Customer Success Operations Coordinator

AI overview

Support Customer Success Manager in optimizing campaign execution and driving revenue growth while managing internal databases and tracking tools.

Responsibilities:
● Manage and update internal databases and tracking tools that are used by the wider Customer Success team
● Work with Production team to create our advertiser’s promotional placements to be published on Forbes Health     properties
● Support Customer Success Manager in onboarding and executing new customer initiatives
● Manage collection of creative assets, tracking, and ad verification from clients/agency contacts and coordinate       with Customer Success Manager
● Audit existing partner placements to optimize performance and monetization and to drive revenue growth
● Project manage and coordinate with internal teams on all necessary elements for campaign execution
● Work with internal teams on billing reconciliation and revenue tracking/forecasting

 

Requirements:
● Customer experience advocate with an entrepreneurial spirit who thrives in a team, goal-oriented environment
● 2+ years of proven digital advertising and/or affiliate marketing experience
● Familiarity with various affiliate platforms such as Impact, ShareASale, CJ, Rakuten, a plus
● Exceptional communication and organizational skills
● Ability to manage stress well and juggle multiple account challenges at once
● Extremely detail oriented
● Fluent in Microsoft Word, Excel, and PowerPoint
● Experience in WordPress, a plus

Perks:

  • Day off on the 3rd Friday of every month (one long weekend each month) 
  • Monthly Wellness Reimbursement Program to promote health well-being 
  • Monthly Office Commutation Reimbursement Program 
  • Paid paternity and maternity leaves

 

Any Full time degree

Perks & Benefits Extracted with AI

  • Commutation reimbursement: Monthly Office Commutation Reimbursement Program
  • Paid Parental Leave: Paid paternity and maternity leaves
  • Wellness Stipend: Monthly Wellness Reimbursement Program to promote health well-being

Forbes Advisor is looking for a Data Research Engineer - Data Extraction to join the Forbes Marketplace Performance Marketing team with a focus on supporting one of Forbes business verticals. If you're looking for challenges and opportunities similar to those of a start-up, with the benefits of an established, successful company read on.We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.The Data Extraction Team is a brand new team who plays a crucial role in our organization by designing, implementing, and overseeing advanced web scraping frameworks. Their core function involves creating and refining tools and methodologies to efficiently gather precise and meaningful data from a diverse range of digital platforms. Additionally, this team is tasked with constructing robust data pipelines and implementing Extract, Transform, Load (ETL) processes. These processes are essential for seamlessly transferring the harvested data into our data storage systems, ensuring its ready availability for analysis and utilization.A typical day in the life of a Data Research Engineer will involve acquiring and integrating data from various sources, developing and maintaining data processing workflows, and ensuring data quality and reliability. They collaborate with the team to identify effective data acquisition strategies and develop Python scripts for data extraction, transformation, and loading processes. They also contribute to data validation, cleansing, and quality checks. The Data Research Engineer stays updated with emerging data engineering technologies and best practices. 

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