The company is looking to manage and enhance customer satisfaction reporting and dashboards by gathering, analyzing, and visualizing customer experience data to provide actionable insights that improve customer satisfaction and loyalty.
Requirements
- Proficiency in BI tools (e.g., Power BI, Tableau, Looker) and data manipulation (Excel, Power Query, SQL).
- Strong analytical skills with the ability to interpret large, complex datasets.
- Experience with customer satisfaction survey platforms (e.g., Qualtrics, Salesforce Feedback Management, SurveyMonkey).
- Knowledge of statistical methods for survey analysis and performance benchmarking.
- Familiarity with CRM and operational systems (e.g., Salesforce, ERP).
Responsibilities
- Collect, validate, and analyze customer satisfaction data from surveys, feedback platforms, CRM systems, and operational systems.
- Incorporate service delivery timelines, SLA compliance, defect rates, and support ticket resolution performance into customer satisfaction analytics.
- Integrate multiple data sources to create a unified view of customer sentiment, trends, and performance drivers.
- Design, develop, and maintain interactive dashboards and reports (e.g., Power BI, Tableau) for customer satisfaction, operational KPIs, and related metrics.
- Automate recurring reports to improve efficiency and consistency.
- Identify patterns, root causes, and correlations between operational performance (e.g., SLA adherence, product delivery) and customer satisfaction scores (CSAT, NPS, Customer Effort Score).
- Monitor trends over time and assess the impact of improvement initiatives.
Other
- 2+ years of experience in business/data analysis, preferably in a customer experience, operations, or customer insights role.
- Excellent communication skills with the ability to simplify complex findings for diverse audiences.
- Partner with Customer Experience, Operations, Product, and Leadership teams to define KPIs, reporting requirements, and improvement initiatives.
- Translate business questions into data analysis and provide actionable recommendations.
- Present findings in a clear, engaging manner to both technical and non-technical audiences.
