Download PDF
Cube Dev > Case Studies > ShopBack's Journey to Efficient Embedded Analytics with Cube
Cube Dev Logo

ShopBack's Journey to Efficient Embedded Analytics with Cube

Technology Category
  • Application Infrastructure & Middleware - Event-Driven Application
  • Infrastructure as a Service (IaaS) - Cloud Databases
Applicable Industries
  • E-Commerce
  • Retail
Applicable Functions
  • Procurement
  • Sales & Marketing
Use Cases
  • Retail Store Automation
  • Time Sensitive Networking
The Challenge

ShopBack, a leading shopping rewards and discovery platform in Asia-Pacific, faced a significant challenge in analyzing transactions on its sites. The company needed to assess various transactional aspects, including purchase value and sales volume. In January 2020, ShopBack embarked on a new project that required extensive dashboard reporting of aggregated data for both internal and external users. One of the options considered was building an in-house application and storing the data in a graph database. However, the data was highly relational and needed to be pre-aggregated into OLAP cubes for analytics. The company also faced performance issues, with p95 query loading times taking as long as 50 seconds, leading to a poor user experience.

About The Customer

ShopBack is the largest shopping rewards and discovery platform in the Asia-Pacific region, with a presence in nine countries including Australia, Indonesia, South Korea, the Philippines, Singapore, Malaysia, Taiwan, Thailand, and Vietnam. The company started with a small team of six in 2014 and has since grown to over six hundred employees across the region. ShopBack's platform enables users to make better purchase decisions while delivering performance-based marketing with high and measurable return on investment to merchants. In 2020 alone, the company powered close to US$3 billion in sales for over 5,000 merchant partners across the Asia-Pacific and awarded over US$200 million of cashback to its users.

The Solution

ShopBack decided to use Cube, a platform that was a better fit for their use case. Cube allowed the company to add new schemas and measures as their data continued to grow, while also improving the performance of their queries. To address performance concerns, ShopBack implemented pre-aggregations in early 2021, which drastically improved the performance of their Cube queries. The company also optimized their pre-aggregations with indexes and modified their approach to pre-aggregations for unique queries. ShopBack's architecture uses pre-aggregations stored in the same Postgres database and a non-clustered instance of Redis for storing fetched data and tracking the latest refreshed pre-aggregations for a multi-tenant application setup. The company also learned to pay attention to details to ensure they hit their pre-aggregations database and indexed their pre-aggregation tables to improve the performance of their queries.

Operational Impact

  • The implementation of Cube at ShopBack has led to significant operational improvements. The company has been able to add new Cube schemas and measures as their data continues to grow, while also improving the performance of their queries. The use of pre-aggregations has drastically improved the performance of their Cube queries, reducing p95 query loading times to below 5 seconds. The company has also learned to pay attention to details to ensure they hit their pre-aggregations database and indexed their pre-aggregation tables to improve the performance of their queries. Furthermore, the Cube community has been a valuable resource for ShopBack, providing answers to questions and offering collaborative support.

Quantitative Benefit

  • Reduced p95 query loading time from ~50 seconds to below 5 seconds

  • Powered close to US$3 billion in sales for over 5,000 merchant partners in 2020

  • Awarded over US$200 million of cashback to users

Related Case Studies.

Case Study
Improving Production Line Efficiency with Ethernet Micro RTU Controller
Moxa was asked to provide a connectivity solution for one of the world's leading cosmetics companies. This multinational corporation, with retail presence in 130 countries, 23 global braches, and over 66,000 employees, sought to improve the efficiency of their production process by migrating from manual monitoring to an automatic productivity monitoring system. The production line was being monitored by ABB Real-TPI, a factory information system that offers data collection and analysis to improve plant efficiency. Due to software limitations, the customer needed an OPC server and a corresponding I/O solution to collect data from additional sensor devices for the Real-TPI system. The goal is to enable the factory information system to more thoroughly collect data from every corner of the production line. This will improve its ability to measure Overall Equipment Effectiveness (OEE) and translate into increased production efficiencies. System Requirements • Instant status updates while still consuming minimal bandwidth to relieve strain on limited factory networks • Interoperable with ABB Real-TPI • Small form factor appropriate for deployment where space is scarce • Remote software management and configuration to simplify operations
Learn more
Case Study
How Sirqul’s IoT Platform is Crafting Carrefour’s New In-Store Experiences
Carrefour Taiwan’s goal is to be completely digital by end of 2018. Out-dated manual methods for analysis and assumptions limited Carrefour’s ability to change the customer experience and were void of real-time decision-making capabilities. Rather than relying solely on sales data, assumptions, and disparate systems, Carrefour Taiwan’s CEO led an initiative to find a connected IoT solution that could give the team the ability to make real-time changes and more informed decisions. Prior to implementing, Carrefour struggled to address their conversion rates and did not have the proper insights into the customer decision-making process nor how to make an immediate impact without losing customer confidence.
Learn more
Case Study
Ensures Cold Milk in Your Supermarket
As of 2014, AK-Centralen has over 1,500 Danish supermarkets equipped, and utilizes 16 operators, and is open 24 hours a day, 365 days a year. AK-Centralen needed the ability to monitor the cooling alarms from around the country, 24 hours a day, 365 days a year. Each and every time the door to a milk cooler or a freezer does not close properly, an alarm goes off on a computer screen in a control building in southwestern Odense. This type of alarm will go off approximately 140,000 times per year, equating to roughly 400 alarms in a 24-hour period. Should an alarm go off, then there is only a limited amount of time to act before dairy products or frozen pizza must be disposed of, and this type of waste can quickly start to cost a supermarket a great deal of money.
Learn more
© 2015-2024 IoT ONE Limited | Privacy Policy

Contact us

Let's talk!

* Required
* Required
* Required
* Invalid email address
By submitting this form, you agree that IoT ONE may contact you with insights and marketing messaging.
No thanks, I don't want to receive any marketing emails from IoT ONE.
Submit

Thank you for your message!
We will contact you soon.