Case Study: Bloomreach achieves 78% of its net-new pipeline with Leadspace

Bloomreach Sources 78% of Net-New Pipeline with ABM Driven by Leadspace

Bloomreach, maker of a Web Relevance Engine that uses NLP and machine learning to match website content and visitors with intent data, faced an ABM challenge: they needed to identify the right people inside target e‑commerce accounts and obtain up‑to‑date contact, demographic and firmographic data to better segment audiences and determine the best product fit for each prospect.

Using Leadspace’s Customer Data Platform for real‑time data enrichment and AI-driven predictive modeling, Bloomreach discovered net‑new accounts and the most relevant contacts, enriched records with 80+ fields, and scored prospects against custom Ideal Customer Profiles. The results: Leadspace-sourced names accounted for 78% of net‑new pipeline, improved campaign reach and ROI, more effective SDR prioritization, and automated Salesforce updates for cleaner, actionable CRM data.

Bloomreach

Jason Seeba

Lead Marketing Technologist