We are looking for a strategic, customer-obsessed, and data-driven Product Manager to define and build an intelligent recommendation product that helps our internal sales teams identify which products, solutions, and offers are most relevant for each customer. Why is a particular product being recommended? The Product Manager will own the product vision, strategy, roadmap, business case, and execution for this capability, working at the intersection of AI/ML, data, CRM, sales enablement, enterprise software, and commercial strategy. This role requires a unique combination of product management, structured problem solving, commercial acumen, analytical thinking, and the ability to influence senior stakeholders across a complex organization. Build and maintain a multi‐year product roadmap balancing customer value, seller productivity, commercial impact, technical feasibility, and company strategy. Define how the product fits within the broader sales, CRM, customer intelligence, and AI ecosystem. Evaluate strategic opportunities and trade‐offs using structured business cases, quantitative analysis, customer insights, and competitive benchmarks.
Reduce seller effort by integrating recommendations directly into CRM, account planning, opportunity management, and seller productivity tools. AI, Data & Recommendation Systems Partner closely with data science, machine learning, engineering, and analytics teams to define the recommendation architecture and product requirements. Identify and prioritize the customer and commercial signals required to generate high‐quality recommendations. Determine how signals such as product usage, installed base, purchase history, customer profile, industry, intent, engagement, support activity, contract information, account potential,



and seller activity should influence recommendations. Define how seller actions and customer outcomes can continuously improve recommendation quality. Ensure responsible use of AI, including appropriate transparency, explainability, governance, and data quality controls.
Partner closely with engineering, design, data science, analytics, and architecture teams throughout discovery, development, launch, and iteration. Make prioritization decisions based on customer impact, seller value, commercial opportunity, technical complexity, model performance, and investment requirements. Lead pilots, experiments, A/B tests, and controlled launches to validate hypotheses and improve the product. Use quantitative and qualitative data to identify issues, uncover opportunities, and drive continuous product improvement. Manage dependencies across CRM systems, customer data platforms, product catalogues, identity systems, analytics platforms, sales tools, and downstream business processes. Commercial Strategy & Business Impact Develop clear business cases for product investments, including potential revenue impact, seller productivity improvements, customer benefits, and implementation costs. Partner with Sales, Finance, Strategy, and business‐unit leaders to understand portfolio priorities and commercial opportunities. Establish measurable links between recommendation quality, seller behavior, customer outcomes, pipeline creation, and revenue.



Translate complex commercial problems into scalable product capabilities rather than one‐off processes or manual interventions.
Cross‐Functional Leadership Work closely with Sales, Sales Operations, Engineering, Data Science, UX, Product Marketing, Finance, Customer Success, Strategy, and product business units. Influence senior leaders through data, structured problem solving, clear recommendations, and compelling product narratives. Build strong relationships across general and matrixed organizations to accelerate execution and adoption.
Success in this role will be measured through a combination of seller adoption, recommendation quality, customer outcomes, operational efficiency, and commercial impact. Recommendation precision, relevance, and quality; Increase in qualified opportunities identified; Model and recommendation performance over time; 5+ years of experience in Product Management, Management Consulting, Corporate Strategy, Product Strategy, or a related role, preferably within technology, enterprise software, SaaS, AI/ML, data products, CRM, sales technology, or digital platforms.
~ Bachelor's degree in Business, Engineering, Computer Science, Economics, Finance, Mathematics, or a related discipline, or equivalent practical experience.
~ Strong commercial and strategic acumen, with the ability to evaluate customer needs, business opportunities, investment priorities, and trade‐offs.
~ Experience developing business cases, defining KPIs, analyzing financial or operational performance, and using quantitative analysis to support decisions.
~ Experience working closely with engineering, data science, analytics, UX, and business teams.
~ Strong understanding of data‐driven product de

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