✗ Need formula |
| CZK | Czech Republic | ??? | ✗ Need formula |
| GBP | UK DTC | Base currency (1:1) | ✓ Known |
| USD | US DTC, Macy's, Nordstrom | ??? (includes tariffs) | ✗ Need formula |
System checks that discounted prices don't fall below minimum thresholds per platform. Flags any violations for manual review.
| Platform | Break-Even Calculation | Status |
|---|---|---|
| Zalando | Cost + Commission + Shipping + ??? | ✗ Need formula |
| About You | ??? | ✗ Need formula |
| UK DTC | ??? | ✗ Need formula |
| US DTC | ??? (different due to tariffs) | ✗ Need formula |
| Macy's / Nordstrom | ??? | ✗ Need formula |
System generates correctly formatted CSV files for each platform, matching their exact import requirements. Also creates an audit log of all pricing changes.
| Output | Format | Sample File | Status |
|---|---|---|---|
| Zalando Price File | a_nr + 30 price columns (15 territories × current/old) | article_pricing_zalando-sale-bfcm-251125_87_.csv | ✓ Have sample |
| About You Price File | Part of Panda file or separate? | Embedded in panda file | ⚠ Need clarity |
| Shopify UK/EU CSV | ??? | None provided | ✗ Need sample |
| Shopify US CSV | ??? | None provided | ✗ Need sample |
| Price Change Log | New - will be created | N/A | ◐ To build |
In Phase 1, CSV files are downloaded and manually uploaded to each platform. Phase 2 could automate this via APIs where available.
| Step | Build | Test & Iterate | Total |
|---|---|---|---|
| Step 1: Season Setup (Line List Input) | 1-2 days | 1 day | 2-3 days |
| Step 2: Panda File Generation (194 cols) | 4-5 days | 2-3 days | 6-8 days |
| Step 3: Pricing Input Interface | 1-2 days | 1 day | 2-3 days |
| Step 4: Territory Selection (21 territories) | 1 day | 0.5 days | 1.5 days |
| Step 5: Processing & Validation (8 currencies) | 2-3 days | 1-2 days | 3-5 days |
| Step 6: Generate Output Files (6+ formats) | 2-3 days | 2-3 days | 4-6 days |
| Integration Testing & UAT with Client | — | 3-5 days | 3-5 days |
| Total | 11-16 days | 10-15 days | 3-4 weeks |
Notes:
• Steps 1-2 run once per season. Steps 3-6 run multiple times throughout season for markdowns.
• Timeline assumes all required data/files are provided upfront. Delays in receiving currency formulas, Shopify samples, or image access will extend timeline.
• Testing includes: output validation against existing files, Tradebyte upload testing, Shopify import testing, break-even threshold verification.
• This system currently requires multiple team members to operate manually — complexity reflects that reality.
Understanding where data currently lives and flows - important context for integration.
| Data | Location | Format | Notes |
|---|---|---|---|
| Master Line List | OneDrive | Excel | Updated live in meetings (Excel more responsive than Sheets) |
| Panda File Master | Google Sheets | Google Sheet | Line list gets uploaded here after meetings |
| Product Imagery | Google Drive | Images | Need access to link images to SKUs |
| Price Files | Various / Local | CSV/Excel | Created ad-hoc, no central repository |
Phase 1 system will need a "source of truth" for product data. Options:
Recommendation: Option A initially (simplest), with Option B as Phase 2 enhancement.
Documented for reference — not in current scope but noted from discovery call.
Remove the manual CSV upload step entirely. Push prices directly to platforms via API.
Leadership wants high-level view without digging into individual platforms. Currently manual and fragmented.
| Platform | Data Available | Access Method |
|---|---|---|
| Tradebyte | Zalando, About You, EU DTC sales | TBD — API likely available |
| Shopify | UK DTC, US DTC sales | API available |
| Power BI | TBI wholesale data | TBD — may need export |
| R360 | Macy's, Nordstrom sales | TBD — bespoke platform |
| Atalos | Zalando profitability analysis | TBD — subscription service |
Verify prices are live and correct on front-end websites. Catch discrepancies before customers do.