The posting
7-Eleven is an iconic family of brands with over 86,000 locations, surpassing every retailer in the world. We revolutionize convenience, restaurants and fuel through cutting edge innovation — working hard to be the customer's first choice. 7-Eleven empowers our employees to "activate awesome" and make a meaningful impact in their stores and communities every day. If you're ready to grow, lead and make a difference, come join our team and help shape the future of convenience.
Job Summary:
7-Eleven is transforming the customer experience through data-driven personalization. As a Senior Data Analyst, CRM & Personalization, you will play a critical role in uncovering insights that shape how we engage with our customers across digital and physical channels. This is a new role on a growing team, offering the opportunity to help build the analytics foundation for CRM and personalization at scale.
You will work closely with marketing, loyalty, digital product, and data teams to deliver impactful analysis, campaign and program measurement, and actionable customer insights that drive business outcomes. You will translate campaign and program results into recommendations regarding investment, targeting, offers, messaging, timing, channel mix, and contact frequency.
Key Responsibilities:
Measurement strategy and business impact:
- Own and evolve the CRM measurement framework, including KPI definitions, metric logic, reporting cadence, source-of-truth dashboards, incremental impact measurement, and success criteria by lifecycle stage.
- Translate campaign and program performance into recommendations that improve customer engagement, retention, frequency, customer value, and business results.
Campaign and Program Analytics:
- Analyze CRM and personalization campaigns across email, app, SMS, in-store, and other relevant channels to evaluate performance, identify trends, and recommend optimizations.
- Analyze campaign exposure, conversion, engagement, retention, and customer-value outcomes across customer cohorts and lifecycle stages.
Customer, Lifecycle and Value Insights:
- Analyze CRM and personalization campaigns across email, app, push and SMS, and other relevant channels to evaluate performance, identify trends, and recommend optimizations.
- Analyze campaign exposure, conversion, engagement, retention, and customer-value outcomes across customer cohorts and lifecycle stages.
Testing and Experimentation:
- Design, execute, and analyze A/B, multivariate, and holdout tests, including hypotheses, success criteria, test design, audience assignment, sample-size considerations, and interpretation of results.
- Distinguish correlation from causation and translate both positive and inconclusive findings into clear recommendations.
Audience Development and Activation:
- Support the strategy and execution of audience creation within the Customer Data Platform, ensuring segments are precise, scalable, and aligned with campaign objectives, personalization strategies, and lifecycle marketing goals.
- Establish audience QA standards, including eligibility logic, identity resolution, exclusions, suppression, consent, frequency controls, count reconciliation, and pre-launch validation.
Data Quality, Governance, and Documentation:
- Partner with CRM, Loyalty, Martech, Data Engineering, and Digital Product teams to ensure data accuracy, consistency, and alignment with business goals.
- Investigate data discrepancies across the warehouse, CDP, CRM platforms, dashboards, and downstream performance reporting; coordinate resolution of root causes.
- Maintain clear documentation for KPI definitions, event and data requirements, audience logic, assumptions, and analytical methodologies.
Reporting and Data Storytelling:
- Build and maintain dashboards and reports that track KPIs, campaign performance, customer engagement, lifecycle progression, and customer value.
- Present findings and recommendations clearly and concisely to technical and non-technical stakeholders, including senior leaders.
Cross-Functional Leadership and Mentorship:
- Lead analytical workstreams from business-question definition through recommendation, implementation support, and post-launch measurement.
- Help onboard, coach, and mentor junior analysts and marketing partners on segmentation, experimentation, data quality, and analytical best practices.
- Influence decisions across Marketing, CRM, Loyalty, Product, Engineering, Martech, Finance, and Operations without relying on formal authority.
Ideal Skillsets & Behaviors:
- Strong attention to detail, curiosity, and a passion for turning data into actionable insights.
- Data quality discipline: notices inconsistencies, validates inputs and outputs, documents assumptions, and prevents unreliable audiences or reporting from reaching stakeholders.
- Experimentation mindset: forms clear hypotheses, protects test integrity, distinguishes correlation from causation, and acts on both positive and null results.
- Commercial acumen: connects customer behavior and campaign results to revenue, margin, retention, visit frequency, basket, and customer value.
- Influence without authority: earns alignment across Marketing, CRM, Loyalty, Product, Engineering, Martech, Finance, and Operations.
- Executive communication: frames the decision, explains the evidence, quantifies implications, and recommends a clear action.
- Curiosity and hypothesis generation: proactively identifies opportunities instead of only responding to reporting requests.
Qualifications:
- Bachelor’s degree in Analytics, Statistics, Marketing, Economics, or a related field, or equivalent practical experience.
- 3+ years of progressively responsible experience in analytics focused on marketing, loyalty, CRM, personalization, lifecycle marketing, or customer insights.
- Experience in retail, QSR, CPG, ecommerce, subscription, or another high-volume, omnichannel environment preferred.
- Demonstrated knowledge of experimental design, control groups, holdouts, incrementality, statistical inference, attribution limitations, and practical interpretation of test results.
- Advanced SQL proficiency, including complex customer-level analysis, joins, data validation, and analysis of large datasets in a cloud data warehouse such as Snowflake, Databricks, BigQuery, or equivalent.
- Experience with data visualization tools such as Tableau, Power BI, or equivalent, along with strong statistical analysis skills.
- Experience analyzing customer, transaction, loyalty, digital behavior, and campaign-exposure data to improve acquisition, engagement, retention, reactivation, frequency, and customer lifetime value.
- Experience validating data, investigating discrepancies, and partnering with data or engineering teams to resolve data-quality issues.
- Hands-on experience with customer segmentation, campaign measurement, experimentation, and lifecycle analytics.
- Excellent communication, collaboration, organization, and stakeholder-management skills.
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If an hourly or salary range is included in this ad it represents the range 7-Eleven in good faith believes is the range of compensation for this role at the time of this posting. The Company may ultimately pay more or less than the posted range. This range is only applicable for jobs to be performed in this state. This range may be modified in the future. No amount is considered to be wages or compensation until such amount is earned, vested, and determinable under the terms and conditions of the applicable policies and plans. The amount and availability of any bonus, commission, long-term incentive compensation, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law.
For a general description of all benefits 7-Eleven is offering in the US for the position, please visit this link.
For a general description of all benefits 7-Eleven is offering in Canada for the position, please visit this link.
