Customer 360 View is a significant aspect of digital transformation, enabling organizations to gain insights into customer behavior. Armed with this understanding, companies can make data-driven decisions to serve their customers with personalized experiences and promote growth through targeted marketing. Yet, gaining this 360 view is data-intensive and requires quick access to up-to-date information.
Digital enterprises turn to Apache Ignite and GridGain’s powerful in-memory computing to power fast, scalable, and robust customer 360 solutions. At GridGain’s core is Apache Ignite, a consistent, distributed database that facilitates high-performance computing with in-memory speed without replacing existing databases and infrastructure. Ignite stores data in memory and on disk and partitions or replicates data across a cluster of multiple nodes, providing scalability, improved performance, and resilience.
24 Hour Fitness had to overhaul its billing system to handle unprecedented closures and support millions of customers when the pandemic hit. Banco do Brasil wanted to ride the wave of digital transformation hitting the financial industry and better serve their customers. Teradata set out to offer real-time insights to their customers, driving personalized marketing and effective machine learning-based testing. Let’s explore how they leveraged the GridGain In-Memory Computing Platform to solve their data-intensive challenges, boost customer experience, enable growth, and improve resiliency.
Customer 360 View at 24 Hour Fitness: Overhauling Billing Before and During the Pandemic
24 Hour Fitness has grown to more than 280 health clubs in 11 US states over the past 35 years and boasts more than two million members. Even before the pandemic hit, they faced billing system limitations.
24 Hour Fitness sought better efficiency and wanted to reduce on-premises data storage. So, they replaced their on-premises enterprise resource planning (ERP) billing system with an SaaS system to leverage web services.
This new billing system should have been an improvement, but it presented a couple of challenges. Firstly, SaaS and vendor systems usually impose API rate limits. This rate limit is an issue when employees are querying information simultaneously across 280 clubs and millions of customers.
24 Hour Fitness needed to create purchase subscriptions, check if the customer has an active subscription, and query members by first and last name using the ‘like’ clause. The SaaS system’s API capabilities couldn’t accommodate all of those functions out-of-the-box.
When 24 Hour Fitness adopted GridGain Ultimate Edition (the enterprise version of Apache Ignite), they solved their API limitations using Ignite as an integration platform for their vendor, SaaS, and cloud systems.
Ignite solved these rate limit issues and helped 24 Hour Fitness improve their overall structure’s efficiency in many ways. They were able to consolidate all their data in one converged database, the Ignite cluster. This cluster pools data from various SaaS systems so 24 Hour Fitness can easily query the data using the Ignite Web Console.
The second challenge 24 Hour Fitness faced was the limitation on querying data live. The SaaS billing system allowed a maximum of one million input records per table after filtering. The upper limit for output records was 500,000. Since the club has over two million members, running queries against the entire customer base would fail. Integrating with Ignite solved this challenge as well.
At the peak of the COVID-19 pandemic, like many other businesses, the fitness club faced shutdowns. When 24 Hour Fitness reopened later in the year, they adjusted their subscription plans to allow for pro-rating and retroactive billing with Ignite’s help.
24 Hour Fitness’s development team ran complex queries and generated CSV files using the Ignite web console’s powerful SQL capabilities. The billing team used these files to effect mass updates on the billing system.
By working with Apache Ignite, 24 Hour Fitness overcame their billing system’s limitations and pivoted their billing to cope with the unprecedented pandemic to offer improved customer service.
Customer 360 View at Banco do Brasil: Creating Event-Driven Microservices
Banco do Brasil is the oldest bank in Brazil, and it’s the oldest bank still operating globally — and there’s a reason they’re still going strong. The financial services company has proven its resilience over the years, intentionally using modern digital solutions to serve their clients.
As the winds of digital transformation blew into the financial services sector many years ago, banks and other financial institutions began to experience massive growth in their customer base, transactions per time, and the number of channels where transactions occur simultaneously. As a result, they needed new infrastructure and software solutions to adapt to this change.
Banco do Brasil tried to use a combination of different solutions. Unfortunately, these tools couldn’t cater to their rapidly-growing customer base, didn’t implement omnichannel concepts, and offered a less than satisfactory user experience. So in 2017, Banco do Brasil began to develop their omnichannel platform called Horus.
Using Apache Ignite as the base and other components like JBoss Drools, Banco do Brasil implemented a complex event processing system. They created event-driven microservices and interface applications for monitoring, serving, and advertising to over twenty-two million monthly digital customers and visitors.
The financial organization is looking to use Apache Ignite Machine Learning (ML) capabilities to support virtual assistant functions, like voice stream, voice over Internet protocol (VoIP), sentiment analysis, and video conferencing to meet their rapidly-growing demand. In addition to their robust personal assistant, Banco do Brasil will implement some of their core banking applications using Apache Ignite resilience and finally move the Horus infrastructure to their private cloud using Kubernetes containers.
Apache Ignite enabled Banco do Brasil to remain at the forefront of digital trends like event processing and machine learning, helping serve their customers better — no matter their location.
Customer 360 View at Teradata: Enabling Real-Time Insights
Teradata Vantage is a connected multi-cloud data platform. They support a unified enterprise analytics ecosystem, providing actionable results and predictive intelligence to their clients.
To meet the needs of their clients, Teradata needed access to real-time data and insights. These real-time capabilities drive the personalized experience customers have come to expect in the modern digital world.
Teradata harnessed Apache Ignite’s capabilities for real-time campaigning. Vantage uses simultaneously-reported data to enable decision-making and connect customers to needed products, based on what’s happening at the moment. This approach dramatically improves customer relationships since clients use current, relevant trends and customer feedback to respond to changes quickly.
Teradata also used Apache Ignite for A/B testing. This technique calculates campaign effectiveness by splitting users into two representative groups (the control and target groups) using machine learning methods. The system then compares the responses between both groups.
Teradata Vantage could create the control groups using a multi-component or all-in-one solution. Each has its advantages and disadvantages regarding flexibility, administration complexity, moving data between components, training models, and more. However, Teradata preferred the all-in-one option, since they can train and deploy models on the same system, eliminating the need to move data between components.
Teradata used Apache Ignite’s features to build an all-in-one solution with many advantages. First, Ignite enabled reading and writing data to memory and the database at high speeds. It also ensured data safety during a failure or an emergency stop. In addition, Ignite enabled horizontal scalability as Teradata expands the system with new servers. Most importantly, Apache Ignite’s machine learning features enabled Teradata’s team to build predictive ML models without costly data transfers.
The image below summarizes Teradata’s current performance using the Apache Ignite solution.
Using Apache Ignite, Teradata enables clients to serve their customers better using effective control group testing and real-time data insights.
GridGain and Apache Ignite helped a variety of international companies better serve their customers across an array of use cases. Ignite and GridGain address common limitations in standard SaaS and cloud applications such as rate limits, limited functionality, sub-optimal performance, and scalability issues. Its converged database with SQL queryable objects helps organizations run queries across multiple large record systems to quickly debug and make quicker, data-driven decisions. Ignite also enables analytical queries that some SaaS systems fail to support out-of-the-box.
GridGain’s In-memory Computing Platform enables data-intensive applications with real-time data access, helping organizations enhance their customer experience. Just like the companies cited here, we can help your organization solve your most challenging problems. Learn more about Apache Ignite and GridGain and get started boosting your own digital transformation.
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