Home > Optimizing Reverse Purchasing Platforms’ Marketing with Data-Driven Spreadsheets

Optimizing Reverse Purchasing Platforms’ Marketing with Data-Driven Spreadsheets

2025-05-28
Product 1

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Jordan 4 Retro (40 color)-0001

$34.25
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AirPods 3-0102

$7.53
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casabianca Fashion Shirts Casual Suits (40 styles)-1146

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Prada Casual Sneakers (22 color)-0015

$38.08
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New Balance 9060 series (20 style)-0011

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2024 New Jordan 4 (12 colors)-0010

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Dior B30 Series (20 style)-0416

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dior b22-b23-0027

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AMIRI MA-1-0024

$71.23
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OG Balenciaga speed-1047

$44.93
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dunk low （30 color）-0003

$19.18
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Denim tears T-shirt -0930

$9.32
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Rolex watches (3 qualities 14 styles)-0396

$52.05
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GOYARD Fashion bags-0182

$9.45
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Balenciaga Triples (7 styles) -0515

$82.19
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Amiri Cap（11 styles）-0662

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LV Louis vuitton belt（36 style）-0246

$11.64
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Louis Vuitton fashion bag-0185

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LV bucket bag（10 styles）-0187

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Reverse purchasing platforms are gaining popularity globally, but competition is fierce. By leveraging historical marketing data from major platforms (e.g. SuperBuy, Pandabuy) structured in spreadsheets, businesses can create hyper-targeted campaigns to maximize conversions.

Step 1: Centralizing Platform Marketing Data

  • Consumer Behavior Metrics:
  • Platform Comparisons:
  • Historical Performance:

[Sample Spreadsheet Frame - Columns]

→ Platform, Target Country, Main User Age, Best-Performing Category, CPA(USD), CTR(%)…→ JapanRabbit → Japan →25-34 → Anime Merch → $2.1 → 3.2% …

Step 2: Components for Performance Marketing

≡ Audience Segmentation

[Data Filters Example]

  1. Use SORTBY !]
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