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Setting up a retail analytics software to leverage multi-contextual metrics for an electronics retail brand

Client Location


Client Industry


Services Provided

Data infused business model & Visualization system

Technologies Used

Power BI, MS SQL Server, ETL, Azure Synapse, Azure Cloud

Allocated Team Size


Project duration

28 Weeks


Client Background

Changing the retail scene in the market, our client is a renowned electronics retailer with multiple branches and hubs across the country. Known for providing excellent in-shop experience and flexible financing options among their consumers, our client has a vast base of loyal brand advocates. Right from basic to flagship electronics, their inventory is stocked with fast-moving products across different categories.


With multiple branches and storage units, our client faced problems with efficient resource accumulation. So, our client needed a central data system that could monitor the footprints of different electronics products across various regions.

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Business Challenges


Identifying the categories of the products is tedious as there are a vast number of products in the inventory.


To monitor the movement of the products, they need to be tagged and numbered in a solid, fool-proof manner including RFID tags.


The success of the product's sales depends heavily on the region and the social & economic capabilities of the people in that region.


If the data system is too complex, employees wouldn't be motivated to use the system.

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Our approach

We collected data from various dimensions for the following factors. These data are then analyzed for efficient resource handling.

Our Team

Team Structure

We handpicked the team members that are best suited for the project. Also, their ability to understand different contexts and problem-solving complemented their proficiency in tools and technologies that were necessary for the project.


Data Analyst


Cloud Architect


Quality Analyst


Backend Developer


Projects Manager


Front End Developer

Tech Stack

Tools and Technologies


Communication Tools:

  • Slack for internal communication.
  • Google meetings/Zoom for client communication.


  • Power BI
  • MS SQL Server
  • ETL
  • Azure Synapse
  • Azure Cloud

Project Management Tools

  • JIRA- Task tracking and sprint plans.
  • Github- version control.
  • Confluence- Documents management.

Solutions Offered


Business Impact



Increased the overall sales

The sales across the weakly-performing branches shot up by 300% and registered positive customer experience.



Identify key performing employees.

Our analytics system helped the client identify the star performers in individual branches and across all their outlets. Incentivizing the employees also motivated them and increased their productivity by 60%.



A deeper understanding of the supply chain

The master data allows the client to monitor the overall product flow. Seasonal sales, annual sales, demand spike, etc., could be easily tackled as the system allowed for a better understanding of the supply chain.

Frequently Asked Questions

How can a retail analytics company collect and analyze data to improve inventory management?

Surveys, sign-up forms, website or app tracking, loyalty programmes, third-party data sources, email marketing, and search engine data can all be used to collect customer data. 

Retail data analytics improves business management by assisting leaders in assessing the effectiveness of current workflows, analyzing process outcomes, automating new workflows, and refining them over time. Data also enables leaders to determine whether processes are burdensome, draining the budget, or difficult to use.

What are some of the key metrics that a retail data analytics company should track in order to optimize their sales and marketing strategies?

The key metrics in the retail analysis industry is:

  • Sales per square foot
  • Gross margins return on investment
  • Average transaction value
  • Customer retention

How can retail data analysis help businesses to identify trends and patterns in consumer behavior?

Data analytics assists retail companies in understanding their customers' purchasing needs and focusing on areas of high demand. The data-driven conclusion assists businesses in forecasting demand and managing inventory accordingly. Accordingly, retail analytics companies specialize in gathering, analyzing, and interpreting retail-related data. They provide valuable insights to their clients by utilizing a variety of tools and techniques such as data mining, machine learning, and predictive analytics.

What exactly is retail analytics?

Retail analytics is a process that collects and analyzes data on products, sales, inventory, pricing, and other factors in order to identify trends and patterns, predict outcomes, and make informed decisions. In addition to the technologies, retail analytics software and retail business intelligence tools also play a critical role in leveraging data to achieve multi-contextual metrics for a retail electronics company. By using retail predictive analytics, we can create customized dashboards and reports that provide our client with a comprehensive view of their business performance.

What role does technology play in the process of leveraging data to achieve multi-contextual metrics for a retail electronics company?

By leveraging data analytics in the retail industry, we can gain a comprehensive understanding of the customer journey, from initial awareness to purchase, and beyond. These retail business intelligence metrics include customer satisfaction levels, product performance, inventory levels, and sales trends, among others. 

The Retail 5P Dashboard is a retail analytics software that uses advanced retail industry technologies such as Power BI, SQL Server, and Azure, to collect and process data from various sources, including sales transactions, customer feedback, social media channels, and inventory levels.

What is the use of big data in the retail industry?

The use of big data in the retail industry has revolutionized the way retailers conduct business. Big data refers to the massive amounts of structured and unstructured data that are generated every day from various sources such as customer transactions, social media, website clicks, and inventory levels.

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