Customer Success Operations Manager

Branch is a FinTech company focused on empowering workers with financial freedom through innovative financial products. The Customer Success Operations Manager will design and operate a scaled Customer Success model, enhancing engagement and product adoption while leveraging AI tools to drive efficiencies across the customer success workflow.

Responsibilities:

• Design and operationalize the tech-touch Customer Success strategy for ~1,000 non-managed accounts
• Develop segmentation models based on account size, payout trends, user growth, and engagement signals
• Build structured lifecycle playbooks covering onboarding, activation, growth, and re-engagement
• Define and implement a customer health scoring framework using data from Looker (usage and revenue signals) and HubSpot (account and engagement data)
• Monitor payout volume, transaction frequency, and roster trends in Looker to detect early signs of decline
• Establish thresholds and triggers for intervention
• Design and execute segmented campaigns using HubSpot to drive adoption and engagement
• Develop proactive education initiatives to increase feature utilization
• Continuously analyze campaign performance and refine outreach strategy
• Use AI tools (e.g., Claude, workflow automation platforms) to design, prototype, and deploy scaled engagement programs, health scoring models, and reporting dashboards
• Identify manual or repetitive processes across the Customer Success workflow and build automated solutions to replace them
• Collaborate with CX Operations to integrate AI-powered tooling into existing systems and workflows
• Stay current on emerging AI capabilities and proactively propose new applications that create leverage across the portfolio
• Personally engage with high-risk or high-potential accounts when data indicates intervention could improve outcomes
• Conduct structured check-ins focused on usage trends, operational friction, and growth opportunities
• Partner with Support and Product to resolve systemic blockers impacting engagement
• Identify usage growth patterns in Looker that indicate upsell potential
• Create structured processes for surfacing qualified opportunities to Sales
• Coordinate transitions when accounts move into managed status
• Partner with the GTM CRM Administrator to define segmentation logic and reporting requirements
• Work closely with CX Operations to leverage automation and tooling enhancements
• Provide structured usage insights to Product and Support to reduce friction and increase engagement
• Operate as a power user of Looker and HubSpot as the two primary data systems for this role, pulling usage/revenue data from Looker and account/engagement data from HubSpot to drive decision-making across all program areas

Requirements:

• 5+ years of experience in Customer Success, CS Operations, Growth, or usage-based SaaS/fintech environments
• Experience operating in a tech-touch or scaled portfolio model
• Strong analytical skills with the ability to interpret behavioral and revenue data; comfortable working directly in BI tools such as Looker to build and modify reports
• Hands-on experience with HubSpot (segmentation, campaign execution, and CRM data management) and familiarity with BI/analytics platforms (Looker preferred) for usage and revenue reporting
• Demonstrated ability to translate data insights into structured customer programs
• Strong written communication and cross-functional collaboration skills
• Demonstrated experience using AI tools (e.g., Claude, ChatGPT, Copilot) to build workflows, automate tasks, or create operational tooling — not just prompting, but building
• Builder mindset: a bias toward creating solutions over requesting them, with comfort iterating quickly and learning by doing
• Experience with workflow automation platforms (e.g., n8n, Zapier, Make) to connect systems and automate multi-step processes
• Familiarity with AI-assisted data analysis, reporting, or content generation in an operational context
• Track record of identifying a manual process and independently building an automated replacement