UK

United Kingdom · Marketing · Mid-Level (2-5 years)

Digital Analytics Analyst

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

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Free to start: a plan built for this role, and a Future Fluency module to try first. No card.

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One email: what AI is changing in this job, and where to start free. With a link back here. Nothing else follows unless you confirm your address.

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  • Experience bandMid-Level (2-5 years)
  • Direct reportsNo direct reports
  • Reports toSenior Digital Analytics Analyst
  • UK framework levelUsually a coordinator, or early in a professional job

Also advertised as Marketing Data Analyst · Web Analytics Specialist · Performance Marketing Analyst

Built on 43,079 real UK job descriptions we analysed · grounded in qualifications employers recognise

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

OCNLR Level 4 Certificate in Digital Marketing OCN London · Level 4 · covers 3 of 10 standards
OCNLR Level 4 Diploma in Digital Marketing OCN London · Level 4 · covers 3 of 10 standards
ATHE Level 4 Extended Diploma in Digital Marketing ATHE Ltd · Level 4 · covers 3 of 10 standards
City & Guilds Level 3 Diploma in Digital Marketing City and Guilds of London Institute · Level 3 · covers 3 of 10 standards
OCNLR Level 4 Award in Digital Analytics OCN London · Level 4 · covers 2 of 10 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Digital Analytics OCNLR Level 4 Certificate in Digital Marketing
Digital Business, Marketing Metrics and Analytics ATHE Level 4 Extended Diploma in Digital Marketing
Digital marketing metrics and analytics City & Guilds Level 3 Diploma in Digital Marketing
Data and digital marketing Cambridge OCR Level 3 Alternative Academic Qualification Cambridge Advanced National in IT: Data Analytics (Certificate)

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
Systems Fluency seeing the whole picture
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Your Plan Illustration

Built for Digital Analytics Analyst

4 units that map to this job, from the qualifications that cover it.

  1. Digital Analytics OCN London · covers 3 of 10 standards Level 4
  2. Digital Business, Marketing Metrics and Analytics ATHE Ltd · covers 3 of 10 standards Level 4
  3. Digital marketing metrics and analytics City and Guilds of London Institute · covers 3 of 10 standards Level 3
  4. Data and digital marketing Cambridge OCR · covers 1 of 10 standards Level 3
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Digital Analytics Analyst?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skill this role is being asked for

  • Advanced Data Storytelling & Visualisation
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Digital Analytics Analyst plan as you set up, starting with a Future Fluency module on using AI in your job. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

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3What this role really is

A Digital Analytics Analyst reports on marketing data and explains what campaign performance figures mean. The work covers regular reporting and digging into campaign performance to work out what's working and what's not. It means turning numbers into findings that a marketing team can use to make decisions. The work involves looking for patterns and clues in digital campaign data.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

Google Analytics 4 (GA4) Intermediate

Pulling standard traffic and conversion reports, setting up basic events, building custom explorations, and understanding the event-based data model.

Google Tag Manager (GTM) Intermediate

Understanding containers, tags, triggers, and variables. You'll be able to implement pre-defined tracking tags and debug basic firing issues with some supervision.

Looker Studio (formerly Data Studio) Intermediate

Connecting to GA4 and other data sources, building basic dashboards from templates, and updating existing reports for weekly and monthly performance reviews.

Excel / Google Sheets Advanced

Proficient with VLOOKUP/INDEX-MATCH, Pivot Tables, conditional formatting, and standard formulas for cleaning, organising, and analysing exported data. You'll use this a lot for ad-hoc analysis.

SQL (PostgreSQL / BigQuery) Intermediate

Writing basic `SELECT...FROM...WHERE` queries to pull data from a single table. You'll also be able to perform simple `JOIN` operations with guidance to combine datasets.

HubSpot / Salesforce Marketing Cloud Basic

Navigating the platform to export campaign performance data and contact lists for analysis, understanding where to find key marketing metrics.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Daily Task Prioritisation Follows explicit instructions from supervisor. Prioritises routine tasks independently based on agreed deadlines; escalates conflicts to Senior Analyst. Sets priorities for own workstreams and influences team priorities.
Data Extraction & Cleaning Methodology Uses pre-defined queries and cleaning templates under supervision. Chooses appropriate SQL queries and data cleaning methods for ad-hoc requests; consults Senior Analyst on complex transformations. Designs and optimises complex data extraction and transformation pipelines.
Reporting & Dashboard Design Updates existing dashboards; builds new reports from templates with guidance. Designs and builds new basic dashboards from scratch; recommends improvements to existing reports based on stakeholder needs. Defines reporting standards and key metrics for specific marketing channels/workstreams.
Tracking Implementation (GTM) Implements pre-defined tags, triggers, and variables with direct supervision. Independently implements standard tracking events and parameters; identifies and debugs basic tracking issues. Designs and implements complex tracking solutions; establishes and enforces GTM governance.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Report Accuracy
The precision and correctness of all standard and ad-hoc reports you produce.
Target · >98% accuracy on all reports

