This case study delves into the obstacles faced by an immersive commerce platform company’s team in gaining real-time insights into user activities, product interactions, and purchasing behavior for their immersive commerce platform.
This case study outlines the hurdles faced by a supply chain management software company in establishing a scalable and high–performing search infrastructure while meeting compliance requirements. With the assistance of 9acts, the company successfully implemented AWS OpenSearch Service, a fully managed search solution, to address these challenges and achieve their goals.
About The Company
The immersive commerce platform company is a retail-tech firm that enables the development of an immersive commerce platform to help brands, retailers, and wholesalers create unique virtual stores and showrooms in the metaverse. These virtual stores form a strong and memorable connection between brands and their customers, increasing discovery, conversion, and retargeting KPIs.
The immersive commerce platform company encountered a significant challenge. They needed to acquire real-time insights into user activities, product interactions, and purchasing behavior. Traditional data analytics solutions proved insufficient in providing the speed and granularity required to enhance customer experiences, offer personalized recommendations, and address issues like cart abandonment. The colossal volume of data generated by millions of users necessitated a sophisticated and scalable approach to enable timely, data-driven decision-making.
To meet this challenge, we devised an innovative solution with Amazon Kinesis at its core, a stateof-the-art real-time data streaming and processing service. Our strategy involved the expert configuration of Amazon Kinesis Data Streams, Kinesis Data Analytics, and Kinesis Data Firehose to precisely align with the unique requirements of our e-commerce clients.
Amazon Kinesis Data Streams, a fundamental component of our solution, empowers us to seamlessly ingest data from a diverse array of sources. This comprehensive approach ensures that data is captured and processed in real-time as it is generated, leaving no room for missed interactions or transactions.
Amazon Kinesis Data Streams is designed for scalability, making it ideally suited to handle highvelocity data streams. It adeptly manages surges in data traffic during flash sales, product launches, and peak periods. As data volume continues to grow, we can dynamically add extra shards to efficiently accommodate the increased workload.
Leveraging Amazon Kinesis Data Analytics, we engage in real-time data transformation by employing SQL-like queries to enhance raw data with enriched insights from customer profiles, product information, and other pertinent data. This approach results in the creation of a holistic view of user activities, fostering a deeper understanding.
Amazon Kinesis Data Analytics equips us to conduct real-time data analysis, providing us with the capability to construct queries, compute metrics, identify patterns, and trigger alerts. The outcomes are promptly visualized on real-time dashboards, delivering immediate insights to guide well-informed decision-making.
These real-time insights revolutionized our clients’ understanding of user interactions with their virtual stores. This heightened awareness facilitated the optimization of virtual store layouts, elevating user engagement and enabling the delivery of personalized product recommendations during user exploration. This had a significant impact on boosting cross-selling and upselling opportunities. Furthermore, real-time insights enabled our clients to swiftly identify and address cart abandonment, leveraging automated responses such as personalized emails to encourage users to finalize their purchases.
Our Amazon Kinesis configuration is meticulously designed to allow for effortless scalability, adapting to the evolving demands of growing data volumes and user requirements. The transition from batch processing to real-time data analytics empowered our clients to make prompt data-driven decisions, enhancing both efficiency and agility.
Our solution had a transformative impact on our e-commerce clients, enabling them to gain realtime insights into user activities, product interactions, and purchasing behavior. With Amazon Kinesis, we achieved remarkable results, including:
20% Increase in Conversions: Real-time insights allowed our clients to optimize their virtual store layouts and user experiences, resulting in a 20% increase in conversion rates. The personalized recommendations made during user exploration led to more significant cross-selling and upselling
45% Reduction in Cart Abandonment: By promptly detecting and addressing cart abandonment, our clients managed to reduce abandonment rates by 45%. Automated responses, such as personalized emails with enticing offers, played a crucial role in converting abandoned virtual carts
into completed purchases. Effortless Scaling: The system’s design allowed for dynamic scaling to meet growing data volumes and evolving user needs. During peak periods, our clients managed the surge in virtual traffic
Enhanced Data-Driven Decision Making: Transitioning from batch processing to real-time data
analytics empowered our clients to make data-driven decisions promptly. The insights from realtime dashboards led to improved efficiency and agility.
In conclusion, our implementation of Amazon Kinesis had a profound impact on the immersive commerce platform company’s clients’ operations, resulting in substantial improvements in conversion rates, cart abandonment reduction, and data-driven decision-making. This case study
underscores the importance of Amazon Kinesis in enabling real-time data analytics and personalized, user-centric experiences in the competitive e-commerce landscape.