AWS for Industries
Winning Back Customers and Growing Revenue with Abandoned Cart Recovery
One of the biggest challenges faced by online retailers is shopping cart abandonment, where customers add items to their shopping carts but ultimately leave the website without making a purchase. To overcome this hurdle and optimize sales opportunities, businesses must prioritize the implementation of efficient customer notification and insight strategies. These strategies play a vital role in recovering potentially lost sales and fostering a more successful online retail experience in today’s competitive market.
Why capture abandoned cart data?
Capturing abandoned cart data is important for ecommerce businesses as it provides valuable insights into customer behavior and helps optimize the online shopping experience. Understanding why customers abandon their carts can lead to improvements in conversion rates and overall revenue. Here are five use cases illustrating the significance of capturing abandoned cart data:
- Cart Abandonment Analysis: By collecting data on abandoned carts, businesses can analyze patterns and trends to identify common reasons for abandonment. This analysis might reveal issues with the checkout process, unexpected costs, or user experience problems that hinder conversions.
- Remarketing and Recovery Strategies: Abandoned cart data allows businesses to implement effective remarketing campaigns. By reaching out to customers who left items in their carts with targeted emails or ads, they can encourage them to return and complete their purchases.
- Personalization and Customer Retention: Understanding what products customers show interest in, even if they don’t complete the purchase, enables businesses to personalize their marketing efforts. Tailoring recommendations and offers based on these preferences can increase customer engagement and encourage repeat purchases.
- Website and Checkout Process Optimization: Abandoned cart data can help businesses pinpoint weaknesses in their website and checkout process. Armed with this information, they can make necessary improvements to enhance usability, reduce friction, and boost conversion rates.
- Product Performance Evaluation: Monitoring the rate of abandoned carts for specific products can be indicative of their popularity and potential issues. Businesses can use this data to assess the performance of individual products and make informed decisions about their inventory and pricing strategies.
Overall, capturing abandoned cart data enables ecommerce businesses to understand customer behavior better, optimize their online shopping experience, and implement effective strategies to recover potentially lost revenue. It’s a valuable resource for increasing conversions and building stronger customer relationships.
By combining these strategies, businesses can gain valuable insights into shopping cart abandonment and take proactive steps to optimize their online shopping experience, reduce abandonment rates, and improve overall sales performance.
Let’s explore how retailers and ecommerce companies can leverage Amazon Web Services (AWS) services to notify customers who have abandoned their shopping carts, re-engage with them, and encourage them to complete their purchases.
By leveraging the power of AWS services, retailers can automate and personalize these notifications, increasing customer conversions and maximizing revenue potential while addressing abandoned cart recovery. Additionally, retailers can gain insight into user interactions that encompass a wide range of actions, including:
- Clicks on links or buttons
- Views of different pages
- The duration of time spent on specific pages
- Submissions of forms
- Downloads of files
- Adding products to shopping carts
- Many other activities that take place within the digital environment
Architecture
The solution uses Amazon API Gateway, AWS Lambda and Amazon Kinesis Data Streams to ingest and process clickstream data. Amazon Kinesis Data Firehose is used to save the raw data in Amazon Simple Storage Service (Amazon S3). Then Amazon Athena and Amazon QuickSight are used to analyze and visualize the data in a user-friendly manner. Lastly, Amazon Simple Notification Service (Amazon SNS) is used to notify the customer using email reminders or push notifications.
Why did we choose these services?
Clickstream data continuously streams in as a large volume of messages, at highly-variable rates depending on user traffic and behavior. When evaluating the performance of new application features, website layouts, or marketing campaigns, it is crucial to analyze them in real-time to enable prompt actions.
The AWS services selected for this architecture offer autoscaling capabilities and cost-efficient solutions for processing clickstream and shopping cart data. These services dynamically scale resources to accommodate the fluctuations in the incoming workload, ensuring near real-time processing and analysis. With a pay-as-you-go pricing model, you only pay for the resources consumed, eliminating the need for overprovisioning and minimizing costs.
