Voice of the Customer Intelligence Manager, Customer Experience and Engagement

JLL•Dallas, TX

13d•Onsite

About The Position

We are seeking a customer-obsessed Insights and Analytics Manager to lead voice of customer (VOC) research and analytics that drive program and product decisions. This individual contributor designs and executes research programs, builds scalable reporting frameworks, and partners with internal stakeholders to translate ambiguous business questions into structured, actionable insights. The role blends traditional survey expertise with an evolving focus on micro-sentiment capture, behavioral analytics, and first-party data integration — helping the team shift from periodic measurement to continuous customer intelligence across the employee travel and events journey.

Requirements

7+ years in market research or data analytics, including survey design, data modeling, and reporting.
Bachelor's degree in a quantitative field such as market research, math, economics, finance, statistics, engineering, or equivalent work experience.
Proficient in enterprise survey platforms including Qualtrics, Medallia, or similar — including programming, logic design, and reporting dashboards; adaptable to new and emerging survey technologies.
Experience synthesizing insights across multiple data sets including surveys, product analytics, campaign metrics, and customer support data, translating findings into clear visualizations using BI tools such as Amazon QuickSight, Tableau, or similar.
Track record of going beyond reporting to proactively connect insights to action — identifying opportunities and recommending changes to product features or program strategies before stakeholders ask.
Consultative communication style — facilitates discovery conversations, translates vague asks into clear research plans, and proactively delivers findings and recommendations to decision-makers with clarity and conviction.
Exercises independent judgment — manages own workload with minimal direction in a fast-paced environment with competing priorities and evolving scope.

Nice To Haves

Experience working within a large-scale, matrixed organization; familiarity with Amazon's internal tools, systems, and decision-making culture is a strong advantage.
Familiarity with AI-powered analytics features and emerging survey technologies.
Familiarity with journey-based or lifecycle analytics — understanding how customers move through touchpoints and where friction or opportunity exists.
Comfort navigating ambiguity — can define the problem as well as solve it; doesn't need a fully scoped brief to get started.
Curiosity about emerging technology — eager to explore how AI, automation, and new data sources can improve how we listen to and learn from customers.
Systems thinker — connects individual data points including survey responses, tool engagement, campaign performance, and customer support data to broader customer journey narratives and strategic recommendations.

Responsibilities

Design, program, and deploy research using enterprise survey platforms such as Qualtrics, Medallia, Amazon Pulse, or similar, leveraging AI-assisted survey design and natural language analysis to accelerate time-to-insight.
Integrate and analyze engagement data across tools, campaigns, and customer touchpoints — connecting survey feedback with behavioral signals including product adoption, feature usage, campaign interactions, and content engagement to build a holistic view of the customer experience.
Conduct stakeholder intake sessions to clarify research needs, guiding partners who struggle to articulate business questions into structured research frameworks.
Analyze and present qualitative and quantitative findings — including outputs from generative AI, text analytics, and behavioral/engagement data — to the insights team and business partners with clear, decisive recommendations.
Build and maintain scorecards, dashboards, and automated reporting pipelines that go beyond survey metrics — incorporating engagement KPIs, campaign performance, and product interaction data to continuously simplify how stakeholders access and act on intelligence.
Manage multiple concurrent research projects independently from study design through reporting.
Monitor key metrics to identify trends impacting business performance and proactively surface emerging signals across surveys, tools, and campaigns — defining data-driven approaches to uncover new insights before they're requested.
Synthesize findings across multiple data streams including survey responses, behavioral analytics, campaign engagement, and customer support signals into thematic insights, exploring AI tools to scale analysis and reduce cycle time.
Create flexible models including predictive and prescriptive analytics to identify opportunities and inform decisions with speed and conviction.