CRM Analyst
Role details
Job location
Tech stack
Job description
At Scopely, we care deeply about what we do and want to inspire play every day - whether in our work environments alongside our talented colleagues or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing and innovating the mobile games industry, connecting millions of people around the world daily. What Will You Do The CRM Analyst is the measurement and intelligence engine of the central CRM organization. Operating across all game titles, this person pulls, verifies, and reports on campaign performance; tracks trends; and ensures experimentation is structured to produce reliable, actionable results. Critically, they look beyond individual game performance to surface portfolio-wide segment insights - understanding how key player cohorts like VIPs, regular customers, new players, and conversion targets perform across the full game catalog. Campaign Reporting & Performance
- Pull and verify campaign data from the CRM platform and downstream analytics systems, reconciling any discrepancies
- Produce regular campaign performance reports for each game team and portfolio-level summaries for the Director of CRM
- Track trends over time - open rates, click rates, conversion, retention impact - and flag anomalies or degradation
- Create and maintain dashboards that give CRM/Lifecycle Lead PMs visibility into the performance of their communication programs
Experimentation Design & Governance
- Support CRM/Lifecycle Lead PMs in designing A/B and multivariate tests, ensuring appropriate sample sizes, holdout groups, and clean control conditions
- Maintain an experimentation log across all games to prevent conflicting tests and ensure results can be interpreted confidently
- Review proposed experiments for methodological soundness before launch
- Analyze and present experiment results with clear, actionable recommendations
Cross-Portfolio Segment Insights
- Define and maintain segment definitions across the portfolio (e.g., VIP, Regular Customer, New Player, Lapsed, Conversion Candidate)
- Track how these segments behave and respond to CRM across multiple titles, identifying patterns and outliers
- Produce regular cross-game segment reports that help the Director of CRM and game teams understand what works universally versus what is title-specific
- Identify high-value segment opportunities that are underserved by current campaigns
Data Integrity & Targeting Validation
- Validate that targeting attributes used in campaigns are correctly populated and reliably representing the intended audience
- Partner with Data Engineering to surface data quality issues and advocate for fixes
- Verify that audience sizes match expectations prior to campaign launch
Requirements
- 4+ years in marketing analytics, CRM analytics, or a related data role - ideally in a behavior-based vs transactional environment - like gaming or live services.
- Proficiency with SQL and at least one BI or reporting tool (e.g., Looker, Tableau, Mode, or equivalent)
- Experience working with CRM or marketing automation platforms to extract and interpret campaign data
- Experience with both performance data and attribution data and able to ensure appropriate tracking is in place.
- Ability to represent data needs to engineers if necessary data options are not available.
- Understanding of A/Bn testing methodology, statistical significance, and experiment design across a complex set of overlapping campaigns.
- Ability to communicate data findings clearly to both technical and non-technical stakeholders
- Experience in games, apps, or a retention-driven consumer product is a strong plus
- Comfortable managing multiple reporting workstreams simultaneously across different game teams
- Experience in gaming as a player or operations manager preferred.
TECHNICAL SKILLS
- SQL (required)
- Excel / Google Sheets (advanced functions, pivot tables)
- BI tools (Looker, Tableau, Amplitude, etc.)
- Familiarity with event tracking tools (Segment, Snowflake, BigQuery, etc.)
- Basic understanding of data pipelines and data quality checks