Loyal Guru used BigQuery to build a complete data management platform that gives retailers a single customer view with ease and efficiency.
Google Cloud Results
- Offers a highly scalable data management platform that can be customized for each client’s needs
- Enables non-technical users to run powerful queries on huge sets of data
- Allows retailers to build and deploy marketing campaigns across different channels, targeting customers based on insights
- Enables retailers to build a customer development strategy
Extracts actionable insight from terabytes of data
Every single day, consumers and companies generate huge amounts of data. One popular estimate says that 90 percent of the world’s data was created in the past two years, and the rate of generation is only increasing. For any business, capturing this data is only half the battle. Making sense of it is increasingly important and can be increasingly difficult. Loyal Guru helps retail stores separate the signal from the noise with a data management platform that can be tailored to each customer’s individual needs without sacrificing power or performance. To build such a solution, Loyal Guru turned to Google Cloud Platform (GCP).
“We wanted a scalable system that could collect, process, and analyze big datasets quickly without the need for batch processing,” says Javi Fernández, co-founder and CIO at Loyal Guru. “For us, the answer was Google Cloud Platform.”
Google BigQuery for power, scalability, and flexibility
Retail stores have a tricky challenge when it comes to Business Intelligence (BI) and data collection. Combining information from loyalty programs, online revenue streams, and sales in physical stores can lead to messy data and a lack of clarity, especially for IT departments that are under-resourced or not experts in this kind of data collection.
“We wanted a scalable system that could collect, process, and analyze big datasets quickly without the need for batch processing. For us, the answer was Google Cloud Platform.”—Javi Fernández, co-founder and CIO, Loyal Guru
That’s where Loyal Guru comes in. Customers sign up to a retailer's loyalty program for example, and grant certain privileges and permissions to the retailer in regards to the collection and use of their personal information. To make this information actionable, Loyal Guru provides the retailer with tools and APIs to collect and analyze this data to create a single customer view.
“We obtain information from various purchasing processes to create a 360-degree view of the customer and provide a smarter, more personalized omni-channel customer experience,” says Javi. “The Loyal Guru app allows retailers to run queries on the data collected, segment their customers, and send promotions via email, mobile, and even physical sales receipts. The promotions are then fully integrated with the point-of-sale systems of the retailer, all from within the platform.”
When Loyal Guru first started in early 2014, its three founders knew that they needed a powerful database solution, but this early on the team did not want to lock themselves in to any one data structure, so flexibility was an important factor. “We needed something offering a good multitenant solution as we wanted to have a completely independent infrastructure and payment system for each of our customers,” says Javi.
Loyal Guru tried a range of options, including NoSQL and PostgreSQL databases, but ran into performance issues and spent too much time on maintenance and fine-tuning. After trying the alpha of BigQuery, Loyal Guru saw a solution to its problems. In addition, for Javi, the relational data structure of BigQuery was a key feature that allowed the company to grow its data management capabilities more quickly and easily.
“We were blown away by BigQuery. You can store so much data with it. We can manage big data in a multitenant platform without any problems.”—Javi Fernández, co-founder and CIO, Loyal Guru
“BigQuery gave us the comfort of a relational structure, where you don’t have to normalize data as you would in NoSQL, but without sacrificing anything in terms of storage and performance,” says Javi. “That’s something that no other database system can offer nowadays.”
In November 2014, the company began building out its data management application on top of GCP. BigQuery was the heart of the new platform, providing not just raw power and performance but ease of use in accessing the data. With BigQuery, Loyal Guru could build a segmentation engine on its platform, allowing non-technical marketers to run complex queries on all the data available.
Since the initial implementation, the company has started converting many of its microservices from Ruby on Rails to GoLang. Currently half of them run on App Engine, taking advantage of out-of-the-box autoscaling features to maximize efficiency. Some recent additions to Loyal Guru’s product range are a mobile app for smaller retailers, which is partly hosted on Firebase, and a digital ticket purchasing system, partly hosted on Cloud Datastore.
“We were blown away by BigQuery,” says Javi. “You can store so much data with it. We can manage big data in a multitenant platform without any problems.”
One platform, many solutions
With BigQuery, Loyal Guru built a data management platform with scale and performance in mind. Loyal Guru collects and processes millions of rows of data every single day for its customers. Using the market segmentation module, retailers can access all the data on their customers in one place, making high-level queries without any technical or coding expertise for powerful insights into their markets. Based on these insights, retailers can build and deploy campaigns across different channels, all within the same platform.
“Without Google, we wouldn’t be able to do what we do. We don’t need a DevOps department. We can focus on building the best product we can for the retail industry instead of spending resources on building and maintaining a complex tech infrastructure.”—Eric Ponce, CTO, Loyal Guru
To provide such a smooth service, the company relies on GCP and its high-performance components to query terabytes within seconds. The flexibility and ease of use of BigQuery mean that Loyal Guru can open up and export its clean datasets for customers’ own third-party BI tools, providing even more value beyond the platform. This combination of power, ease of use, and added value has helped Loyal Guru and its small team win big clients like Spar and Euromadi, Spain’s biggest alliance of independent retailers, over some very experienced and well-resourced competitors.
“Without Google, we wouldn’t be able to do what we do,” says Eric Ponce, CTO at Loyal Guru. “We don’t need a DevOps department. We can focus on building the best product we can for the retail industry instead of spending resources on building and maintaining a complex tech infrastructure.”
As Loyal Guru continues to grow and win new clients, it keeps looking for ways to break new ground. It is currently redesigning its architecture to maximize performance and minimize unnecessary costs with Cloud Pub/Sub, Cloud Datastore, Cloud Dataprep, and Cloud Dataflow. As well as optimizing its existing services, Loyal Guru is exploring the possibilities of BigQuery ML to harness the power of machine learning for more powerful data analysis.
“We’d been working for a year with data scientists to see what else we could do in terms of machine learning, and then to see this coming to BigQuery, it just made me smile,” says Javi.
About Loyal Guru
Loyal Guru helps retailers maximize sales and take control of their data with a complete loyalty marketing cloud platform.