Process: compiling lists of potential customers, researching and qualifying them against an ideal customer profile (ICP) to produce a list of prioritised prospects.
Problem: reliance on limited data and inefficient manual processes negatively impacts ROI by diverting valuable marketing and sales resources toward only moderately qualified, medium-probability conversion leads.
Use case: AI obtains intelligence (Transfer Learning) to become an instant expert in ESG. Then, by reading and understanding vast amounts of company data via natural language processing (NLP) for companies in your addressable market, a weighted score and future outlook (Predictive Modelling) is calculated, producing a prioritised target list of companies.
Case-study:
For QCP, we successfully applied advanced AI, including transfer learning and predictive modelling, to analyse and extract ESG characteristics from potential SME acquisition targets. This process successfully scored and prioritised leads for private equity, resulting in a highly segmented list.
This enabled focused sales efforts to engage high-quality asset owners seeking impact investment, where we also used AI email marketing to write personalised emails.