You'll spot a discrepancy between GA4 and Google Ads data, investigate, and correct it before anyone else notices, ensuring the weekly report is flawless.

Ad-Hoc Request Turnaround Time
How quickly you deliver on specific data requests from the Marketing team.
Target · 90% of requests delivered within agreed 48-hour SLA

A channel manager needs conversion data for a specific campaign by Friday morning; you deliver it by Thursday afternoon, complete with a quick summary.

Dashboard & Tracking Health
The reliability and up-to-dateness of our key performance dashboards and the underlying tracking.
Target · All 15 weekly dashboards updated by 9 AM every Monday; <1 critical tracking error per quarter

You'll notice a drop in 'add to basket' events in GA4, quickly check GTM, and realise a tag has stopped firing, then fix it before it impacts reporting for too long.

Campaign Performance Insight Contribution
Your ability to provide clear, data-driven observations on specific marketing campaigns.
Target · At least 1 actionable insight per month that directly influences a campaign adjustment

You identify that a particular ad creative has a significantly lower conversion rate on mobile devices, leading the Paid Media team to pause it and test a mobile-optimised version.

Clarity of Communication
How well you explain complex data findings to non-technical marketing colleagues.
  • Stakeholders consistently understand your reports
  • you're able to simplify jargon
  • you get positive feedback on your explanations during meetings. People don't just nod politely
  • they actually 'get it'.
Proactive Problem Identification
Your initiative in spotting potential issues (e.g., data discrepancies, tracking errors) before they become major problems.
  • You flag data anomalies before others do
  • you suggest improvements to our tracking setup
  • you anticipate reporting needs. Basically, you're not just waiting to be told what to do.
Stakeholder Satisfaction with Support
How helpful and responsive the Marketing team finds your data support.
  • Channel managers regularly come to you for data questions
  • they express appreciation for your help
  • your insights are genuinely used in their decision-making. They see you as a partner, not just a report generator.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Solving Puzzles with Data

You love diving into a messy dataset, finding the patterns, and figuring out why something happened. It's like being a detective every day.

You're given a report showing a sudden drop in conversions for a specific region. You enjoy digging into the traffic sources, landing page performance, and device types to pinpoint the exact cause.

Seeing Your Work Make a Difference

You get a real kick out of knowing your analysis directly helped a marketing campaign perform better or stopped a bad decision from being made.

You highlight a specific audience segment that's underperforming, and the Paid Media team adjusts their targeting, leading to a noticeable improvement in ROI—and you know it was your insight.

Continuous Learning & Mastery

You're always keen to learn new tools, advanced analytical techniques, or better ways to visualise data. You enjoy becoming really good at what you do.

You proactively take an online course in advanced SQL or experiment with a new feature in GA4, even if it's not immediately required for a project, just to expand your skills.

What frustrates people
  • The 'Garbage In, Garbage Out' Principle: You'll spend a fair bit of time cleaning up messy data caused by inconsistent campaign tagging from the very marketing team you're trying to support. It's frustrating when the foundation isn't solid.
  • Stakeholder Whiplash: You might get an 'urgent' request for a deep-dive analysis, spend days on it, only to have the stakeholder ignore the findings or completely change their priorities the next day. It happens more often than you'd think.
  • Platform Discrepancies: You'll explain for the hundredth time why the number of clicks in Google Ads will never perfectly match the number of sessions in Google Analytics. It's just how the systems work, but people still ask.
  • The 'Quick Question' Ambush: The 2-minute question from a manager that you know will actually take four hours of complex querying and analysis to answer properly. Sometimes you just have to manage expectations.
What this role does not give you
  • A completely predictable daily routine (expect some curveballs).
  • A role where you only ever work with perfectly clean, structured data.
  • Guaranteed immediate implementation of every single insight you provide.
  • A job where you don't have to explain basic concepts multiple times.

