Editor’s note: Today we hear from NTUC Enterprise, which operates a sprawling retail ecosystem, including NTUC FairPrice, Singapore’s largest grocery chain, and a network of Unity pharmacies and Cheers convenience stores. As a social enterprise, NTUC Enterprise’s mission is to deliver affordable value in areas like daily essentials, healthcare, childcare, ready-to-eat meals, and financial services. Serving over two million customers annually, NTUC Enterprise strives to empower all Singaporeans to live more meaningful lives.
In August 2021, NTUC FairPrice launched a new app payment solution, allowing customers to pay for purchases and accumulate reward points at any FairPrice store or Unity pharmacy, by simply scanning a QR code. The app eliminates the need to present a physical loyalty or credit card and integrates all customer activities across NTUC FairPrice’s network of stores and services. By using the FairPrice app’s payment feature, customers enjoy a seamless checkout experience at all FairPrice and Unity outlets.
The mission to build an integrated app across a network of over 200 stores encountered two challenges that we were able to overcome with Google Cloud solutions, namely Cloud Functions, BigQuery, and Cloud Run:
Financial reconciliation: FairPrice transactional data sits in multiple locations, including the point-of-sale (POS) server, the FairPrice app server, and the payment gateway (third-party technology used by merchants to accept purchases from customers). For the app to work, our finance team needed to ensure that all sales data coming from disparate sources are tallied correctly.
Platform stability: Instead of a staggered rollout, we opted for a ‘big bang’ launch across all FairPrice and Unity stores across Singapore. System resilience, seamless autoscaling, and a near-zero latency network environment were critical for ensuring that customers weren’t stuck in line due to network delays or outages, especially during peak hours.
For a complex operation such as ours, the main technical hurdle was agile syncing between transaction systems. Our finance team needed to ensure that all funds that land in the bank correspond with sales made through our stores’ POS machines. Resolving this issue required a custom solution that integrates disparate data sources across the sales spectrum.
At the time, the architecture of our sales system was as follows:
The POS system processed a transaction and sends the data into our SAP network. From there, the data was funneled through enterprise resource planning (ERP) workflows managed by the finance team.
The actual financial transaction, however, was performed on our FairPrice app server. This communicated with a third-party payment gateway that then transferred funds electronically to our bank.
The POS system was sophisticated enough to aggregate different payment methods registered in the FairPrice app, from GrabPay to Visa and Mastercard, and send granular transactions information to finance. But given that it wasn’t executing actual transactions, finance then needed to make extra reconciliations to ensure that the POS data and payment data corresponded. This process placed a significant manual strain on the team, which would only increase as the business continued to grow.
Automating financial processes to drive business growth with cloud technology
To automate financial reconciliation, we used Google Cloud tools and designed a custom solution to integrate POS data with the payment network. Here’s a step-by-step summary of how we integrated all the elements of our transactions ecosystem, unlocking the potential for growth in our FairPrice app:
We first worked with the POS team to set up real-time data pipelines to import all transactional data across our retail network, from online sales to physical store purchases, into Cloud Storage every five minutes.
Next, we deployed Cloud Functions to detect changes made in Cloud Storage, before processing the data and syncing it with BigQuery, our main data analytics engine for data imported from POS systems into SAP systems.
Leveraging CloudSQL as our main managed database, we created data pipelines from the app server into BigQuery. We created two parallel channels to ingest datastreams into BigQuery, which then became a unified data processing engine for unlimited, real-time insights.
At that point, we used Google Cloud Scheduler to send BigQuery data analytics at the end of each day to a SAP secure file transfer protocol (SFTP) folder for processing by the data analytics team.
Combining readouts from these two data sources, our data scientists can now build an easy-to-read Data Studio dashboard. If transactions from different systems do not match up, an email alert will be sent to the finance team and other platform stakeholders.
Finance then reconciles the transactions in Data Studio to ensure all sales from the POS system and the app server correspond correctly.
Combining the power of BigQuery with the convenience of Data Studio provided us with an additional advantage: the finance team, without requiring in-depth technical knowledge, can now easily obtain any piece of data they need without seeking help from the engineering team. The finance team can directly query what they need in BigQuery, and create an instant visualization on the Data Studio dashboard for any business use case.
Keeping customers happy with seamless autoscaling driven by Cloud Run
One of the key objectives of launching Pay for our FairPrice app is to enable faster, more seamless checkouts across all stores in our retail network, through quick-and-easy QR code scanning. With a ‘big bang’ rollout, we needed the most powerful and agile computing infrastructure available to handle fluctuations in footfall at our stores, from peak lunchtime to dips in the middle of the night.
We sought to combine this ability to autoscale with minimal infrastructure configuration, so our development team could focus on building innovative solutions that delight our customers.
Google Kubernetes Engine (GKE) had been powering NTUC FairPrice solutions for a long time. When it came to developing our new payment solution, we decided that it would be a good time to try Cloud Run, cognizant of the complex interplay of APIs required to evolve the app. The aim was to see if we could achieve even more automation and ease-of-use in scaling and deploying our solution.
The experiment paid off as we gained a new dimension of API agility through the optimized deployment of Cloud Run features. Here’s an overview of how we leveraged Cloud Run to support failure-free store operation with virtually no manual configuration:
Default endpoints: Our FairPrice app deploys a wide range of proprietary APIs to synchronize all aspects of the solution. Cloud Run’s key advantage here is that provides a secure HTTPS endpoint by default. This automates the connection of APIs to software programs, removing the need to set up extra layers of network components to manage APIs. Ensuring this strong connectivity results in a seamless experience for shoppers.
Automated configuration: Even with Autopilot, the new GKE operating environment, we still needed to set up CPU and memory for our microservices clusters. With Cloud Run, we’re freed from this task. All that is required is to set the maximum instance variable, and Cloud Run takes care of the rest, by automatically scaling microservice clusters in real-time according to our needs.
This saves our DevOps team several hours per week, which they can devote to developing new features and updates for the FairPrice app. Ultimately, this convenience is passed on to our customers, translating into a more seamless and enjoyable shopping experience.
In just one year since launching Pay for the FairPrice app, we have gained measurable benefits from the innovations enabled by Google Cloud tools:
A 90% rate of return to the app. This means that nine out of 10 customers who use the app once will continue using it for subsequent purchases.
Added nearly 270,000 new FairPrice customers to the app, and that number is growing at an exponential rate.
Since launching the app, we have been able to convert 6% of offline transactions into digital transactions.
Given that app availability and seamless end user experiences are major factors in Net Promoter Scores (NPS), NTUC FairPrice has achieved ~75% in overall customer satisfaction.
Building Singapore’s food “super app” with Google Cloud tools
We’re excited about the next stage of our digital evolution, which is to turn the FairPrice App into a food ‘super app.’ We aim to spark customer delight in everything related to food within the NTUC FairPrice Group network. This includes “hawker centers” (food courts), restaurants, deliveries, and takeaways.
All of these services will be built on Google Cloud solutions, in particular Cloud Run and BigQuery. We believe that with our newfound autoscaling and data analytics capabilities, NTUC FairPrice is ready to bring the business to new heights, and meet Singapore’s appetite for great food.
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