Red Bull UK is currently recruiting for a Shopper Insights Industrial Placement (12-Months) to be based in London, UK.
The purpose of this 12 month paid internship is to support the Shopper & Consumer Insights Manager in making Red Bull the definitive expert in how shoppers and consumers behave in outlet, across both Off Premise and On Premise. It is designed for someone at the start of their career, whatever their route in, who wants a hands on first year in commercial insight, and it builds the foundations for a future career in insights.
The Shopper Insights Intern supports the engine room of the shopper insight agenda. Working under the guidance of the manager, the intern runs core analysis that answers the business’s day to day shopper questions, helps turn that analysis into clear stories that people act on, and keeps ad hoc research projects organised and on track.
Sitting in the Strategy, Insights & Data team and reporting into the Shopper & Consumer Insights Manager, the role works across continuous data, shopper loyalty and panel data, and custom research. It supports the evaluation of in outlet activation and point of sale, helps prepare the evidence that feeds Business Planning and campaign design, and spends regular time in store to stay close to the real shopper.
This is a structured, hands on learning year with genuine responsibility. The intern will work with Customer Marketing, Trade Marketing and agency partners from day one, follow an agreed development plan with regular check ins, and by the end of the year own at least one project from brief to recommendation. Curiosity about why people buy what they buy matters more than experience.
Every application is reviewed by a member of our recruitment team. We take a people-first approach to hiring, ensuring that every application receives thoughtful consideration. However, due to the expected volume of applications this process may take a little longer than usual, so we appreciate your patience. In the meantime, we encourage you to explore the world of Red Bull!
Responsibilities
Areas that play to your strengths
All the responsibilities we'll trust you with:
- SHOPPER AND CATEGORY ANALYSIS
- STORYTELLING WITH DATA
- SUPPORTING THE AD HOC RESEARCH PROGRAMME
- SUPPORTING MEASUREMENT OF ACTIVATION AND POINT OF SALE
- GETTING CLOSE TO THE SHOPPER
- INSIGHT OPERATIONS AND KNOWLEDGE SHARING
Travel 0-10%
SHOPPER AND CATEGORY ANALYSIS
- Run regular and ad hoc analysis that supports the team’s view of the shopper across Off and On Premise. Learn to use continuous data (NIQ, Circana) and shopper loyalty and panel data (Kantar) to pull and interpret the core shopper KPIs: penetration, frequency, repeat, switching, basket and source of volume. Check the numbers carefully, flag what has changed, and build towards bringing a first point of view to the manager rather than raw outputs.
STORYTELLING WITH DATA
- Help turn analysis into clear, well designed outputs that people act on: headline first, evidence second, implication third. Build charts, one page summaries and presentation sections for Business Planning, customer meetings and campaign reviews, and learn to adapt the same insight for different audiences. Present findings to stakeholders during the year, starting within the team and building up to wider forums.
SUPPORTING THE AD HOC RESEARCH PROGRAMME
- Provide day to day coordination for the ad hoc research programme, working alongside the manager, who owns briefs, agency selection and budget. Keep timelines, fieldwork checkpoints, stakeholder reviews and debrief logistics on track, help draft briefs and compare agency proposals, maintain the research spend tracker, and close every project with outputs stored, actions logged and the decision it informed recorded.
SUPPORTING MEASUREMENT OF ACTIVATION AND POINT OF SALE
- Support the measurement framework for trade marketing assets. Help set up pre and post analysis, maintain the tracker of activations tested and their results, and gather the evidence on which point of sale, creative and communication drive trial and conversion. Write up each evaluation as a short, reusable learning so the next campaign starts from what we already know.
GETTING CLOSE TO THE SHOPPER
- Spend regular time in outlet through store visits, shop-alongs and observation, alongside Field Sales and agency partners, to bring the data to life and test our assumptions. Support qualitative and quantitative fieldwork, from survey and discussion guide input to in store observation, and feed what you see back into the team’s thinking.
INSIGHT OPERATIONS AND KNOWLEDGE SHARING
- Help keep the insight engine running. Maintain the regular reports and dashboards, support data deliveries and quality checks with data providers, and keep the insight repository organised so anyone in the business can find what we already know. Produce a regular insight digest and, before the internship ends, document processes and hand over live work so the next intern or team member can pick it up without losing momentum.
Experience
Your areas of knowledge and expertise
What matters most for this role:
- No previous insight experience required. A university project, part time job, society role or earlier internship that shows you can work with numbers and with people is a plus.
- Strong numerical and analytical skills, comfortable in Excel (pivot tables, lookups, charting), careful with detail and keen to learn how to work with large data sets.
- Ability to turn numbers into a clear story, with good PowerPoint skills and an eye for simple, well designed visual outputs.
- Well organised, able to juggle several tasks and deadlines at once and keep people updated on progress.
- Clear written and verbal communication, and the confidence to ask questions, share a view and present your own work.
- Genuine curiosity about shoppers, consumers and retail, and a proactive, hands on approach to learning.
- Exposure to NIQ, Circana or Kantar data, research methods (surveys, focus groups, shop-alongs) or tools such as Power BI, Tableau or SQL, for example through your degree, is an advantage but not required.
- Interest in using AI and self-serve data tools to work faster and smarter is an advantage.
