Fave Case Study: Empowering users to make data-driven decisions
How Fave manipulated their raw data to create insights, making precise data-driven decisions across every department by using Holistics.
Holistics helps different teams understand what data they have, look into the raw data, and see what insights they can find, rather than coming to the Business Intelligence team. So they are more empowered to use data to make decisions.
Head of Business Intelligence, Fave
Fave Asia Technologies is the creator of Fave, an online platform that provides discounted offers on things to eat, do, see, and experience in a city. It operates in several cities in Malaysia and Indonesia, as well as in Singapore.
Fave Asia Technologies started out with one main product—KFit, which offered access and discounts to fitness activities. In 2017, it bought Groupon’s business in Malaysia, Indonesia and Singapore, and pivoted to become a group deals platform.
That same year, the company launched FavePay, an online-to-offline (O2O) payments platform that people can use at Fave-registered merchants’ brick-and-mortar outlets by simply scanning a QR code.
An extremely unscalable spreadsheet process
Fave has two types of customers—shoppers and merchants. Given their platform strategy, signing up as many of both types of customers as possible is key, and to keep them using the platform.
One way to do that is to shorten the time it takes to get merchants on board and to have them launch their deals on the app. Another is to provide them with in-depth insights into how their deals are performing.
The Fave team also focuses on making it more convenient for people to buy deals and use them at merchant stores—hence, the mobile payments feature. But Fave is also interested in enhancing and personalizing its marketing efforts to get people to buy more deals.
At first, Fave used Google Sheets to track and make sense of data on the usage of both the Fave app and FavePay. But it soon became unsustainable.
“It was a very messy, manual process,” says Amos Tay, the head of Fave’s Business Intelligence team. The system relied on employees updating the sheets regularly, and making sure every entry was accurate. “[Imagine] if anyone deletes a cell or accidentally deletes the entire sheet. That’s an extremely unscalable process.”
Enabling data analytics access for every team within Fave
Fave decided it was time to find an intuitive business intelligence platform. They selected Holistics and began using it in 2016. They connected their own AWS data warehouse to Holistics, as well as their PostgreSQL database. They also made a replica of their production database to feed real-time data to Holistics.
Now, around 70% of Fave’s 200+ employees in Malaysia, Indonesia and Singapore use Holistics to access data and make data-driven decisions. They track a wide range of data, such as:
- Industries and merchants driving sales
- Number and value of transactions
- Number of customers
- Source of sales
- Use of promotional codes
- Cancellations of deals
- Customer retention per merchant
Fave also collaborates with other major companies, such as AirAsia and Grab. Sales, marketing, operations and other teams monitor the performance of these projects and assess how well they attract customers to the platform.
“Last thing I checked before going to sleep, is to look at my email from Holistics to show how our performance is versus yesterday versus same day last week, which is pushed to me hourly,” says Chen Chow Yeoh, Co-Founder of Fave. “More than half of the emails that I clicked to read each day is emails from Holistics.”
One thing we really appreciate about Holistics is how good the support is. [Whether via] Slack or email, we almost immediately get a response. That’s something we can’t really find in bigger companies.
– Amos Tay, Head of Business Intelligence, Fave
How Fave uses Holistics
This level of accessibility came especially handy when Fave acquired Groupon. During the transition, they had to transfer both merchants and users to their own platform.
The Business Intelligence team, which consists of seven analysts, built dashboards on Holistics to monitor the transition daily and put out fires if any part of the system broke down. They monitored whether or not they were losing users, and if so, how many. They were able to see how many Groupon users started using Fave. They were able to notice platform issues and respond to them quickly.
Whenever merchants sign up to join the Fave platform, they go through various stages, such as editorial content production, quality assurance, setting up of deals and more. The operations team tracks this process closely and aims to reduce the time the merchant takes to go through each department.
This eases the process for the merchant and also helps prevent them from dropping out of the process. Most importantly, it helps them to start selling deals earlier.
The company’s top management also stay on top of data such as hourly sales. Using Holistics’ email scheduler, the Business Intelligence team sends them multiple reports throughout the day and week.
“Data from Holistics is being used as single source of truth,” says Chen Chow. “So, if I see any poor performance on any category or city, I would often put the business and business intelligence folks into email and ask, whether business is having problem or data is having problem. It must be one of the two that is the issue.”
Great to see Holistics been growing with us over the past 2 years plus, and looking forward for many years working together. I have always strongly recommended Holistics, whenever startup founders asked me which is the best way to get their data reporting.
– Chen Chow Yeoh, Co-Founder, Fave
A Data-driven Future
Future Of Data at Fave
“Today, we are already a data-driven organisation. But still, we are not fully using the capabilities of what data can give us,” says Amos. They plan to build machine learning models to improve their deal recommendations to customers. They can also push deals to customers based on their location.
Amos notes that the ability to actually access raw data has helped different teams within Fave to understand where all the information is coming from. They have also learnt how to manipulate the data to make decisions.
The company has emerged from what Amos jokingly called “the early uncivilised stages of data” to becoming a data-driven organisation that makes informed decisions and uncovers deep insights. “Now, users have a single source of truth.” he says.
Tips & tricks from the Fave team
As your company grows, you may need to place a dedicated data analyst in each department. Fave is looking at having analysts in the marketing, operations, sales, and other teams within the company. This reduces bottlenecks by allowing each team to run autonomously in terms of how it accesses, manipulates, and visualizes data.
If your organisation already uses data to make decisions, and has robust data infrastructure and management systems in place, it may be time to take the next step of building machine learning models.
Email Schedules are great for delivering data to internal stakeholders as well as partners, use it liberally.