Solutions

Data Management

In today’s digital ecosystem, organizations manage vast volumes of structured and unstructured data across multiple systems and external sources. Benori’s Data Management solutions ensure that data is accurately collected, standardized, enriched, and operationalized, transforming fragmented information into reliable, analysis-ready assets that power business intelligence, AI initiatives, and operational excellence.

What We Offer

We build scalable data foundations that aggregate information across internal platforms and external ecosystems, apply quality controls, and enhance datasets with AI-driven contextual intelligence. The result is accurate, consistent, and insight-ready data that empowers faster, smarter decision-making.

Data collection & standardization

Systematically collect structured and unstructured data from internal and external sources, then clean, normalize, and harmonize it into consistent formats, eliminating duplicates and inconsistencies to enable cross-functional analysis and decisions.

Data enrichment

Augmenting raw data with additional contextual, behavioral, financial, or market intelligence to increase depth, improve segmentation, strengthen insights, and enable more accurate decision-making.

Automation pipeline

End-to-end automated workflows that ingest, process, validate, transform, and deliver data through dashboards, alerts, reports, and downstream systems—ensuring real-time updates, scalability, and minimal manual intervention.

Data labeling & curation

Classifying, tagging, and validating data to improve relevance and searchability for downstream analytics and AI model performance. Preparing high-quality, governed datasets that are trusted, scalable, and ready for analytics, AI, and enterprise use.

Impact Stories

Our work speaks through results. From market entry strategies to competitive turnarounds, these stories showcase how our intelligence has powered real-world outcomes for global leaders.

Conducting Comprehensive SKU Data Management for a US-Based Chemical Supplier

Objective & Scope

A US-based supplier of composite materials, fiberglass reinforcements, chemicals, and consumables in North America is modernizing its business operations by implementing a new enterprise resource planning (ERP) system and enhancing its online product catalog. For this, they wanted Benori’s assistance in data enrichment of ~70,000 stock keeping units (SKUs) of their own and partners’ products. The task included: Consolidating and simplifying their database and elevating their product portfolio Updating the material attributes of their products, available SKUs, and variants, and adding descriptive notes on products in a revised database that could be easily fed into their ERP systems

Approach

Our approach used data from tax deducted at source (TDS) information, company websites, product catalogs, etc., to interpret product descriptions. The relevant attributes or features were enriched and validated using the pre-defined framework in consultation with the client. The project was executed over 12 months, with two to three weekly alignment calls and quarterly governance calls to review the output and address any bottlenecks.

Impact

The research helped the client in: Keeping their business process and product documentation up-to-date Streamlining their digitalization efforts, specifically their online presence Increasing sales through the online channel

Gathering Pricing Intelligence for E-Pharmacy Platforms in India

Objective and Scope:

The client, an India-based e-pharmacy service provider, wanted to understand pricing trends across categories at the Stock Keeping Unit (SKU) level for its key competitors. For this, it sought Benori’s support in: Scraping product information from various e-pharmacy platforms and capturing their details, including pricing Analyzing the data collected and assessing if the brand needs to refine its pricing strategy Approach

Approach:

Benori developed Python scripts tailored to each competitor’s website to scrape product details, including product name, price, and availability, across metro cities for a defined set of SKUs, encompassing over 10,000 products. The scraped data from each e-pharmacy platform was then mapped and compared in Excel. A combination of manual and technical efforts was used to create an Excel dashboard that visualized insights, including the types of products in private label categories, generic medicines, diabetes medicines, and more.

Impact:

The report helped the client in:  Compare pricing of different players and discounts offered across categories Refine their strategy around pricing, discounts, and stock availability in the four metro cities with the help of the dashboard

Benchmarking Healthcare Treatment Pricing Across Competitors

Objective and Scope:

The client, a global healthcare provider, wanted to track the pricing for a variety of treatments offered by its competitors across its clinic locations across the country. For this, it sought Benori’s support in: Creating a list of competitors, located in the vicinity of its ~400 locations, and map the largest competitors based on their reviews and services Conducting secondary and primary research on selected competitors (~2000) to understand the price points of the treatments specified

Approach:

Benori mapped clinic locations by automating the extraction of geospatial data from digital maps, followed by scanning competitor websites using web intelligence workflows to capture procedure-specific pricing. Large Language Models (LLMs) were applied to extract predefined treatment fees, while primary research addressed missing or unclear data points. The collected information was standardized into a unified dataset for like-for-like comparisons and to develop a benchmarking dashboard highlighting key pricing trends across clinics.

Impact:

Gain an understanding of the treatment timelines, delivery formats, and payment terms of the competitors Conduct a pricing analysis of competitors across the selected dental clinic locations to strategize business development

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