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Last updated on July 12th, 2024

A US-based E-commerce Company Partnered With iTechnolabs For ERP System Development

6505894

800+

Mobile Apps Delivered

17+

Years of Experience

200+

Development Staff

94%

Client Retention Rate

iTechnolabs developed a data transformation engine for an e-commerce company to boost profitability with deep data analytics.

About
The Client

The client runs an e-commerce business located in Austin, Texas. They partnered with several vendors to build a product portfolio for sale on Amazon. 

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The Tech Stack

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Tech Team Composition

iTechnolabs engaged with the project by providing resources as needed, based on project requirements and stage. A Project Manager was also assigned to serve as the main point of contact (SPoC).

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The Problem Statement

The client sought to analyze their performance against competitors in the market by researching and studying their central seller data. They compared this data with similar industry sellers using the same E-commerce platform. They explored many data sources and needed support to choose the right data provider for their analysis. The client also needed DevOps support for hosting data analytics and transformation services. 

The Challenge

The client was primarily into importing and selling products on Amazon. They needed a data-driven solution to assess the viability of vendor partnerships, products, and shipments. 

The client wanted to build a system that would assess and report on the profitability of purchases, analyzing products, campaigns, offers, sales, and purchases. They wanted iTechnolabs to develop a data engine with comprehensive functionality to evaluate total profitability across product ranges and SKUs. This was to get insights into the effectiveness of client’s purchases.

The Solution

iTechnolabs’ flexible engagement model allowed the client to easily adjust their developer team. This rolling-resource-based approach aimed to reduce costs, speed up time-to-market, and add skills as needed, enhancing project flexibility. 

The project coordinator assessed the data architecture and improved it for smoother data transformation. Further, the team analyzed two data service providers, examining their datasets and APIs. They selected a provider based on factors like refresh interval, data integrity, and performance, ultimately choosing the best fit.

A MySQL database was created in AWS. An ETL library was developed to populate and refresh a MySQL data warehouse. Notifications were set up to alert about data non-availability, ensuring data is current. 

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Our Process

The team iTechnolabs followed a well-strategized process to fulfill the client’s requirements in this collaboration.

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Mapping and Vetting Developers

The collaboration started by selecting skilled resources to work on the project. With our rolling-resource engagement model, we assigned the resources based on current needs. This flexible approach ensured resources were allocated efficiently, optimizing costs throughout the project.

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Client Interviews

After selecting developers, they were introduced to the client for vetting and interviews. This process included familiarizing them with the client, their requirements, procedures, and methodologies for the project.

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Team Collaboration

The project coordinator analyzed the client’s needs thoroughly, understood the tech stack, and engineering requirements.

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Scaling Project

The team size changed as needed for the project, adding or removing members based on the progress and requirements.

The Result

iTechnolabs achieved the following outcomes for the client through their approach:

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