The 10 Biggest Checkout Killers (and How to Fix Them)

By the time a shopper reaches checkout, you have already earned the visit and persuaded them to care. But that isn’t always enough to win the sale. Cart abandonment or a checkout forfeit is one of the most common and significant challenges that e-commerce businesses face. When a visitor stalls or drops a purchase, it is usually not about intent. It is about friction, doubt or confusion.

Here is a practical look at the ten of the most common issues that block or slow checkout most often, and specific ways to address each. We’ve compiled these by observing how experienced e-commerce teams have successfully mitigated card abandonment from across the Alhena community.  

A simple lens for thinking about checkout friction

Most checkout problems fall into one of three buckets:

1. Clarity The shopper does not fully understand price, options or what happens next.
2. Control The shopper feels boxed in by limited choices in accounts, payments or shipping.
3. Confidence The shopper is not yet comfortable with fit, quality, trust or support.

Every issue below is one of those three. The fix is usually about reducing the cognitive load, restoring a sense of control or adding targeted reassurance at the exact moment doubt peaks.

1. Forced account creation and weak guest checkout

The problem: Requiring an account before payment is still one of the highest impact checkout blockers. New customers do not yet see the value in “joining”, they just want to complete the purchase. Being pushed into creating a password, confirming email and opting in or out of marketing creates both friction and suspicion.

How to fix it

• Offer a clear, prominent guest checkout path, above the fold.
• Position account creation as optional and benefit led, for example: “Save your details for next time” or “Track orders and manage returns”.
• Allow password creation after the first successful order, using a simple one click link in email or on the confirmation page.
• Consider passwordless options such as email or SMS login that do not feel like “registration”.

Account walls can be valuable for loyalty programs, but making them optional at the point of payment tends to improve completion without harming long term engagement.

2. Late stage price shocks, fees and duties

The problem: Nothing slows a checkout like a total that suddenly jumps. Common culprits are shipping fees, taxes, duties, handling charges, platform fees and currency conversions that appear only at the final step. Shoppers interpret these as a lack of transparency and often abandon to “think about it”, then never return.

How to fix it

• Provide running totals that update as soon as shipping method, address or currency is selected.
• Show estimated taxes and duties early for international shoppers, even if the exact amount is finalized at the end.
• Avoid adding “mystery” fees that are not clearly explained in plain language.
• If free shipping or thresholds are part of your model, show progress clearly, for example: “You are 12 dollars away from free shipping”.

The goal is not to be the cheapest, it is to be predictable. Shoppers can work with a higher price. They struggle with a surprise.

3. Slow or unstable checkout experience

The problem: Even modest delays at the payment step have a strong impact on completion. Pages that lag between steps, spinners that feel endless, card validation errors that take several seconds, or mobile pages that freeze when switching payment methods all undermine confidence.

The real issue is less about patience and more about trust. If the interface feels unreliable, the shopper is reluctant to enter payment details.

How to fix it

• Measure time to interact and time to complete for each step, on real devices and networks, not just in a lab.
• Defer non essential scripts, analytics and widgets that load during checkout.
• Use inline validation that responds almost instantly for fields like card number or postal code.
• Test payment flows specifically on older devices and mid range Android phones, which often differ from desktop or flagship performance.

There is no need for perfection, but the experience should feel responsive and stable from the first click to the confirmation screen.

4. Form friction and unnecessary fields

The problem: Long forms, ambiguous labels and fields that do not map to how people think are a quiet but persistent cause of drop off. Common examples are:

• Asking for data you already have from earlier steps.
• Strict formatting on phone numbers or addresses without clear examples.
• Over collecting information for marketing or CRM at the expense of speed.

Shoppers do not mind filling in what is clearly necessary to receive their order. They resist what feels redundant or irrelevant.

How to fix it

• Start with the minimum viable checkout. Only collect what you need for payment, fraud checks, shipping and legal requirements.
• Use address lookup and auto complete where local regulations allow.
• Combine fields where appropriate, for example “First and last name” can sometimes be a single field if it matches your downstream systems.
• Make input expectations visible, using examples or inline hints, instead of relying on error messages after submission.

Teams that treat form fields as a product decision, not as a default from their platform, generally see steady gains here.

5. Inflexible shipping and delivery options

The problem: Shoppers often abandon not because shipping is expensive, but because it does not fit their constraints. Long windows with vague estimates, no pickup options or requiring a signature that the customer cannot provide can all stall the decision.

How to fix it

• Offer a small, clear set of shipping options that cover different priorities: cheapest, fastest and most predictable.
• Show realistic delivery estimates with dates, not just ranges, for example “Delivers Thursday 19 December” rather than “3 to 7 days”.
• Where possible, offer pickup points or locker collection, especially in markets where home delivery is less reliable.
• If some items are exceptions, label them early and clearly, not only at the final step.

You do not need every possible shipping configuration. You do need at least one option that feels workable for each major segment of your customer base.

6. Limited or misaligned payment options

The problem: Checkout can stall when the available payment methods do not match the shopper’s habits or constraints. Examples include:

• No local wallets in markets where they are dominant.
• No buy now, pay later option for higher ticket items.
• Forcing manual card entry on mobile when wallets could autofill.

When shoppers cannot pay in the way they consider safe and convenient, many will postpone or cancel.

How to fix it

• Map payment methods to your top markets and segments. For example, cards may be sufficient in some countries, while wallets and local bank transfers are critical in others.
• Prioritize mobile friendly methods such as Apple Pay, Google Pay and local wallets where adoption is strong.
• Respect customer preferences. If a return visitor has used a method before, preselect it when appropriate.
• Keep the number of visible options manageable. Too many choices can create friction, so group or collapse rarely used methods.