Amazon API Gateway is a fully managed service that makes it straightforward for developers to create, publish, maintain, monitor, and secure APIs at any scale.
AWS Lambda is a serverless, event-driven compute service that lets you run code for virtually any type of application or backend service without provisioning or managing servers. You can trigger Lambda from over 200 AWS services and software as a service (SaaS) applications—only paying for what you use.
Amazon SNS is It is a fully managed messaging service provided by AWS that enables developers to send messages or notifications to a large number of subscribers or endpoints (such as mobile devices, email addresses, or HTTP endpoints).
Amazon S3 is an object storage service offering industry-leading scalability, data availability, security, and performance. Customers of all sizes and industries can store and protect any amount of data for virtually any use case, such as data lakes, cloud-native applications, and mobile apps.
Amazon Athena provides a straightforward, flexible way to analyze petabytes of data where it lives. With Athena, you can analyze data or build applications from an Amazon S3 data lake and 30 data sources, including on-premises data sources or other cloud systems using SQL or Python.
AWS Step Functions is a serverless orchestration service It allows you to coordinate and sequence multiple AWS services into serverless workflows, making it easier to build, manage, and visualize complex applications.
Amazon QuickSight powers data-driven organizations with unified business intelligence (BI) at hyperscale. With QuickSight, all users can meet varying analytic needs from the same source of truth through modern interactive dashboards, paginated reports, embedded analytics, and natural language queries.
Architecture diagram
Figure 1 presents the shopping cart events data flow architecture, showcasing how the shopping cart events payload progresses through a series of steps. The customer web portal in the diagram, which serves as a digital platform, such as a website or mobile application, enables users to interact with the system. As users navigate through the web portal and add items to cart, the stream data undergoes the following stages of flow.
Figure 1 – Architecture
- The client (customer web/mobile portal) sends the shopping payload (record) to the API Gateway.
- The API Gateway transmits the record to a Lambda function, where the data is standardized.
- Lambda sends the record to Kinesis Data Streams for asynchronous processing.
- Lambda sends the record to DynamoDB to store and calls a step function to initiate a notification flow.
- Lambda(GetCart Metrics) adds these events data to an S3 Bucket.
- Aetena is used to query and analyze the data stored in the S3 bucket.
- QuickSight is used to create dashboards and display the data visually.
- Step Functions are used to trigger a simple workflow to trigger the notification to the user.
- Amazon SNS is used to send notifications to the customer about items pending ready to be checked out.
Conclusion
Addressing shopping cart abandonment is a pivotal challenge that can significantly impact the success of any online business. By understanding the root causes of abandonment and implementing effective solutions, businesses can reclaim lost revenue and enhance the overall shopping experience for their customers.
We’ve now explored a few use cases to gain valuable insights into cart abandonment. From leveraging various AWS services and user surveys to implementing personalized remarketing campaigns and optimizing the checkout process, each approach plays a crucial role in reducing cart abandonment rates.
The key takeaway is that no single solution fits all scenarios, and businesses must continuously analyze and adapt their strategies to match evolving customer needs and behaviors. By employing a combination of these tactics, businesses can create a seamless and personalized shopping journey, ultimately encouraging customers to follow through with their purchases.
As we navigate the ever-changing landscape of online retail, understanding and combating shopping cart abandonment remains a top priority for savvy businesses. By investing in customer engagement, user experience enhancements, and data-driven decision-making, businesses can forge stronger connections with their customers and unlock the full potential of their online store.
Remember, the journey to solving cart abandonment is an ongoing process. Embracing innovative technologies and staying attuned to customer feedback will undoubtedly position businesses ahead of the competition, driving higher conversion rates, and fostering lasting brand loyalty.
Contact an AWS Representative to know how we can help accelerate your business.