CarParts.com valdo internetinę automobilių mažmeninės prekybos platformą, orientuotą į atsargines dalis, transporto priemonių priedus ir kitus vartotojams skirtus komponentus. Jos tiesioginio pardavimo vartotojams e. prekybos veikla siūlo antrinės rinkos ir originalios įrangos gamintojų atitikmenų produktus, o ją palaiko automobilių mažmeninės prekybos, logistikos ir gamybos veiklos.
Data Analyst, Marketing Analytics — CarParts.com
Improve CarParts.com’s e-commerce marketing with campaign analysis, experimentation, and website analytics. Turn customer behavior data into insights that inform growth decisions.
Aprašymas
- Assess email, paid media, SEO, and loyalty campaign performance to quantify incremental impact and return on investment.
- Plan and evaluate A/B and multivariate tests across site pages, landing pages, and marketing funnels.
- Set test hypotheses, sample sizes, outcome measures, and thresholds for statistical significance.
- Track and report website metrics such as traffic, bounce and conversion rates, average order value, and session behavior.
- Use Google Analytics or GA4 and BigQuery to identify user behavior patterns and opportunities to improve performance.
- Analyze customer journeys to locate friction and points where users drop off.
- Create and maintain dashboards and stakeholder reports.
- Turn business questions into analytical projects and carry out analysis from start to finish.
- Share practical findings and work with marketing, product, and engineering teams to incorporate them into strategy.
Reikalavimai
- Bachelor’s or master’s degree in data analytics, statistics, marketing, business analytics, or a related quantitative discipline.
- At least two years of professional experience in marketing analytics, web analytics, or a related analytical position.
- Proficiency in SQL and Excel for extracting, analyzing, and reporting data.
- Familiarity with Python for statistical analysis.
- Practical experience with web analytics platforms such as Google Analytics or GA4, BigQuery, or Adobe Analytics.
- Experience working with e-commerce or retail marketing data.
- Knowledge of SEO and SEM metrics and practices.
- Strong grasp of A/B testing, statistical significance, and sound experimentation practices.
- Experience with a data visualization platform such as Tableau, Looker, or Power BI.
- Clear communication skills and the ability to explain data insights to nontechnical audiences.