The objective is not to chase every new payment trend, but to align with how your customers already pay in their daily lives.

7. Poor mobile checkout ergonomics

The problem Mobile traffic often exceeds desktop, but many checkouts are still designed primarily with desktop in mind. Issues include:

• Tap targets that are too small or too close together.
• Keyboards that do not match the field type.
• Important information placed below lengthy sections or images.
• Modals or popups that are difficult to close on small screens.

Even when everything technically works, a layout that feels cramped or awkward can increase abandonment on small devices.

How to fix it

• Design checkout mobile first, then scale up to tablet and desktop.
• Trigger the correct keyboard for each field, for example numeric for card numbers and phone, email keyboard for email.
• Keep progress and order summary visible or easily accessible, so shoppers always know where they are and what they are paying.
• Regularly test flows on real phones in portrait orientation, not just with responsive design tools.

Mobile checkout does not need to be fancy. It needs to be legible, predictable and thumb friendly.

8. Promotion, coupon and pricing confusion

The problem: Discounts that do not apply as expected can undermine the entire purchase. Examples:

• Coupon codes that appear in marketing but are expired or with undisclosed limits.
• Promotions that apply only to some items in the cart without clear messaging.
• Fields that invite coupons but leave customers feeling they are missing out if they do not have one.

Shoppers who feel they are getting a worse deal than others often pause “to find a better code” and never return.

How to fix it

• Keep promotion logic as simple and explicit as possible, for example “20 percent off all full price items today” instead of complex combinations.
• Validate codes early in the checkout and clearly explain why a code does not apply.
• If you must show a coupon field, consider adding neutral copy such as “Optional” and make sure the final price is clearly presented even without a code.
• Ensure marketing, merchandising and engineering share a single source of truth for active campaigns and rules.

The aim is not to run more promotions. It is to ensure that the ones you do run are reflected accurately and consistently at checkout.

9. Size and fit hesitation, and how AI agents can help

The problem: In categories like apparel, footwear and accessories, one of the most common reasons shoppers stall at checkout is very simple: “Will this actually fit me the way I expect?”

Size charts often do not bridge the gap between abstract measurements and real bodies. Shoppers worry about:

• Brand specific fit quirks, such as “runs small” or “relaxed cut”.
• Differences between regions, for example US and EU sizing.
• How an item will fit compared to something they already own and like.
• The hassle of returns if they choose incorrectly.

This hesitation frequently surfaces at the last moment, when the shopper sees their chosen size in the cart and starts doubting it.

How AI agents can address this

Modern AI driven fit assistants can reduce this hesitation in practical ways:

• Contextual recommendations The agent can consider height, weight, body shape indicators and age, then combine that with purchase and return data from similar customers to suggest a size with a clear confidence level.
• Brand and product specific guidance Instead of generic advice, the agent can explain that a particular jean “fits snug at the waist and relaxed at the thigh”, or that this sneaker runs half a size smaller than another brand the customer may know.
• Comparison to existing items When shoppers have an account or allow limited data use, the agent can compare measurements to items they have previously bought, for example “Similar fit to the black chinos you ordered in August”.
• Conversational clarification A shopper might ask “I am between medium and large, I like a slightly looser fit, what should I pick?” The agent can respond in plain language rather than forcing the customer back into charts and tables.

How to implement this without creating new friction

• Place the AI fit assistant close to size selection and visible in the cart or checkout, not hidden in a separate tool.
• Allow shoppers to ignore it if they prefer, so it adds reassurance rather than becoming a gate.
• Make it clear which data is being used and how, and offer a simple opt out path.
• Use output that is specific and modest, for example “Most customers like you chose size M and kept it”, rather than absolute guarantees.

AI agents will not eliminate all returns or all concerns. They can, however, provide targeted reassurance at the point of decision, which often reduces both hesitation and post purchase regret.

10. Weak reassurance on returns, support and next steps

The problem: Even when price, fit and logistics are acceptable, shoppers sometimes hesitate because they are not sure what happens if something goes wrong. Questions include:

• How easy is it to return or exchange this?
• What if it arrives late or damaged?
• Is customer support reachable if there is an issue?

If those answers are buried in a separate policy page, many shoppers will simply pause and “come back later” instead of proactively seeking out the information.

How to fix it

• Surface return and exchange basics directly in the checkout summary, for example “30 day free returns on unworn items” or “Free exchanges on size”.
• Provide a clear link to the full policy, but lead with a short, human summary.
• Show basic support availability, such as chat hours or response times, and a clear path to contact.
• Keep confirmation emails consistent with what you promised at checkout, so there is no sense of bait and switch.

The goal is to give the shopper enough confidence that if the purchase does not work out perfectly, they will not be stuck.

Bringing it together

Checkout is not one problem, it is a collection of small decisions that either build or erode trust. The ten issues above are common because they sit at the intersection of multiple teams: product, engineering, marketing, finance, logistics and customer service.

A practical approach is to:

1. Instrument the journey so you can see where and for whom stalls occur.
2. Prioritize fixes that reduce friction across many orders, such as guest checkout and transparent totals.
3. Add targeted reassurance where doubt is highest, for example with AI fit agents in size driven categories.
4. Treat checkout changes as experiments, with clear hypotheses and outcome metrics.

Most brands that take this methodical approach do not see overnight transformation. They see steady, compounding gains in completion and customer confidence. Over time, that is usually what makes the difference between a checkout that feels fragile and one that reliably converts intent into revenue.