Shopping Cart Abandonment Rate

What is Shopping Cart Abandonment Rate?
How is Shopping Cart Abandonment Rate calculated?
Why is Shopping Cart Abandonment Rate Important?
Common Reasons for Shopping Cart Abandonment
Shopping Cart Recovery
Measuring the Online Shopping Cart Abandonment Rate alongside other eCommerce metrics
Average Cart Abandonment Rates
Using A/B testing and machine learning to improve AOV

What is Shopping Cart Abandonment Rate?

Cart or Basket Abandonment Rate is when a potential customer starts the checkout process for an online order but drops out before completing their purchase. If a user adds items to their cart/basket but never completes the transaction, this is referred to as ‘abandoned’. According to the Baymard Institute, the average cart abandonment rate stands at 69.82% which makes it a vital part of any eCommerce brand’s optimization roadmap.


How is Shopping Cart Abandonment Rate calculated?

The Shopping Cart Abandonment formula is as follows:

Shopping Cart Abandonment Rate % =(1-(Completed Transactions / number of transactions initiated)) x 100

This is calculated as a percentage and will provide retailers and brands insight into purchase completion in relation to initial purchase intent.

For example, if 3,500 transactions were started and 1,000 completed, then the abandonment rate was 71.43%.
i.e. (1-(1000/3500)) x 100 = 71.43%


Why is Shopping Cart Abandonment Rate Important?

Shopping Cart Abandonment is a vital metric to monitor for any retailers and brands as a high abandonment rate could indicate a poor or broken user experience.

Looking at ways to reduce Shopping Cart Abandonment Rates is often a focus for Conversion Rate Optimization strategies.

By optimizing the checkout process, you make every visit to your site more valuable and in turn can positively impact other key metrics such as Conversion Rate and Revenue Per Visitor.

If we take the example below, by reducing the Shopping Cart Abandonment Rate by 15% from 69.82% to 60%, you see a 28% uplift in completed transactions. If we apply an Average Order Value (AOV) of £50, that equates to a £35,300 increase in revenue.

Company A B C
Initiated Transactions 8,000 8,000 8,000
Shopping Cart Abandonment Rate 69.82% 65% 60%
Completed Transactions 2,494 2,800 3,200


Common Reasons for Shopping Cart Abandonment

Shoppers will abandon carts for a range of reasons, but some of the most common and most important to address are listed below:

  1. Lack of Trust: If the shopper is new to the Brand, or has not seen evidence of positive shopper feedback during their Buying Journey, they may not feel comfortable sharing their card details. Integrating social proof throughout a site or app has been statistically proven to build trust, increase conversion rates and average order values (AOV) whilst simultaneously reducing cart abandonment
  2. High/Unexpected Costs: This may be in the form of high shipping costs, taxes or unexpected fees. Presenting shoppers with this information earlier in the Buying Journey or reviewing fees (e.g. bundling shipping costs into the overall product cost) can help dramatically reduce cart abandonment
  3. Limited Payment Options: Shoppers now expect to be offered their preferred payment method at checkout which spans far further than just debit or credit card options. Increasingly retailers and brands are offering their shoppers a range of payment options such as: PayPal, Apple Pay, Coupons and Gift Cards – in addition to Buy Now Pay Later (BNPL) options with companies such as Klarna. According to a study from PPRO, 44% of UK consumers stop a purchase if their favourite payment method isn’t available
  4. Confusing/Long Checkout Process: The checkout process should have the fewest amount of fields possible to complete the transaction whilst also offering auto-complete or quick lookup options (e.g. saved payment details, postcode lookup etc)
  5. Price Comparison Shopping: It is common for shoppers to add items to cart whilst they browse other websites. By offering limited time promos and using social proof at cart, you can increase the % of users going straight through to purchase
  6. Technical Issues: Monitoring key drop out points during the checkout process and performing regular cross-browser, cross-device and cross-platform checks is fundamental to identifying and fixing any technical issues
  7. Ambiguous Return Policy: Shoppers will often seek out the returns policy and warranties for items added to their cart. If this is insufficient or ambiguous, this can lead customers to abandon their purchase
  8. Mandatory Account Creation: Sites that force shoppers to create an account without offering a ‘guest checkout’ option will see a far higher Cart Abandonment Rate
  9. Payment Security Concerns: Outdated checkout designs, no SSL certificate, non-device optimized payment gateways and missing images can all impact shopper confidence in the checkout process
  10. Limited Delivery Options: 50% of shoppers said that they abandoned their shopping carts because the delivery choices being offered by the retailer are unsatisfactory or did not meet their needs (source SmartCompany)
  11. No Discounts / Promo Code Options: New or returning customers may come to expect discounts or promotional codes on items during common sales periods (e.g. Black Friday, end of Season) or see that your competitors are offering discounts on the same item(s)
  12. Site/App Speed Performance Issues: According to a study by Unbounce, nearly 70% of consumers admit that page speed influences their likeliness to buy.


Shopping Cart Recovery

In addition to addressing the common issues mentioned above, another key strategy to address Shopping Cart Abandonment is Shopping Cart Recovery.

Even checkouts which have been thoroughly optimized will see shoppers abandon their carts. Cart Recovery attempts to bring these shoppers back into the Buying Journey.

Below are three common eCommerce Cart Recovery Strategies

  • Exit Overlays: As a user goes to leave the site, an exit overlay can be triggered offering shoppers discounts or coupons.
  • Remarketing: If a user has already left the site, remarketing them using a range of formats such as display ads, social media formats, video etc, can bring them back into the Buying Journey.
  • Abandoned Cart Emails: Depending on a retailer or brand’s Privacy Policy and the country(ies) they operate in, if a shopper has entered their email address during the checkout process before leaving, then there may be an opportunity to send them an abandonment email. This may include an offer and / or related items.


Measuring the Online Shopping Cart Abandonment Rate alongside other eCommerce metrics

The Online Shopping Cart Abandonment Rate should not be viewed in isolation. You may have a very low Cart Abandonment Rate but only a handful of orders. Holistic reporting should include:

  • Total orders: All orders for the reporting period
  • Items per order: The average number of items per order
  • Revenue Per Visitor (RPV): The value of each visit to the site – this is arguably a more important measure as it is a strong indicator of non-engaged visits
  • Conversion Rate (CR%): Orders per visit as a percentage
  • Return on Investment (ROI): Return on investment divides the net profit (or loss) from an investment by its cost

Depending on your business model, there may be additional metrics to monitor alongside the KPIs mentioned above.


Average Cart Abandonment Rates

Whilst the overall cart abandonment rate sits at 69.82% (source: Baymard Institute), drilling down further into industry statistics shows significant variability. Statista shares regularly benchmarked averages for selected industries across the globe. Retail as a whole is showing abandonment rates of 71.24% but this increases for Luxury and Fashion brands with 87.93% and 87.79% respectively. Travel sits is also well above the overall average at 82%.

Using A/B testing and machine learning to improve AOV

A/B testing can be used to understand how changes to titles, descriptions, imagery and layouts can affect performance. Social Proof Messaging A/B testing with Taggstar is no different.

Our results are scientifically tested and proven. We support all industry A/B testing software to independently validate results, or use our in-built capability with an experiment dashboard to track results in real-time.

As leaders in social proof machine learning, our technology delivers the right message at the right time in the customer buying journey to continually optimize conversion.

Using real-time information ensures a true picture of product popularity that customers can trust and avoids message fatigue of repeatedly sharing the same message.


Taggstar’s Social Proof Messaging solutions presents real-time shopper behavior that statistically and scientifically increase online conversion rates and AOVs whilst simultaneously reducing cart abandonment rates.

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