As a consumer, we don't know or care whether the applications we're using have 10 other concurrent users or 10 million other concurrent users. We expect a speedy, trouble-free response, no matter what. On the other hand, for the organizations responsible for supporting customer experiences, the question of how many customers need to be supported, and how processing and storage need to scale means a great deal. In this post, I will discuss the importance of scalability and how it applies to customer data management, with some customer examples.
Got Scalability? Why it Matters
As discussed in the blog "Customer Experience Trends: How To Stand Out From the Crowd", business responsiveness and scalability are vital requirements to win in the experience economy. However, delivering consistent and engaging customer experiences at scale and making an impact at the point of engagement, in the real-time, present significant challenges. The issue is particularly prevalent in industries like retail and financial services, which can contend with massive spikes in usage based on seasonality and marketing initiatives. We are noticing some businesses witnessing such spikes due to a shift to digital in retail and financial organizations responding to current market situations with loan deferment or managing the surge in refinancing.
Enterprises need a responsive data strategy so they can scale up and down based on the market environment. If an application performs well with a handful of concurrent users, that's great, but what happens when the number of users grows to millions? What happens if a system needs to go from supporting five use cases to 500? What happens when the surge goes away, and the business returns to normal. There is always this fear of over-investment and under-investment in the infrastructure. Responsive data management platforms take that uncertainty away.
Elasticity is the degree to which a system can support scaling up and down at different layers of the system architecture such as compute power, storage, UI response time, API response times. It can support the need for the burst capacity - increase in workloads or usage during peak requirements. Can the system scale seamlessly, or does the code need to be rewritten? Once usage meets a certain level, does the architecture need to be redesigned? Does more hardware need to be procured and deployed? These questions are critical, both in the near and long term. If a system can't seamlessly scale to support more users, workloads, or traffic, it can significantly constrain an organization's agility and flexibility.
Scalability for Connected Customer Data
What does scalability mean for a cloud-based, responsive data platform like the Reltio Connected Customer 360 platform?
Traditional MDM systems are typically built as a monolith and have trouble scaling. Reltio's responsive data management platform is built from the ground up to be horizontally scalable at every layer. It's a microservices-oriented architecture where we can scale the independent services as the demands come from the customer to handle peak capacity and varying performance requirements while managing infrastructure costs and giving our customers the best value for their dollar.
Reltio's customers demand consistent and reliable performance. Reltio customers are managing data at a petabyte-scale. Customers not only bring their master data, but they can also bring in their interaction and transactional data. Blending omnichannel interactions and transactions is not typical for a legacy MDM tool where you're usually restricted to bringing only your master data and encouraged to leave your transactional data at home. With Reltio, we encourage you to bring it all into the system.
Reltio's cloud-native responsive platform offers a sophisticated horizontally scaling system to deliver elastic performance that supports the throughput you need for the most demanding operational environments. Reltio can provide billions of entities and relationships through the use of our polyglot data architecture. These include Elastic Search, Cassandra, Spark, and our graph technology. These are all horizontally scalable technologies that allow us to scale up to any size of data volumes and enable our customers to include not only their master data but also their transactions and interactions. Through advanced monitoring, intelligent automation, and horizontal scaling, the platform can seamlessly support dramatic spikes with minimum human intervention.
Reltio responsive data management platform supports usage and consumption-based models allowing customers to scale up and scale down the capacity-on-demand based on the workloads. This model enables our customers to utilize burst capacity while handling scenarios such as initial data loads, the spike in usage, or during peak usage loads. It also helps the customer to save during the downturn by scaling down the resources. Customers don't have to worry about investing too much or too little in the infrastructure like they do for the on-premise solutions. Reltio takes care of it automatically by scaling services as necessary for customer workloads. When the demand goes up, the infrastructure goes up to meet requirements, and when the need goes down, we scale back down so that we're not over-provisioning allowing us to control the cost of our service to customers.
Reltio leverages highly scalable components like Cassandra, ElasticSearch, and Spark. We are able to handle high volume transactions, high volume API calls, support sophisticated analytics, and manage backend jobs for any workload. These components enable us to deploy them in an auto-scaling cloud environment. As demand increases, the infrastructure, where possible, also automatically increases to accommodate the workloads. By taking advantage of the elastic cloud technology stack, we're able to meet the service level agreements for our customers as well as scaling down when the demand is not there to give better cost optimization. We also add guardrails to make sure that there are no runaway costs to our customers by putting default thresholds on the autoscaling.
Reltio Connected Customer 360: Scalability Examples
Data innovators at global 2000 companies trust and count on Reltio to deliver the scalability required during the mission-critical business needs. The following are examples of how Reltio has helped customers scale efficiently to support their critical business needs.
Luxury Retailer Addresses Online Traffic Spikes in the Wake of COVID-19 Pandemic
Organizations in every sector are reeling as they look to contend with the impact of the COVID-19. For a nationwide luxury retailer, in-store traffic stopped, and they initiated an immediate response to provide the same in-store hyper-personalized service through their online channels, empowering their store associates to reach out to their customers with personalized offers. The situation is evolving daily, with no precedent or historical trends to reference but the team is equipped to react swiftly. With Reltio, the team was able to manage the increase in digital transactions and data provisioning they needed because their environment could seamlessly scale its service to meet the online traffic and store associates are helping to drive sales digitally.
Online Lender Supports Massive Traffic Spikes After Super Bowl Ad
A leading online lender was planning an ad placement during the 2020 Super Bowl. The Reltio platform plays an integral role in supporting the company's online loan application process, supporting several steps. In such a situation, data platform scaling is crucial as the ad is presented to an audience of 99.9 million. The solution included the customer submitting Lambda functions to the Reltio platform in parallel to drive the required seamless scaling. On the day of the Super Bowl, Reltio easily accommodated a massive one-day spike in usage, helping the company ensure loan applicants received optimal experiences and responsiveness.
Pet Supply Chain Scales to Meet Demand Spikes in Holiday Season
Between the holiday season that spans from Thanksgiving to just past New Year, an international pet supply chain typically generates the majority of its revenue. While these seasonal fluctuations are somewhat predictable, the team can't anticipate the traffic and transaction volumes in advance. The traffic is particularly high on a day like Black Friday or in current market challenges that add to uncertainties.
The retailer developed a mobile app that includes embedded inquiries to Reltio, which means the scalability of the platform is critical. If Reltio is slow, it will have a direct impact on the mobile application and the user experience. Particularly when it comes to impatient mobile app users, slow performance can translate directly to lost sales, eroding loyalty, and customer retention issues. However, with Reltio, the retailer was able to seamlessly scale to support one of the biggest days of the year, without any disruption.
Even if your organization isn't running ads in the Super Bowl, scalability and responsiveness are imperative to deliver optimized, hyper-personalized experiences that today's market demands. The Reltio responsive data management has been proven to offer the high scalability required to support the operational use cases of some of the largest enterprises for whom scalability and accelerating real-time operations is essential.
Join us for the webinar on how you can formulate your Responsive Data Strategy.