Senior Platform Product Analyst

CORE PROFILE

Experienced product analyst that has used data and insights to drive product and operational decisions in customer-facing or operationally intensive domains.

This Product Analyst role revolves around continuously identifying and going after business and operational improvements through measurement, analysis, and evidence-based recommendations. This role focuses on helping the company understand why customers need help, what it costs, and how to resolve their issues as quickly as possible, whether through in-product self-service, AI-powered chatbots, or human agents with the right tooling. You will work across product, chatbot, and support data to provide the insights and business cases that drive prioritization across the Customer Care platform team and influence the wider product organization.

In this role, you will work at the intersection of support operations, product analytics, and customer experience, helping to ensure that the team is always solving the highest-impact problems and that product teams across the organization understand how their products impact the customer support experience.

NATURE OF WORK

In this role, you will be responsible for analyzing product, chatbot, and support data across all products and channels, building the metrics and business cases that drive prioritization, identifying opportunities to resolve customer issues as early as possible, and measuring the success of the team's initiatives.

Your responsibilities include:

Analysis & Root Cause Investigation

·       Analyze data across all resolution channels: product usage and user behaviour, chatbot and AI conversation logs, and human agent support interactions, across all products and customer segments (consumer and enterprise).

·       Connect product usage data to support outcomes. Identify the in-product journeys, error states, and drop-off points that lead to customers needing help.

·       Analyze chatbot conversation data to identify where AI interactions fail, where customers drop off or escalate, and where conversation design or knowledge gaps reduce resolution effectiveness.

·       Build and maintain a structured contact reason taxonomy that is specific enough to be actionable by product and engineering teams.

·       Identify patterns and root causes: which products, features, or journeys generate disproportionate support load, and why. Distinguish between support problems and product problems.

·       Track repeat contact patterns. Customers hitting the same issue multiple times signals a product gap, not a support gap.

Metrics & Measurement

·       Define and maintain the care platform team's metrics framework, anchored to the team's north-star outcomes: customer satisfaction (CSAT), resolution effectiveness, and operational efficiency (cost-per-interaction, agent productivity).

·       Establish baseline metrics across all products and channels, and track trends over time.

·       Measure the success of the team's initiatives across all resolution channels. Close the loop on whether changes delivered the expected results and surface follow-up opportunities.

·       Build and maintain dashboards and reporting that give the team and leadership real-time visibility into performance across chatbot resolution, self-service adoption, and agent efficiency.

·       Track the effectiveness of process changes and operational improvements over time.

Prioritization & Business Cases

·       Translate analytical findings into prioritized recommendations for the wider team, backed by data on volume, cost, customer impact, and feasibility.

·       Segment issues by the best resolution channel: which are best addressed by in-product self-service, chatbot improvements, or better agent tooling.

·       Identify and prioritize which support actions and issue types the chatbot should handle next, based on volume, resolution complexity, cost, and customer impact.

·       Build cost attribution models that quantify each product's support burden. This creates accountability and visibility for product teams whose flows generate significant ticket volume.

·       Build business cases for investment decisions: quantify the cost of inaction, the expected ROI of proposed improvements, and the trade-offs between competing priorities.

Self-Service & Product Quality Influence

·       Identify opportunities where customers could resolve issues themselves through better in-app information, improved FAQs, clearer product flows, or proactive communication, rather than contacting support.

·       Socialize findings with product managers across the organization and influence product quality improvements by presenting clear, data-backed business cases for change.

·       Track the impact of self-service and product quality improvements on resolution rates to build momentum and demonstrate value.

Stakeholder Collaboration

·       Work closely with the Customer Service Group (CSG) and other back-office teams to understand operational realities, validate analytical findings, and ensure recommendations are grounded in how support actually works.

·       Partner with data science and AI teams to share conversation insights, validate chatbot performance, and inform priorities for chatbot capability expansion.

·       Own the closed-loop feedback mechanism between support operations, the care platform team, and other product teams.

·       Ensure recurring support issues are surfaced to the right product owners with enough context and data to drive action, including volume, cost, customer impact, root cause, and the upstream user behaviours that trigger them.

·       Monitor CSAT trends and correlate with product changes, support process changes, and AI rollout to understand what is driving movement.

DISPLAYED SKILL MASTERY

·       Ability to work across operational, product, and user behaviour datasets to extract meaningful, actionable insights and translate them into business language: cost, customer retention, operational efficiency, revenue impact.

·       Strong product thinking: goes beyond surfacing problems to proposing feasible solutions and segmenting issues by the right resolution path.

·       Proficiency in SQL and data visualization tools (Tableau, Looker, Power BI, or similar).

·       Strong organizational skills to manage multiple analytical workstreams across metrics, business cases, and stakeholder reporting.

·       Ability to present findings clearly and persuasively to product managers and leadership, and to influence decisions across teams.

·       Strong customer-centric mindset: interprets data in the context of real customer and agent experiences, not just in the abstract.

·       Understanding of customer support operations: ticketing, contact drivers, resolution workflows, queue dynamics, chatbot and AI-assisted interactions, and customer satisfaction measurement.

·       Familiarity with financial services operations and industry-specific challenges.

EXPECTED RESULTS

·       As a Platform Product Analyst, your performance will be measured by the following key performance indicators and expected results:

·       CSAT Attribution: Increase clarity on what drives CSAT movement by delivering timely, actionable attribution analysis across all products and channels.

·       Root Cause Coverage: Increase the percentage of top contact drivers with documented root cause analysis and actionable recommendations.

·       Cost Attribution: Reduce unattributed support cost by building and maintaining per-product cost attribution across the organization.

·       Resolution Channel Effectiveness: Increase the percentage of customer issues resolved through self-service and chatbot channels, driven by data-backed recommendations for product, content, and conversation improvements.

·       Initiative Measurement: Increase the percentage of team initiatives with clearly defined success metrics, baseline measurements, and post-launch outcome tracking.

·       Prioritization Impact: Increase the percentage of shipped improvements that deliver measurable results in CSAT or operational cost reduction.

REQUIRED QUALIFICATIONS 

·       At least 5 years of experience in product analytics, business analysis, or operations analytics, ideally in customer support, customer experience, or operationally intensive domains

·       Strong SQL and data visualization skills; experience building dashboards and working with BI tools (Tableau, Looker, Power BI, or similar)

·       Demonstrated ability to turn analytical findings into business cases and prioritized recommendations that drive product or operational decisions

·       Strong communication and presentation skills, to make complex data accessible and compelling to both technical and non-technical audiences

·       Experience working with and influencing cross-functional teams including product managers, engineers, and operations teams

·       Experience in FinTech, financial services, or payments is a strong advantage

·       Fluent in English