Home > How to Combine OOTDBuy Coupons with Spreadsheets for Consumer Spending Data Analysis

How to Combine OOTDBuy Coupons with Spreadsheets for Consumer Spending Data Analysis

2025-07-18
Product 1

AirPods 3-0102

$7.64
Product 1

Jordan 4 Retro (40 color)-0001

$34.72
Product 1

casabianca Fashion Shirts Casual Suits (40 styles)-1146

$26.25
Product 1

Prada Casual Sneakers (22 color)-0015

$38.61
Product 1

New Balance 9060 series (20 style)-0011

$38.89
Product 1

2024 New Jordan 4 (12 colors)-0010

$38.89
Product 1

Dior B30 Series (20 style)-0416

$45.83
Product 1

OG Balenciaga speed-1047

$45.56
Product 1

dior b22-b23-0027

$45.83
Product 1

dunk low （30 color）-0003

$19.44
Product 1

AMIRI MA-1-0024

$72.22
Product 1

Denim tears T-shirt -0930

$9.44
Product 1

Balenciaga Triples (7 styles) -0515

$83.33
Product 1

Rolex watches (3 qualities 14 styles)-0396

$52.78
Product 1

GOYARD Fashion bags-0182

$9.58
Product 1

Louis Vuitton LV belt（36 style）-0246

$11.81
Product 1

Amiri Cap（11 styles）-0662

$13.75
Product 1

Louis Vuitton fashion bag-0185

$48.61
Product 1

Louis Vuitton LV bucket bag（10 styles）-0187

$55.42
Product 1

24-25 Football Jerseys (40+ Colors)-0948

$9.44

By integrating OOTDBuy coupons with spreadsheet tools, businesses can perform in-depth analysis of consumer spending patterns to refine marketing strategies.

Step 1: Data Collection

First, gather key data points from OOTDBuy coupon transactions, such as:

  • Order details (product names, quantities)
  • Original prices and discounted amounts
  • Date/time of coupon usage
  • User demographics (when available)

Use platforms like OOTDBuy.com

Step 2: Spreadsheet Organization

Create structured spreadsheets with columns for:

Coupon Code Product Category Original Price Discount Applied Date Used

Key Analysis Methods

1. Coupon Effectiveness

Calculate metrics like:

=COUNTIF(coupon_column,"PROMO2023")  // Usage frequency
=AVERAGE(discount_column)            // Average savings

Deep Dive Example

For a tech product campaign, pivot tables might reveal:

Age Group Coupon Usage % Avg. Order Value
18-25 62% $89

Pro Tip: Use time series analysis to identify seasonal patterns in OOTDBuy

Actionable Insights

  1. Optimize coupon values based on price sensitivity analysis
  2. Schedule promotions during high-engagement periods
  3. Personalize offers using customer segmentation data
Integrations:ootdbuys.com/api).
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