Executive Summary
Perspectives on customer success have been evolving over the past several years. As B2B organizations are more entrenched than ever in the “retention” and “everything as a service” economy, customer success as a technology category is becoming a far more critical element than a simple tool for tracking subscription/software-as-a-service (SaaS) renewal cycles. In addition, with advancements in artificial intelligence (AI), customer success (CS) software has become a tool to drive a more strategic, growth-oriented approach to overall customer engagement.
The core tenets of CS solutions remain focused on automating postsale processes, leading up to managing renewal and, in some cases, expansion revenue opportunities. CS software differs from customer relationship management (CRM) software, in that it is designed less for the “lead to opportunity close” process and instead homes in on more structured engagement cycles. CS software, in the best-case deployment models, draws upon CRM, enterprise resource planning (ERP), and other systems to create a richer mosaic of data that CS managers and other stakeholders in the renewal/expansion cycle can leverage to better prioritize with whom they engage, and when.
Leading CS providers have been adding agentic AI tools to aid CS managers in performing routine actions, gathering customer information across various systems, and optimizing pre- and post-meeting tasks. In addition to AI developments, leaders in this sector are broadening their suites to offer more product usage tracking, training, and education, as well as customer community management capabilities. This is all aimed at supporting a growth mindset go-to-market model for organizations that spans the entire customer lifecycle and more departments than CS.
