Job details

Web Analyst

Job reference: 003485

Closing date: 27/10/2020

Salary: up to £30,000 per annum plus excellent benefits

Department: Brand and Creative

Hours per week: 36.17 hours per week

Trading is an essential part of our retail organisation and we are looking to recruit a Web Analyst here at N Brown to join our Customer Insight Team. For our internal stakeholders to make data led decisions and become a truly world class e-commerce retailer, our Customer Analytics team partner with our core brands to deliver analytical trading insight. This role provides customer and web analytics to support in season trading performance with the emphasis primarily on this week and last week performance.


Your role as Web Analyst:

  • Working across Trading to champion, influence and exploit the agenda for Customer and Web Analytics.
  • In week tactical and response analytics and recommendations
  • Analysis and recommendations to support in season demand forecasting from a customer perspective (to including web analytics)
  • Trend analysis to support recommendations for quarterly selling plans
  • Test design and reporting of campaign performance
  • Creation of and maintenance of reporting suite to facilitate diagnostic of key customer and web trading KPIs
  • Facilitation of self-serve data options
  • Act as a business partner to capture requirements and provide consultancy to the Trading team.  Provide challenge where appropriate.
  • Conduct research and development on the latest tools & techniques; whilst improving on current methods and introducing new ways of sourcing data.
  • Conduct research and adopt best practices in establishing business analytics platforms, systems and approaches.

What experience are we looking for in our Trading Analyst?

  • Degree in relevant discipline.
  • Up to 2 years relevant work experience.
  • A logical thinker who can analyse, interpret and provide compelling insight.
  • Proficient in the use of GA / Adobe Web Analytics
  • Experience of advanced customer analytics using tools such as SQL and an appreciation of open source tools (Python, R etc.) and open source data would be useful.