Client Retention and Insights Analyst - Henley Business School
Listed on 2026-02-28
-
Business
Data Analyst, Data Scientist -
Marketing / Advertising / PR
Client Retention & Insights Analyst
6-Week Strategic Project | The Marketing Centre
Please note this is only open to Masters students at Henley Business School
About The Marketing CentreThe Marketing Centre is a UK-wide provider of fractional Chief Marketing Officers (CMOs) to ambitious SMEs. We place experienced, board‑level marketing leaders into growing businesses that require strategic marketing direction but do not need a full‑time CMO.
Our CMOs embed into leadership teams, typically one day per week, helping shape strategy, improve marketing performance and drive commercial growth. Clients gain access to senior marketing leadership in a flexible and commercially efficient model.
As a relationship‑led professional services business, long‑term client partnerships are central to our success. We are investing in a deeper understanding of what drives client longevity and lifetime value within our model.
This project sits at the heart of that work.
The OpportunityWe are seeking one or two exceptional Masters in Business Management students to undertake a six‑week strategic project focused on client retention and lifetime value.
This is not a theoretical exercise. It is a live commercial challenge sponsored by senior leadership.
You will work directly with business data, identify patterns that matter, and develop recommendations that will inform real decisions about how we strengthen client relationships across the UK.
The project combines data analysis, commercial thinking and structured problem solving. It requires intellectual rigour, sound judgement and the confidence to present clear conclusions to senior stakeholders.
Project AimTo use data and targeted client insight to understand the drivers of client retention at The Marketing Centre and identify practical, high‑impact opportunities to strengthen long‑term client relationships.
Scope of WorkOver six weeks, you will:
1. Define the Analytical Framework- Agree how retention will be defined and measured.
- Clarify the time period and scope of analysis.
- Identify key data sources and relevant variables.
This stage will establish the foundation for disciplined analysis.
2. Prepare and Structure the Data- Clean and organise historical client data.
- Create a structured dataset suitable for analysis.
- Segment clients by relevant dimensions (e.g. tenure, region, sector).
The focus is on building a reliable base for meaningful insight.
3. Analyse Retention Patterns- Review retention trends over time.
- Compare retention across segments.
- Identify differences and potential early indicators of disengagement.
The objective is to move beyond surface observation and identify patterns that matter.
4. Identify and Assess Key Drivers- Explore which measurable factors are most closely associated with client longevity.
- Distinguish correlation from commercially meaningful drivers.
- Prioritise insights based on potential business impact.
Complex modelling is not required, but structured, disciplined analysis is essential.
5. Conduct Targeted Client ConversationsYou will conduct a small number of structured client interviews to provide qualitative context to the data.
These discussions will explore:
- What clients value most
- What influences their decision to continue working with us
- Where we can further strengthen the client experience
The aim is to explain and validate data findings.
6. Quantify Commercial Implications- Estimate the potential impact of improving retention.
- Translate analytical findings into clear commercial implications.
- Identify a focused set of practical, high‑impact actions.
- Distinguish between immediate improvements and longer‑term opportunities.
- Present findings in a concise, senior‑ready format.
Your final presentation will be delivered to the leadership team.
What We Are Looking ForThis opportunity is suited to high‑performing students who are motivated by real business impact.
The ideal candidate will demonstrate:
Analytical Strength- Confidence working with structured datasets.
- Ability to clean, interpret and extract insight from data independently.
- Familiarity with tools such as Excel, Power BI or similar.
You must be comfortable moving from raw data to…
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