A customer segmentation data model reclassified leads and improved B2B targeting turning warm leads into hot prospects and generating millions in additional revenue.
Context
A leading global technology and electronics manufacturer with European headquarters in Germany wanted to enhance the performance of its marketing campaigns. The company, one of the world’s largest producers of imaging and printing equipment, manages an extensive customer base across both B2B and B2C markets.
The Challenge
The European marketing team had accumulated a vast customer database segmented into B2B and B2C categories. However, many records were inaccurately classified by customers – reducing the effectiveness of targeted campaigns. Reclassifying contacts manually would have required extensive time and resources. The organisation needed a smarter, automated approach to accurately distinguish business from consumer customers and improve marketing precision.
The Solution
Objective developed an intelligent customer segmentation model powered by data analytics and machine learning. The data model pulled information from multiple data sources — including email domains, website activity, engagement metrics, and purchase history — to predict whether each contact should be classified as B2B or B2C.
Using a small, high-quality “gold standard” dataset of manually verified contacts, the model was trained to automatically reclassify thousands of records with accuracy and consistency.
The Results & Benefits
- 50,000 contacts reclassified – 30,000 from B2C to B2B and 20,000 from B2B to B2C.
- 14,000 contacts saw lead scores increase, boosting prioritisation for the sales team.
- Increased marketing relevance – refined segmentation improved personalisation and targeting.
- Over €1.5 million in new sales directly attributed to the reclassification model during the testing phase alone.
The data-driven segmentation approach delivered immediate impact, enabling the company to focus its B2B marketing efforts on high-value prospects and unlock significant new revenue streams.