After users have weighed up various options in the consideration phase, the final purchase decision takes center stage in the purchase phase. In this phase, it is crucial to minimize possible uncertainties, optimize the purchase process and remove any final hurdles.
Targeted conversion rate optimization (CRO) in the decision phase ensures that users do not abandon the purchase but successfully complete it. In addition, optimizing this phase has a direct influence on the retention phase - because a smooth checkout process increases both customer satisfaction and the repurchase rate.
Important KPIs For Optimizing The Purchase Phase
Conversion rate: How many users successfully complete the purchase?
Shopping cart abandonment rate: How many users leave the purchase process before completing it?
Average order value: What is the average value per order?
Time to checkout: How long does it take from shopping cart to order?
Use of payment options: Which payment methods are preferred?
Relevant CRO Methods For The Purchase Phase
A/b testing: optimize the checkout process in a targeted manner
A smooth checkout is essential to reduce shopping cart abandonment. A/B testing and funnel analyses can be used to identify and systematically improve critical bottlenecks in the purchasing process.
Use case: An online store tests two checkout variants - one with a guest order and one with a registration requirement - to find out which leads to a higher conversion rate. In addition, session recordings and heat maps can be used to precisely analyze and optimize problem areas in the checkout process.Personalization: setting individual incentives in the purchasing process
Personalized content such as exclusive discounts or targeted product recommendations can make a decisive contribution to users completing their purchase.
Use case: A fashion retailer sends customers who have abandoned their shopping cart a personalized message with a discount code for their preferred style. Other possible uses for personalization in the checkout: Recommended payment options based on previous purchases and dynamic elements such as real-time notifications of low availability (“Only 3 items left”) or social proof (“Already bought 25× today”)Digital analytics: understanding abandonment and optimizing based on data
With the help of web analytics tools, companies can understand user behaviour during the purchasing process and identify weak points. This allows targeted optimizations to be derived.
Use case: An electronics retailer recognizes that many customers abandon their purchase if shipping costs are only displayed in the last step. Solution: Communicate shipping costs earlier and transparently.
Recommendation: Carry out a funnel analysis to identify the biggest abandonment points in the checkout process. It is also worth segmenting by end device to identify differences between mobile and desktop users.User research: recognizing usability problems in the checkout
User surveys and live chat analyses provide valuable first-hand insights into stumbling blocks in the purchasing process.
Use case: A travel platform discovers through interviews that customers find the payment process confusing. Revising the presentation leads to a noticeable increase in the conversion rate.Strategic consulting: developing the right payment strategy
The selection of suitable payment methods is a critical success factor for the conversion rate. Companies should analyse which payment methods are most popular with their target group and optimize the payment UX in a targeted manner.
Use case: An international online store increases the conversion rate by integrating regional payment methods such as Klarna (Europe) or Alipay (China) into the checkout.
Conclusion: Actively Support The Purchase Decision
The purchase phase not only determines the successful completion of a purchase, but also customer satisfaction and repurchase rates. Companies should specifically remove the last hurdles, ensure a smooth checkout and minimize conversion inhibitors through methods such as personalization, A/B testing and analytics.
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