Retail Business Intelligence
Key functionality, integrations, costs, benefits, and more
ScienceSoft presents an overview of features, integrations, success factors, cost components, and benefits of retail business intelligence solutions.
Retail Business Intelligence: Definition and Benefits
Retail business intelligence (BI) solution is used to collect, process, and analyze retail-specific business data and present relevant insights for the decision makers in the retail sector to:
- Increase customer satisfaction and improve customer retention.
- Optimize and plan assortment.
- Plan marketing campaigns.
- Identify new sales opportunities, etc.
Retail BI Solution: Core Functionality
At ScienceSoft, we tailor retail BI solutions to the specific business processes of our customers. Here, we’ve compiled a set of solution features commonly requested by the retail organizations we work with.
Customer relationship management (CRM) software
- To identify most valuable customers and customer segments and concentrate marketing and sales efforts accordingly.
- To analyze customer engagement, customer satisfaction, profitability, attrition, etc. across customer segments.
Ecommerce platform
Tracking metrics like the conversion rate by devices (PC/tablet/mobile), average order value, revenue and product/service preferences by customer segment, advertising channel performance, return on ad spend, etc. to:
- Analyze sales performance.
- Gain an insight into customer behavior.
- Measure the effectiveness of marketing campaigns, etc.
Point of sale system
- To track customers’ spending habits (preferred payment methods, purchase time, etc.).
- To identify popular product/service bundles.
- To measure promotion effectiveness.
- To assess store performance.
Customer service software
- To determine gaps in customer service, product assortment, etc.
- To create and optimize customer retention strategies for particular customer segments based on the analysis of customer service requests together with customer behavior.
- To analyze customer sentiment for optimized customer service, store product assortment, etc.
Marketing campaign management software
- To create marketing campaigns and optimize marketing activities (upselling and cross-selling, markdown strategies, etc.).
- To measure the success of marketing efforts.
Inventory management software
- To analyze inventory performance and maintain the optimal inventory stock levels.
- To prevent lost sales and decrease operational costs by optimizing store transfer, replenishment and inventory allocation activities.
Supplier management software
- To analyze supplier performance and conduct supplier benchmarking.
- To analyze supplier product performance (top and bottom performing products by supplier).
- To establish the cause-effect relationship between supplier performance and product cost/profitability/sales, etc.
Self-service analytics and reporting capabilities
Business users with different levels of tech expertise can rely on drag-and-drop functionality, natural language querying support, and highly customizable dashboards to access data independently and support their decision-making.
A set of data source connectors and easy-to-use APIs
To allow for seamless integration with the existing IT infrastructure and reduced development costs in case of the addition of new data sources.
Automated data management processes
To improve decision-making by reducing the time consumed for retail data ingestion, aggregation, and analysis and eliminating error-prone manual data management activities.
Data security focus
To secure highly sensitive customer and financial data, meet regulatory compliance requirements (e.g., GDPR) and enable secure data access and sharing across different employee levels with fine-grained access control, multifactor authentication, dynamic data masking and anonymization, end-to-end data encryption, etc.

Design and Implementation of a Comprehensive Data Analytics Solution
- 360-degree customer view across all the channels and business directions.
- Rich retail analytics, e.g., traffic and convertion, engagement, wish lists.
Cost Factors and Benefits of Retail Business Intelligence Implementation
The cost of retail business intelligence implementation varies greatly depending on a number of factors, such as:
- Number of retail data sources (CRM, ecommerce platform, customer service software, etc.), their integration capabilities, existing data models.
- Retail data complexity (in terms of size, structure, variety, etc.).
- Complexity of retail data cleansing.
- Complexity of the retail data storage layer (data warehouse, data marts, a data lake, etc.).
- Types of retail analytics required (presence and number of ML algorithms, if streaming or big data analytics is required, etc.).
- Complexity of data reporting and visualization (number and complexity of reports, including ad hoc reports, number of dashboards, if custom data visualization is required, etc.).
- User permission system complexity.
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The cost of a retail BI implementation project, which involves developing a centralized data warehouse with data marts for retail data storage, OLAP cubes, and self-service reports and dashboards may cost as follows:
* Software license fees are NOT included. |
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The implementation of retail business intelligence enables:
Microsoft Power BI
Best for
Retail data visualization and reporting.
