Senior Customer Success Manager Job ID 2026-1583

Internet Brands•Minneapolis, MN

16h•Onsite

About The Position

The Senior Customer Success Manager (CSM), Full Portfolio, is accountable for driving measurable business outcomes for high-value law firm clients across the Internet Brands Legal ecosystem, including FindLaw, Martindale-Avvo, Lead products, Websites, Paid Media, CRM integrations, and related solutions. This is not a relationship management role. It is a performance consulting role for the AI era. The LGE Full Portfolio CSM owns a performance-driven solution spanning visibility, reputation, marketing execution, intake optimization, and case conversion. Critically, this person is expected to contribute to the adoption of AI-powered workflows and agent-based automation — not just use AI as a tool, but support how it reshapes the function itself. The Senior CSM serves as the strategic point of accountability for a defined portfolio of high-investment law firms. They operate as a performance consultant, internal quarterback, executive partner, and AI-forward team builder, ensuring that marketing efforts translate into measurable business results through increasingly automated, intelligent systems. This role is critical to scaling the Legal Growth Engine model and defining what a differentiated, agent-first approach to legal marketing looks like in practice.

Requirements

5–8+ years in Customer Success, Account Management, or Performance Marketing roles.
Experience managing complex, multi-channel marketing programs (PPC, paid media, lead generation, websites).
Demonstrated ability to translate data into executive-level insights.
Comfort managing demanding, high-investment clients.
Strong understanding of marketing KPIs: CPL, CPA, ROAS, conversion rate, attribution.
Experience with CRM platforms (Clio, Salesforce, Litify, LeadDocket, or similar) and lead-to-case workflows.
Hands-on experience using AI tools in a professional context, not just awareness, but active, iterative use.
Familiarity with AI agent frameworks, workflow automation tools, or LLM-based productivity tooling.
Ability to identify where AI can replace or accelerate a workflow and take practical steps to implement it.
Agent-first thinker: you ask ‘how can a system do this?’ before ‘how do I do this manually?’
Highly organized, systems-oriented, and operationally disciplined.
Executive presence and strong presentation skills.
Thrives in ambiguity and scaling environments.
Operates with urgency and accountability in a performance-driven model.
Builds and shares playbooks, not just personal workflows.

Nice To Haves

Experience building or managing AI-augmented workflows within a CS or marketing operations function.
Familiarity with legal intake systems and law firm operations.
Prior experience in a scaled SaaS or performance marketing environment with portfolio-level accountability.
Track record of reducing manual work through automation or process redesign.

Responsibilities

Own Business Outcomes, Not Products: Manage a portfolio of high-value, multi-product law firm accounts. Align each client to defined performance KPIs: leads, cost per lead, signed cases, cost per case, ROI. Translate multi-channel activity into measurable business impact. Drive renewals, expansion, and portfolio growth through proven performance. Deploy AI-driven reporting and alerting to identify performance shifts before clients do.
Lead Cross-Portfolio Strategy: Coordinate visibility (directories, profiles, paid placements), marketing (PPC, lead gen, website), and conversion (intake, CRM integration) into a unified strategy. Partner with Paid Media, Product, Marketing, Reporting, and Operations to ensure campaigns are optimized toward case outcomes. Ensure CRM integrations are implemented and maintained to enable lead-to-case tracking and closed-loop reporting. Identify and implement automation opportunities across onboarding, reporting, escalation, and QBR workflows. Escalate and resolve operational blockers that impact performance.
Adopt and Contribute to an Agent-First Function: Champion the design and deployment of AI agents across the CSM workflows, including automated performance monitoring, intake analysis, anomaly detection, and client communication drafting. Identify repetitive, high-volume CSM tasks that can be delegated to AI agents, and lead their implementation with support from Product and Engineering. Develop and maintain a personal toolkit of AI-assisted workflows (prompt libraries, agent configurations, automation stacks) that accelerate your work and serve as a model for the team. Contribute to building a team culture where AI augmentation is expected, iterated on, and shared — not optional. Provide feedback on AI tooling, identify gaps, and partner with Product to influence the roadmap for agent-based CSM capabilities.
Executive-Level Client Partnership: Conduct structured monthly performance reviews grounded in data, strategy, and forward-looking AI-driven insights. Translate performance dashboards (increasingly AI-generated) into business narrative and recommended actions. Manage sophisticated stakeholders including managing partners, marketing directors, and intake leaders. Maintain proactive communication around risks, performance shifts, and growth opportunities.
Performance & Data Leadership: Analyze multi-channel reporting across directories, PPC, lead programs, website performance, and CRM data. Leverage AI tools to surface trends, attribution gaps, and optimization opportunities at a pace not possible manually. Ensure alignment between marketing performance and case conversion data. Contribute to the evolution of reporting systems, dashboards, performance benchmarks, and AI-assisted insight generation.
Revenue & Margin Accountability: Identify expansion opportunities across the portfolio. Proactively mitigate churn and downsell risk by using predictive signals and automated health scoring where available. Understand unit economics, portfolio margin impact, and growth thresholds. Partner with Sales during renewal cycles and expansion motions.
Scale the Program: Contribute to best practices, playbooks, onboarding frameworks, and performance standards. Document and share AI workflows, prompt strategies, and agent configurations that improve team-wide efficiency. Support pilot initiatives tied to AI, CRM integration, advanced attribution models, and agentic automation. Provide structured feedback to Product and Leadership on systemic gaps or opportunities.