eCom Engine's SaaS products had hit market saturation — growth required expanding into analytics, but the team had zero in-house expertise and no clear technology path. RTS Labs ran a 6-week discovery and Azure Data Explorer proof of concept that gave them the architecture, tooling, and roadmap to ship 6 customer-facing analytics reports by year-end with a 2.5-person team.
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eCom Engine has served Amazon sellers for nearly 20 years through two core SaaS products: FeedbackFive for managing customer feedback and reviews, and RestockPro for inventory management. Both products had reached a point of market maturity — well-established, but with limited room for organic growth in their respective niches.
The company identified analytics as the next frontier: building data-driven features and reports that would add new value for Amazon sellers and differentiate the product suite. The problem was that eCom Engine had no internal analytics expertise, no established tooling, and no clear view of which technology path — Azure, AWS, or on-premises — would best fit their existing infrastructure and team capabilities.
FeedbackFive and RestockPro had reached maturity in their markets, leaving limited avenues for product-led growth. Analytics represented a new value layer, but required capabilities the company didn’t yet have.
The internal team had no experience with analytics tooling — ADX, Power BI, Synapse, or otherwise. The landscape of options was overwhelming, and choosing the wrong stack would mean costly rework down the road.
Ecom Engine was undecided on infrastructure direction: stay on Azure, migrate to AWS, or move to on-premises. Without a clear architectural view, new product development was stalled.
RTS Labs began with a structured architecture discovery — reviewing eCom Engine’s existing Azure infrastructure, analyzing usage and costs, and gathering non-functional requirements around scalability, availability, and observability. Rather than prescribing a solution upfront, RTS evaluated all options (Azure, AWS, on-prem) before recommending a path. The engagement culminated in a targeted proof of concept with Azure Data Explorer, demonstrating how ADX could ingest and process eCom Engine’s data at scale — giving the team a hands-on foundation before committing to a full build.
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