Description
- 120 + native data source connectors including connectors for Azure services (Azure Synapse Analytics, Azure Cosmos DB, Azure Data Lake Storage, etc.) and third-party solutions (Google Analytics, Salesforce Reports, etc.).
- Self-service data preparation and analytics capabilities for non-tech users to run data analysis, create reports and dashboards.
- Scheduled and ad hoc reporting capabilities.
- Interactive reporting and dashboarding capabilities to drill down, drill through and filter retail data.
- Creating dashboards with out-of-the-box visuals (charts, cards, maps, matrix, etc.) and custom visuals created with the Power BI open-source visuals framework.
- Robust data security (data sensitivity labeling, end-to-end data encryption, real-time access monitoring, etc.).
- Cloud and on-premises deployment.
Pricing
- Power BI Desktop – free.
- Power BI Pro – $9.99/user/month.
- Power BI Premium –$4,995/dedicated cloud storage and compute resources/month with annual subscription.
Azure Synapse Analytics
Best for
Enterprise-scale retail data warehousing.
Description
- 90+ pre-built data sources connectors for ingesting structured, semi-structured, unstructured retail data from SQL and NoSQL databases, data lakes, operational data stores, third-party applications backed up with Azure Data factory.
- Native integration with the Azure ecosystem (Azure Data Lake Storage for data lake setup, Azure Data Factory for ETL, Azure Stream Analytics for streaming analytics, Power BI for BI and data visualization, Azure Machine Learning, Azure Cognitive Services for artificial intelligence and ML management, etc.).
- Reporting on all management levels, from the C-suite to department heads, managers and supervisors, is protected with a fine-grained data access control (granular permissions on schemas, tables, views, individual columns, procedures, other objects).
Pricing
- On-demand pricing: $1.20/hour (DW100c) - $360/hour (DW30000c).
- Reserved instance pricing can save up to 65% over the on-demand option (in a 3-year term).
- Data storage: $122.88/TB/month.
Amazon Redshift
Best for
Data warehousing for omnichannel retail analytics.
Description
- Native integration with a data lake (Amazon S3) to enable querying exabytes of structured, semi-structured, and unstructured data for analysis without loading and transformation.
- Native integration with the AWS analytics services (AWS Glue for ETL, Amazon Kinesis Data Firehose for streaming analytics, Amazon EMR for big data processing, Amazon QuickSight for BI and data visualization, Amazon SageMaker for ML management, etc.)
- Manually enabled end-to-end data encryption, granular row-level and column-level security controls.
Pricing
- On-demand pricing: $0.25 - $13.04/hour.
- Reserved instance pricing offers saving up to 75% over the on-demand option (a 3-year term).
- Data storage (RA3 node type): $0.024/GB/month.
Note: No charge for the amount of data processed.
Consider Professional Services for Retail BI Implementation by ScienceSoft
Since 2003, ScienceSoft has helped companies from the retail industry achieve analytics transparency and set up company-wide reporting to aid their decision-making and enhance customer understanding, balance supply and demand, cut operational costs and drive sales.
Retail BI implementation consulting
- Retail BI needs analysis.
- Retail BI solution conceptualization, architecture design and tech stack selection.
- Retail BI implementation planning (milestones, risk management planning, optimal sourcing model, defining KPIs for measuring BI software quality, etc.).
- Business case creation, including cost estimation, time budget estimates.
Retail BI implementation
- Analysis of retail BI needs and drawing up BI software requirements.
- Conceptualization and tech selection for a retail business intelligence solution.
- Iterative retail BI solution development.
- Retail BI solution quality assurance.
- After-launch support and optimization.
About ScienceSoft
ScienceSoft is an IT consulting and software development company headquartered in McKinney, Texas. We help midsize and large companies in retail digitalize their data management and analytics processes and optimize business performance with all-around business intelligence and analytics services. Being ISO 9001 and ISO 27001 certified, ScienceSoft relies on a mature quality management system and guarantees that cooperation with us does not pose any risks to our customers’ data security.