Customer Analytics Specialist
DISHER is currently partnering with an organization that is evolving from a logistics services company into a technology-enabled services company. Technology, data, and AI increasingly are determining not only how efficiently they operate, but what services they can offer, how differentiated those services are, and the value they can create for their customers.
In this role, you will build and own customer analytics that directly drive Net Revenue Retention and customer success outcomes. You will translate complex customer data into actionable insights and automated intelligence that enable Account Managers, Customer Success Managers, and executives to make faster, more informed decisions about retention, expansion, and customer value.
You will report to the Vice President, Customer Operations and work directly with customer-facing teams to understand what decisions they need to make, validate whether your analytics are creating measurable impact, and iterate toward insights they trust and act on.
What you will get to do:
Customer Health & Retention Analytics
- Build and maintain a customer health score combining order frequency, dispute rate, response time, fill rate satisfaction, and other key indicators
- Produce weekly “at-risk account” reports (red/yellow/green) with specific drivers of score changes
- Develop a churn propensity model that flags accounts 30-60 days before potential churn
- Automate renewal dashboards with win probability estimates
- Support internal and customer data analysis requests for executive and board-level decision making
Expansion Signal Analytics
- Generate monthly insight views and reports to identify expansion opportunities
- Perform market share analysis to identify wallet share movement
- Track service behavior and activities by account and surface SLA upgrade opportunities
- Produce quarterly customer value reports for Account Managers and CSMs to use in customer QBRs
- Build executive-level decks for monthly and quarterly business reviews
Data Infrastructure & Automation
- Maintain connections between their internal database, CRM, and BI tools (Power BI / Tableau)
- Build and maintain dashboards that automatically refresh weekly
- Implement automated alerts to CSM and AM when health scores cross thresholds
- Document data definitions and standardize reporting
- Work with operations and IT to resolve data quality issues at source
AI & Advanced Analytics
- Lead AI adoption for analytics and collaborate with IT to productionize analytic models
- Implement AI prompts and query interfaces for AM/CSM self-service
- Validate AI-generated insights and ensure accurate, quality data for customer-facing teams
- Develop subject matter expertise in new technology platforms and products
What success looks like:
- A 30% reduction in “red” health score accounts week-over-week
- A 50% reduction in CSM time spent on manual data extraction from baseline
- 100% on-time delivery of automated reports
What will make you successful:
- 8+ years as a BI Analyst, Data Analyst, or Analytics Specialist (Power BI preferred)
- Experience in logistics, supply chain, distribution, or e-commerce fulfillment (spare parts experience strongly preferred)
- Proven track record of building dashboards that tell stories and drive action, not just visualizations
- Knowledge of service supply chain and spare parts logistics metrics
- Proficiency in Power BI or Tableau
- Experience connecting to ERP/WMS data sources
- Working knowledge of Python or similar for analysis (pandas, basic stats)
- Familiarity with CRM data structures (HubSpot, Salesforce, Pipedrive)
- Ability to translate business questions into data requirements
- Strong verbal and written communication
- Customer-facing and customer-centric mindset
- Must have the current and continuing right to work in the United States of America without restrictions or expirations
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
