The Challenge
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 dataset inevitably results in missed conversions for end customers.
During the data acquisition process from official sources such as Infocamere, SevenData encountered structural issues related to ATECO codes, leading to several key challenges:
- Official data not aligned with reality, with direct impact on end customers’ ROI
Company classification, based solely on public registries and ATECO codes, proved to be limited and often misaligned with actual business activities. Incorrect or overly generic classifications undermined the effectiveness of targeting strategies, exposing end customers to inefficient and dispersed marketing investments.
- Erosion of perceived value and trust in the service
Poor data accuracy directly affected the quality of the data packages delivered, reducing their perceived value. End customers were forced to invest time and resources on non-target contacts, negatively impacting trust in data as a strategic asset and weakening the overall service reputation.
- Lack of a structured data validation process
Despite the known limitations of official sources and the exclusive reliance on ATECO codes, there was no systematic process in place to verify and update data. Validation activities were carried out manually and retrospectively, resulting in high costs and limited scalability.
The Solution
To transform its data assets into a true strategic driver for end customers, SevenData fundamentally evolved its data enrichment strategy. With the support of beSharp, the company implemented an advanced data augmentation solution powered by Generative AI, enhanced through retrieval-based techniques to improve accuracy and contextual understanding.
This solution enabled SevenData to go beyond the limitations of outdated registries and imprecise standardized classifications, accurately identifying the real business activity of each company and providing highly reliable classification recommendations.
The Benefit
The introduction of the new model transformed data quality from an operational challenge into a strategic growth driver, redefining SevenData’s positioning in the market.
Data Quality and Precision Targeting
The accuracy of company classification significantly improved, reaching levels between 85% and 93%. This level of precision turned data packages into a premium asset, enabling advanced targeting strategies that reduce advertising waste and maximize conversion potential for end customers.
Cost Optimization
Eliminating dependency on external providers for data validation led to immediate cost efficiencies. A significant and recurring expense was replaced by a highly efficient internal infrastructure, maximizing project ROI and freeing up resources for innovation.
Accelerated Go-to-Market
By centralizing and automating data management, manual inefficiencies were eliminated. The ability to continuously process millions of records and rapidly act on datasets now allows SevenData to respond quickly to market demands, delivering highly 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. The company can now independently tune parameters and select the most suitable LLM for each use case. The infrastructure is designed to seamlessly adapt to new data sources and evolving classification standards, eliminating reliance on external system integrators for future developments.
Privacy and Security by Design
The exclusive use of aggregated public data, combined with the robustness of the underlying infrastructure, ensures full compliance by design. By avoiding the use of sensitive data altogether, risks related to data processing are minimized while preserving the system’s analytical and targeting capabilities.
