Digital Department

Data Analyst

Roles & Key responsibilities

The Job

 
 

Role Purpose

The Data Analyst will strengthen TDM's data-driven decision-making by converting campaign, audience, media, PR, social, client and business data into clear insights, dashboards and recommendations. The role supports strategy, creative, digital, PR, media buying, client service and management by ensuring that reports move beyond data presentation to business interpretation. The Data Analyst will help TDM measure client results, improve delivery excellence, reduce reporting inconsistencies, support pitches and build repeatable measurement systems for a 360-degree agency model.

Key Responsibilities

1. Design measurement frameworks for campaigns, retainers and pitches, including clear objectives, KPIs, data sources, tagging requirements, baselines and reporting cadence.

2. Collect, clean, validate and analyse data from digital platforms, websites, social analytics, media reports, PR coverage, influencer reports, client datasets, CRM exports and internal performance records.

3. Build dashboards, campaign reports, monthly retainer reports, quarterly business reviews and post-campaign analyses that are accurate, visual, executive-ready and decision-useful.

4. Work with media, PR, digital, creative and client service teams to define what success means before campaigns go live and to ensure tracking requirements are in place early.

5. Analyse campaign performance, customer/audience behaviour, content performance, media efficiency, sentiment, share of voice, conversion funnels and competitor activity to generate actionable recommendations.

6. Support proposal development with audience insights, category research, competitor benchmarking, performance benchmarks, market context and evidence-based recommendations.

7. Establish data quality checks, data dictionaries, reporting templates, UTM/tagging governance, dashboard standards and version control to reduce errors and inconsistencies.

8. Use AI and automation responsibly to speed up data cleaning, pattern detection, reporting and analysis while independently validating conclusions before client use.

9. Train and support teams on data interpretation, reporting discipline, dashboard use and the difference between activity metrics and business outcomes.

10. Maintain confidentiality, ethical data handling, source documentation and clear assumptions in all analyses and client-facing outputs.

Skills & Competencies