Sevendata

The Challenges

In a market where personalization can increase conversion rates by over 200%, data accuracy makes the difference between a targeted action and wasted investment: every inaccuracy in a database inevitably leads to missed conversions.

During the data acquisition process from the official source Infocamere, Sevendata identified structural issues related to ATECO codes, resulting in several critical challenges:

• Official data not reflecting reality, with a direct impact on ROI
  Company classification, based solely on public records and ATECO codes, proved limited and often misaligned with actual business activities. Incorrect or overly generic classifications compromised targeting strategies, exposing end customers to inefficient and scattered marketing investments.
• Erosion of perceived value and trust
  Poor data accuracy directly affected the quality of the data packages sold, reducing their perceived value. End customers found themselves investing time and resources in off-target contacts, negatively impacting both their trust in data as a strategic asset and the overall reputation of the service.
• Lack of a structured data validation process
  Despite the known limitations of official sources and reliance on ATECO codes, there was no systematic process for verifying and updating information. Any validation activities were carried out manually and retrospectively, resulting in high costs and limited scalability.

The Solution

beSharp enabled Sevendata to implement a data augmentation solution powered by Agentic AI, further enhanced through the use of Retrieval-Augmented Generation (RAG) techniques.

This approach allowed the company to move beyond the limitations of outdated records and imprecise standardized labels, accurately identifying the true operational sector of each business and providing highly reliable classification suggestions.

With beSharp’s support, Sevendata transformed its data assets into a true strategic resource for end customers, fundamentally reshaping its data enrichment strategy.

The Outcomes

The introduction of the new model turned data quality from a challenge into a strategic lever, redefining Sevendata’s market positioning.

Data Quality and Precision Targeting

The accuracy of company classification significantly improved, reaching between 85% and 93%. This level of precision elevated data packages into a premium offering, enabling advanced targeting that drastically reduces wasted ad spend and maximizes conversion potential.

Cost Optimization

Eliminating reliance on external providers for data validation led to immediate cost savings. A substantial recurring expense was replaced by a highly efficient internal infrastructure, maximizing project ROI and freeing up resources for innovation.

Faster Go-to-Market

Centralized and automated data management eliminated manual inefficiencies. The ability to continuously process millions of records and quickly update datasets now allows SevenData to respond rapidly to market demands, delivering targeted offerings with unprecedented speed and flexibility.

Full Autonomy Through Knowledge Transfer

Thanks to a comprehensive knowledge transfer program delivered by beSharp, SevenData’s team gained full ownership of the solution. Today, the company is fully autonomous in tuning parameters and selecting the most suitable LLM for each use case. The infrastructure is already designed to adapt seamlessly to changes in data sources or new regulatory frameworks, removing dependence on external system integrators for future developments.

Privacy and Security by Design

The exclusive use of aggregated public data, combined with the inherent robustness of AWS infrastructure, ensures compliant outputs. By eliminating the use of sensitive data at the source, risks related to data processing have been effectively mitigated, without compromising the system’s analytical and profiling capabilities.