Online retail sales are projected to reach 6.3 trillion dollars. Seventy three percent of shoppers report greater likelihood to purchase when discounts are personalized. Figures on cart abandonment and discount code abuse show which offer depths lift conversions and which reduce long term profit.
Key Takeaways
- Online retail sales are projected to reach $6.3 trillion in 2024
- 22.7% of all retail sales were conducted online in 2023
- The global e-commerce market reached $7.4 trillion in 2023 (including wholesale and retail categories)
- 73% of shoppers say they are more likely to shop with a retailer if they receive personalized discounts
- 42% of consumers report they have abandoned an online shopping cart because delivery fees were too high
- 77% of consumers say they check product reviews before making a purchase
- Discount code abuse accounted for 38% of observed promo fraud attempts in 2023
- The average discount offered in US online apparel was 25% in 2023
- Discount depth of 20–30% was associated with the highest conversion rates in US e-commerce experiments
- Email marketing ROI averaged $36 per $1 spent in 2023
- The average email click-through rate was 2.5% in 2024 (US)
- Mobile conversion rates were 1.9% for e-commerce in 2024 (global benchmark)
- Retailers are shifting promotions toward digital channels: 44% of US promotional spend moved to digital by 2023
Personalized digital discounts drive online sales, but high delivery fees and promo fraud still cost retailers.
Related reading
01 · Category
Market Size3 stats
01
Online retail sales are projected to reach $6.3 trillion in 2024
02
22.7% of all retail sales were conducted online in 2023
03
The global e-commerce market reached $7.4 trillion in 2023 (including wholesale and retail categories)
Interpretation
Market Size Interpretation
With online retail projected to hit $6.3 trillion in 2024 and already accounting for 22.7% of all retail sales in 2023, the Market Size landscape for Discount is expanding fast as e-commerce reached $7.4 trillion globally in 2023.
02 · Category
Customer Behavior6 stats
01
73% of shoppers say they are more likely to shop with a retailer if they receive personalized discounts
02
42% of consumers report they have abandoned an online shopping cart because delivery fees were too high
03
77% of consumers say they check product reviews before making a purchase
04
39% of US consumers said coupons were the reason they switched brands in 2023
05
31% of consumers say they look for promo codes before making an online purchase
06
In 2023, 18% of US shoppers used retailer subscription discounts
Interpretation
Customer Behavior Interpretation
Customer behavior shows shoppers strongly favor incentives and transparency, with 73% more likely to buy when discounts are personalized and 42% abandoning carts over high delivery fees.
03 · Category
Category Economics5 stats
01
Discount code abuse accounted for 38% of observed promo fraud attempts in 2023
02
The average discount offered in US online apparel was 25% in 2023
03
Discount depth of 20–30% was associated with the highest conversion rates in US e-commerce experiments
04
Dynamic discounting can reduce inventory holding costs by 10–20% in retail simulations
05
A 2017 study in Marketing Science found that monetary discounts can increase purchase probability but may reduce long-term profit due to increased price sensitivity
Interpretation
Category Economics Interpretation
Across Category Economics, the data suggests that discounts are most effective when they are targeted and kept moderate, with 20–30% depth producing the highest conversion rates while discount-related promo fraud reached 38% of attempts in 2023 and dynamic discounting can cut inventory holding costs by 10–20%.
More related reading
04 · Category
Performance Metrics7 stats
01
Email marketing ROI averaged $36per $1 spent in 2023
02
The average email click-through rate was 2.5% in 2024 (US)
03
Mobile conversion rates were 1.9% for e-commerce in 2024 (global benchmark)
04
Average e-commerce cart abandonment rate was 70% in 2024
05
In 2023, US consumers reported using buy-now-pay-later on 15% of purchases in a typical month
06
Retailers report an average 2.1x increase in average order value when bundle discounts are used
07
A 2020 peer-reviewed study found that loyalty-program discounts can increase customer retention by about 5 percentage points
Interpretation
Performance Metrics Interpretation
In performance metrics, shoppers are responding with measurable but constrained engagement and conversion, shown by a 2.5% email click through rate and 70% cart abandonment in 2024, while discounts can still drive stronger outcomes such as a 2.1x lift in average order value with bundle discounts.
05 · Category
Industry Trends1 stats
01
Retailers are shifting promotions toward digital channels: 44% of US promotional spend moved to digital by 2023
Interpretation
Industry Trends Interpretation
Under the Industry Trends category, the biggest signal is that US retailers moved 44% of promotional spend to digital by 2023, showing how strongly discounts are migrating online.
report visual · Breakdown
Discounts: what drives demand vs. what holds customers back
Personalized discounts boost shopper intent, while friction points like delivery fees and cart abandonment continue to reduce conversions.
30%
Discount depth of 20–30% was associated with the highest conversion rates in US e-commerce experiments
70%
Average e-commerce cart abandonment rate was 70% in 2024
source-verifiedcrowdtap.com · baymard.com2024
Reference
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Karl Becker. (2026, February 13). Discount Statistics. Gitnux. https://gitnux.org/discount-statistics
MLA
Karl Becker. "Discount Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/discount-statistics.
Chicago
Karl Becker. 2026. "Discount Statistics." Gitnux. https://gitnux.org/discount-statistics.
Sources & references
22 datasets cited across this report · attribution is report-level
+3 additional datasets cited (not shown individually)