Retail pricing is both an art and a science. In today’s fast-paced and highly competitive consumer landscape, retailers can’t afford to have science missing from the equation.
Revionics, an Aptos company, provides enterprise retailers with leading science-based solutions for pricing, promotions, markdowns, and advanced analytics to illuminate their lifecycle pricing optimization journey. As a trusted partner for top retailers across a variety of categories, Revionics has equipped retailers with the clarity and confidence to make the right pricing decisions.
With AI and machine learning at the center, Revionics’ pricing capabilities translate consumer, competitor, and market data into actionable insights and transparent pricing recommendations for high-impact results while providing them with the most sophisticated AI to successfully navigate inflation and numerous disruptions while profitably gaining share.
Originally, Revionics built and managed their proprietary, world-class, automated data science analytics platform to process massive amounts of data on their innovative infrastructure. Revionics started on-premises, with their own data center resources, and soon extended their workflow to colocation facilities.
“Since our beginning two decades ago, we have always delivered our B2B solutions as software-as-a-service, before that was even a common term,” says Patrick Lea, Senior Vice President of Enterprise Infrastructure and Operations at Revionics.
All of Revionics’ processed customer data ultimately landed in SQL Server. Clients utilized the same architecture but were isolated in that each had a specific set of repositories and data layer that operated its own SQL Server database. Running a highly complex and intricate data model relying on everything to go in and out of SQL Server presented scalability issues and was often difficult to troubleshoot.
When the company started to expand into Europe, Revionics leveraged AWS. “We basically used their EC2 and other resources like we were operating our own data center by deploying VMs, installing the OS, and managing the applications running on those, much like the operations we were doing on our own,” says Lea. “Yet as we continued to grow, we knew we really needed the ability to massively scale, and equally important, we wanted to take advantage of new cloud-native technologies and services.”
The IT and development teams at Revionics set out to determine the best approach for the journey to the cloud with a hosting provider that could reduce expenses and match their culture of innovation and hard work.
Revionics selected Google Cloud as the platform to provide “enterprise quality, an extremely high level of service, operational excellence, and address a number of architectural, operational, and cost limitations that we had previously encountered,” says Lea.
First, Revionics started with their data warehouse and data lake, moving them from an in-house appliance-based warehouse to BigQuery. Data that used to go through SQL Server is being leveraged in BigQuery as the primary analytics platform, reducing the demand for SQL Server. All of Revionics’ remaining instances have also been ported to Google Cloud. This move allows retail customers to obtain more optimized reporting and pricing analytics at a higher frequency. SQL Server is now used solely for the application database and provides information to Revionics’ web-based UI portal.
SADA played a significant role in this cloud transformation. “SADA came in and helped us with very specific work,” says Lea. “For example, with labeling and monitoring automation, SADA helped us understand exactly what each customer is running and for how long, when they start, when they stop, and the corresponding cost implications.”
As a multiple-time Google Cloud Sales Partner of the Year, SADA can leverage its deep experience across cloud services and its expertise in emerging solutions. “Not only has SADA helped us on the operational side, but they’ve also helped us on our next-gen platform to deliver modern tools with an innovative tech stack based upon cloud capabilities for our customers,” says Lea. “With the experience SADA brings to the table, Revionics relies on them to help us mature, become enterprise scalable with world-class operational reliability, and ultimately attain a high level of success.”
As a result of working with SADA, Revionics was able to complete their migration to Google Cloud in under two years–faster than originally scheduled–and has shut down their data centers, colocation facilities, and other hosting services.
Their migration to Google Cloud increased Revionics’ capabilities by leveraging cloud-native technologies and eliminating capital investment by moving to an opex, utilization-based cost model. Revionics no longer needs to forecast and invest in infrastructure based on peak usage and can scale up or down to manage costs more effectively for their customers.
“It’s really quite amazing how flexible our system is,” says Lea. “We’re now able to optimize prices that meet the needs of our retail customers to stream transactions in real-time and hit their strategy goals.”
Revionics successfully scaled to meet business demands with over 85,000 retail locations/sales channels and 50 million active products serviced, with multiple petabytes of data processed and analyzed. All told, Revionics scaled to cover over four billion unique product-location combinations. Overall, SADA helped Revionics:
- Standardize on and migrate to cloud-native technologies via Google Cloud
- Deliver more granular cost analysis
- Improve job performance by 100X
- Gain visibility into operations and manage cloud costs effectively
- Provide their customers faster optimization time, better data security, and capability to learn and adapt AI models quicker to drive better recommendations more dynamically
“With SADA and Google Cloud, we can now scale in ways that we weren’t able to before when we were running our own infrastructure,” says Lea. “It’s an entirely different model that’s more efficient and effective, lowers cost, and increases productivity at an order of magnitude of 100X or greater, based on the number of jobs supported.”