Ecommerce Funnels and Carts
Break down add-to-cart and checkout completion by category and device, interpret the 70% abandonment headline, and estimate the recoverable share.
Written and reviewed by Eric Han · Co-founder & CTO, reopt
Key takeaways
- Shopify medians are 6.8% add-to-cart, 49% checkout completion, and 1.4% session conversion. Cart-to-purchase is approximately 21% (calculated).
- Cart abandonment of 70.22% averages 50 studies. It does not mean 70% is recoverable.
- In a US survey, 42% were only browsing. Among other reasons, additional costs ranked first at 40%.
- Mobile has lower add-to-cart (5.4% versus 9.8%) but higher checkout completion (63% versus 35%). The source does not explain why.
- The average checkout has 5.1 steps and 11.3 form fields.
Funnel Stages
Sessions 100%
├─ Add to cart 6.8%
├─ Start checkout about 2.9% (calculated)
└─ Purchase 1.4%The sample comprises 436 Shopify stores using Littledata, July–October 2026 (grade C). Ratios of medians are approximations. We found no original benchmark for session-to-product-view conversion.
| Stage | Bottom 10% threshold | Bottom 20% threshold | Median | Top 20% threshold | Top 10% threshold |
|---|---|---|---|---|---|
| Add-to-cart rate | 2.1% | 3.4% | 6.8% | 12% | 17% |
| Checkout completion | 15% | 26% | 49% | 66% | 74% |
| Segment | Add to cart | Checkout completion |
|---|---|---|
| Mobile | 5.4% | 63% |
| Desktop | 9.8% | 35% |
| Beauty | 12% | 50% |
| Food / beverage | 11% | 53% |
| Health | 8.2% | 60% |
| Fashion | 6.0% | 48% |
| Home | 5.0% | 51% |
Simulation Inputs
| Stage | Input | Evidence and conditions |
|---|---|---|
| Add to cart | Mean 8.5%, | Fitted to Littledata quantiles, C; median about 6.8%. Category presets multiply medians by approximately 1.25 to estimate means |
| Cart → checkout start | Mean 43%, | Approximation from ratios of medians |
| Checkout completion | Mean 49%, | Fitted to the same dataset's quantiles, C |
Do not use 70.22% abandonment as a recoverable share, Baymard's 35.26%, Klaviyo attributed revenue, or Shop Pay's 50% as forecast inputs.
Ecommerce funnel intervals
Choose a category to populate add-to-cart and checkout completion. Distributions capture differences between stores, producing a wide session-conversion interval of about 0.2–5%. Cart-to-checkout start is approximated from ratios of medians.
Each input alone moves to its 5th and 95th percentile with others at the mean. Measure the top one first.
- Add-to-cart rate141orders ~ 2,130orders
- Checkout completion345orders ~ 1,480orders
- Cart → checkout start610orders ~ 1,220orders
8,000 runs. Stages are independent. If they move together the real interval is wider; if they move in opposite directions it is narrower. The 90% interval holds only rate uncertainty around the expected value; the actual count adds chance variation in counts. Vertical lines mark the 5th percentile, median (darker), and 95th. The last bin collects values above the 99th percentile. Concentration k is an author judgment.
Cart Abandonment
| Value | Definition | Evidence |
|---|---|---|
| 70.22% | Average of 50 studies from 2006–2025. Wide variation and no basis for assuming consistent definitions | Baymard 2025, C |
| 79% (top 10% 56%, bottom 10% 94%) | Nonpurchasing share of add-to-cart sessions, store median | Littledata, C |
Why People Leave
Baymard's US survey does not state sample size on the page. Of respondents, 42% were merely browsing. Excluding browsing, reasons were:
| Reason | Share |
|---|---|
| Additional costs | 40% |
| Slow delivery | 20% |
| Concerns about sharing card details | 19% |
| Forced account creation | 18% |
| Complicated checkout | 17% |
| Errors | 17% |
| Return policy | 13% |
| Total cost not shown | 12% |
| Card declined | 10% |
| Too few payment methods | 9% |
Survey statements differ from experimental effects. Although shipping costs rank first, experiments with free-shipping offers/messages averaged −0.2% revenue per visitor and 0.0% conversion effect (Effect Sizes of Ecommerce Levers).
Estimate the Recoverable Share
“Recover 70% abandonment and triple revenue” is faulty arithmetic. A more realistic calculation narrows the target:
- Remove people who were only browsing.
- Retain reasons the site can address, such as additional costs.
- Apply an effect size smaller than the benchmark headline.
If 79% of add-to-cart sessions do not purchase, they represent about 5.4% of all sessions (6.8% × 79%). Excluding the 42% who were only browsing leaves about 3.1%; applying the 40% additional-cost reason gives about 1.2% (calculated, mixing sources and multiplying multiple-response survey shares only as an order-of-magnitude check). The addressable population is around 1% of sessions, not “70%,” and an experimental effect must still be applied.
Baymard estimates that checkout UX improvements could increase large-site conversion by 35.26%. This is potential inferred from usability benchmarks, not an experiment, and comes from a company selling usability research. Treat it as an upper bound for planning.
Measuring Reminder Effects
Klaviyo 2026 reports abandoned-cart email revenue of $6.77 per recipient and a 6.0% click rate; SMS figures are $4.48 and 10.3% (more than 110,000 customers). Attribution methods and controls are undisclosed. These appear to be flow-attributed metrics, which would include purchases that happened without the message.
In the randomized Li et al. experiment, timing reversed the effect: a 30-minute reminder reduced purchasing, while a 24-hour reminder increased it (grade A). Add only holdout-measured incrementality to a simulation, not attributed revenue directly.
Checkout
Baymard benchmark sites average 5.1 checkout steps and 11.3 form fields (2024, C), down from 12.7 fields in 2019.
Shop Pay claims such as “up to 50% versus guest checkout” are upper-bound statements from Shopify-commissioned research with undisclosed methods (C). We found no randomized experiment on adding payment methods.
Ecommerce Conversion Baselines
Compare global, UK, and Shopify conversion rates by category and device, and examine Korean public statistics and their limitations.
Effect Sizes of Ecommerce Levers
Distinguish evidence on speed, reviews, free shipping, discounts, and checkout UX, and examine realistic A/B test effects.