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Seller Tools

A SaaS for Amazon sellers that provides a modern toolkit to help them with research and sale automation.

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Solution and Objectives

Consolidate existing capabilities into an integrated suite of data-driven management tools tailored to Amazon sellers’ needs around business intelligence, safeguards, task automation, and omnichannel optimization. Transform chaotic multivariate data points into clear, actionable recommendations that create remarkable commercial outcomes. Package sophisticated analytics and machine guidance into easy-to-follow playbooks lifting seller strategy beyond guesswork heuristics. Drive efficiency through reliable store data connections and automation so clients can focus on high-judgment tasks.

Goal to efficiently equip over 5,000 merchants managing over $2B in Amazon revenue within the first 18 months post-launch by providing an enterprise-grade self-serve digital commerce suite catered to lean SMB budgets. Support 20%+ month-over-month subscriber growth by quantifying value in unlocking previously opaque profit growth opportunities at scale. Expand TAM long-term by localizing capabilities for international Amazon marketplaces.

Technology Planning

Built on scalable cloud infrastructure leveraging Django, MongoDB, Express, and React to facilitate secure and reliable store data connections serving thousands of unique Amazon accounts. Combined analytical databases for query efficiency with flexible NoSQL architecture to handle unstructured large-scale datasets fueling machine learning algorithms. Kubernetes cluster managed versioning and traffic load balancing while Docker containers enabled rapid parallel capability development sprints using microservices principles.

Applied agile product methodology to systematically evolve platform priorities, emphasizing foundational data services followed by the highest complexity tools integrating predictive analytics and machine learning models to prescribe lucrative business growth opportunities. CI/CD automation streamlined coding while extensive unit testing and monitoring procedures ensured system stability during growth.


Conclusion and Results

In 18 months after its launch, over 5,000 merchants trusted the platform to manage over $2B in Amazon revenue by leveraging tools tailored for e-commerce growth. The 20%+ month-over-month subscriber growth trajectory highlights strong product-market fit as existing clients also expanded usage rapidly after onboarding.

Sellers gained access to enterprise-grade business intelligence capabilities catered to lean SMB budgets, quantified in strong engagement metrics around identifying advertising performance gaps and demand forecasting for inventory planning and logistical purposes. Unlocking growth opportunities through leveraging data analytics at scale, the platform aims to level the playing field against mammoth competitors through machine leverage.

Emotcia: The solution

Key Challenge

Early technology hurdles existed around facilitating reliable, scalable store data connections across thousands of disparate Amazon accounts to fuel the platform's multivariate analytics engines while balancing security and permissions compliance.

Continual prioritization tensions posed challenges in allocating finite development resources between short-term subscriber feature requests and long-term high-complexity capabilities enabling orders-of-magnitude commercial opportunity through machine intelligence over heuristics.

Next Steps

Besides localizing capabilities for international Amazon marketplaces, the significant untapped potential exists in further personalizing automated insights and recommendations to each seller's specific business structure, stage, and objectives using machine learning.

Exploring embedded software partnership distribution models to provide suite access to agencies managing large seller portfolios also seeks to strategically drive subscriber growth.

Emotcia: The solution

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