Client Network: An Interactive Model for Predicting New Clients

TL;DR

The paper introduces the Client Network, an interactive model that uses complex network analysis of organizational connections to predict and facilitate successful sales pitches to prospective clients.

Contribution

It presents a novel network-based approach combining ranking algorithms and visualization tools to improve client prediction and sales strategies.

Findings

Effective in predicting successful client interactions

Supports sales tasks through visualization and navigation

Validated by experiments and user interviews

Abstract

Understanding prospective clients becomes increasingly important as companies aim to enlarge their market bases. Traditional approaches typically treat each client in isolation, either studying its interactions or similarities with existing clients. We propose the Client Network, which considers the entire client ecosystem to predict the success of sale pitches for targeted clients by complex network analysis. It combines a novel ranking algorithm with data visualization and navigation. Based on historical interaction data between companies and clients, the Client Network leverages organizational connectivity to locate the optimal paths to prospective clients. The user interface supports exploring the client ecosystem and performing sales-essential tasks. Our experiments and user interviews demonstrate the effectiveness of the Client Network and its success in supporting sellers' day-to-day tasks.