Embedding Client-First Mindset for a Global SaaS Knowledge Management Company
“Can Knowledge Management evolve from a data repository into a ‘Conversational Insight Companion’?”
The Challenge
Bridging the Aspiration-Reality Gap
The Insights & Analytics function is currently navigating a turbulent metamorphosis, moving away from being order takers or a library of reports toward becoming a proactive "Strategic Growth Engine". However, a stark dichotomy exists between this aspirational identity and the operational reality. Insights & Analytics professionals are grappling with an "identity crisis" in which their core mission to guide growth is often buried under a severe time compression, with demands for immediate, digestible answers.
For my client, a Global SaaS Knowledge Management (KM) Company, this user-level struggle created a secondary challenge: their platform was often perceived as a "digital landfill"—a static repository where data went to die. The business needed to understand how to evolve its product from a high-friction storage unit into a dynamic "thinking partner" that could help Insights teams reclaim their "seat at the table".
The Solution
A Foundational Research & Strategic Roadmap
I led a lean, fundamental research project designed to close the understanding gap between the SaaS platform and its two core audience archetypes: the "Strategic Navigator" (Senior Insights Leaders) and the "Stressed Orchestrator" (Insights Managers).
The project was executed in three strategic phases:
Phase 1: Planning & Design: Defined objectives to leverage learnings holistically across Marketing, Sales, and Product, specifically focusing on building an in-house "AI Persona" for product innovation and commercial development.
Phase 2: Qualitative Deep-Dives: Conducted 15 in-depth interviews across the FMCG, Retail & Apparel, Quick-Service Restaurants and Consulting sectors to explore key goals, pain points, and opportunities.
Phase 3: Data Analysis, Insight Creation & Recommendation: Synthesised over 80 hours of research into a concise set of strategic implications and recommendations on core actions to win and retain customers.
The Impact
Quantifying Value and Defining the "Ideal End-State"
The research provided the company with a definitive blueprint to move from "Storage & Search" to " Conversational Insight Companion".
Product Pivot: Identified the end of the search bar era, advocating for a "Conversational Insight Companion" that shifts from retrieving documents to synthesising narrative answers with conversational capabilities.
Operational Efficiency: Quantified the "heavy lift" of manual maintenance, leading to a recommendation to automate ingestion and integration into native systems or existing workflows.
Commercial Strategy: KM systems can be positioned as untouchable utilities by demonstrating Risk Mitigation and Efficiency (e.g., preventing $50k in duplicative research).
Institutional Wisdom: Mapped the "Contextual Memory" need to solve the knowledge churn problem, ensuring that the "why" behind past business failures is captured even when personnel leave.