Analytics at Scale: Leverage automated subscriber data with Recurly
Why are subscriber analytics important?
Subscription analytics are crucial for overall business growth. It enables businesses to stay competitive and relevant in a rapidly evolving digital landscape where customer preferences and behaviors are continually changing.
With the right set of data, you can, among other things:
Find valuable insights into how customers interact with your product–identify patterns, preferences, and pain points to optimize your strategies.
Divide your audiences into cohorts for personalized campaigns more likely to resonate with customers and lead to higher conversion rates.
Identify at-risk customers and proactively enhance customer satisfaction and loyalty to ultimately reduce churn.
Assess the performance of your marketing channels, campaigns, and initiatives, helping you refine your strategy and allocate resources more effectively.
Benchmark your performance against competitors and identify areas for improvement.
How Recurly Analytics work
At Recurly, scaling analytics means detailed and aggregated data availability, consistent innovation, and snappy response times for all our customers–no matter their size.
Recurly utilizes Google’s flagship BigQuery database product to provide web-speed analytics after processing and aggregating billions of rows every half an hour to provide hourly updates to its breadth of Analytic reporting.
The BigQuery platform uses a custom in-memory solution with powerful network multiplexing to complete multi-terabyte processes in just minutes while providing near-instantaneous row lookups.Â
As a fully managed service, it eliminates the burden of infrastructure management, allowing our team to focus on data analysis and insights. Its architecture distributes data processing across multiple nodes, ensuring efficient handling of large and growing datasets.
Additionally, it dynamically adjusts resources based on demand, guaranteeing optimal performance during peak times while reducing costs during lower usage periods. This flexibility enables us to adapt to changing workloads without manual intervention–a game-changer.Â
By employing a distributed columnar storage system and parallel query execution, it can process complex analytical queries with remarkable speed. This capability significantly accelerates our data exploration and decision-making processes.
Furthermore, the platform seamlessly integrates with other Google Cloud services, such as Dataflow and Cloud Machine Learning Engine. This integration empowers us to build end-to-end data pipelines and implement advanced machine learning models on our data, all within the same ecosystem.
This allows the Recurly product team to innovate in the analytics space without worrying about taxing backend systems or concerns that the reporting will be costly or non-performant.
Recurly Analytics at scale
Our customers are able to use the resulting analytics to provide views into the traditional subscription reporting metrics like MRR and ARR, churn, gateway transactions, cohort retention, plan performance analysis, revenue recovery, and more.
Recurly’s recent innovations include drill-to-detail reports, regional around-the-globe mapping of transactions, forecasting capabilities, and build-your-own explore reports within the application using off-the-shelf report tools to provide ease of use and ready-made documentation to support customization.
Want to learn more about scaling subscription infrastructures?
Scaling IT infrastructures is a common challenge for subscription businesses. Technology teams are often spread too thin across demands for product innovation, business scalability, and running a recurring billing system.Â
Hear from Tony Allen, Recurly CTO, and Andrei Rebrov, Scentbird CTO, and discover how to build an unshakeable foundation that supports the performance and security risks subscription companies face.