8Who you work with

This role directly impacts the effectiveness of our marketing spend and the accuracy of our performance measurement. You'll help us allocate budget more efficiently, improve campaign ROI, and ensure we're making data-backed decisions rather than just guessing. Essentially, you're helping us get more bang for our buck and prove Marketing's value to the wider business.

Inside the business
  • Marketing Channel Managers (Paid Media, SEO, Email)
  • Content Marketing Team
  • Product Marketing Team
  • Sales Team (for lead quality insights)
Outside the business
  • Digital Marketing Agencies (for data sharing and reporting alignment)
  • Platform Vendors (e.g., Google, Adobe for support issues)

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • A minimum of 2 years of hands-on experience in a digital analytics or marketing data role, where you were regularly pulling and analysing performance data.
  • Demonstrable experience with Google Analytics 4 (GA4) for reporting and basic analysis, or a similar web analytics platform.
  • Proven ability to write basic SQL queries to extract data from databases.
  • Strong proficiency in Excel or Google Sheets for data manipulation and presentation.
  • A genuine curiosity for data and a desire to understand 'why' things are happening in our marketing performance.

10What to practise next

Where the job is going, and what to do about it starting this week.

Advanced SQL for Deeper Insights

As our data warehouse grows and we integrate more sources, you'll need to move beyond basic queries. The ability to pull and transform complex datasets efficiently will be crucial for answering more sophisticated business questions.

Window Functions · Common Table Expressions (CTEs) · Complex Joins & Subqueries · Query Optimisation

  • This month: Dedicate an hour a week to SQL practice platforms (e.g., LeetCode, HackerRank) focusing on intermediate problems.
  • Next quarter: Ask your Senior Analyst for opportunities to work on more complex data extraction tasks.
  • Month 4-6: Take an advanced SQL course specifically for data analysts.
  • Ongoing: Review query logs to understand how your queries are performing and identify areas for improvement.

Quick win: Next time you need to combine data, challenge yourself to use a CTE instead of a subquery. It's a small change that makes a big difference in readability.

AI-Powered Analytics & Prompt Engineering

AI isn't just a buzzword; it's rapidly becoming a core tool for analysts. Knowing how to effectively 'talk' to AI models (prompt engineering) and integrate them into your workflow will significantly boost your productivity and insight generation.

Prompt Engineering Basics · AI for Anomaly Detection · AI for Data Summarisation · Output Validation & Hallucination Detection

  • This week: Start using ChatGPT or Claude for simple tasks like drafting email summaries or generating ideas for report structures.
  • This month: Experiment with using AI to help you write or debug simple SQL queries.
  • Next quarter: Explore an AI-powered analytics platform (e.g., Google Analytics' AI features, or a dedicated anomaly detection tool) and see how it works.
  • Ongoing: Stay updated on new AI tools and features relevant to analytics through industry blogs and webinars.

Quick win: Use an LLM to draft a few different headlines for your next report. You'll be surprised how quickly it can generate options you might not have thought of.

11Staying current once you are in

What people here do to keep up
  • Regularly follow industry blogs and thought leaders in digital analytics (e.g., Avinash Kaushik, Measure Slack community).
  • Attend relevant webinars or virtual conferences to stay updated on new tools and techniques.
  • Take online courses on platforms like DataCamp, Coursera, or Udemy to deepen your SQL, Python (for data analysis), or data visualisation skills.
  • Participate in data analytics communities or forums to learn from peers and share knowledge.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Advanced Data Storytelling & Visualisation

As data gets more complex and AI handles more of the raw analysis, your ability to translate findings into compelling, actionable narratives for senior leaders becomes absolutely critical. It's not enough to have the numbers; you need to make them sing.

  • Audience-Centric Storytelling
  • Narrative Structure
  • Effective Visualisation Principles
  • Actionable Recommendations

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • UTM Tagging & Campaign Tracking Governance
  • A/B & Multivariate Testing Support
  • Customer Segmentation & Basic Cohort Analysis
  • Conversion Rate Optimisation (CRO) Principles
  • Attribution Modelling Concepts

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Junior Digital Analytics Assistant (L1)

    1-2 years

    Skills to master

    • Mastering basic reporting, accurate data entry, understanding core metrics, and learning our internal tools and processes under close supervision.

    You're ready to move on when

    • Consistently delivers accurate reports without errors.
    • Can independently pull basic data from GA4 and other platforms.
    • Proactively identifies minor data discrepancies.
    • Demonstrates a strong desire to learn and take on more responsibility.
  2. 2

    Marketing Intern / Graduate Scheme

    1-2 years

    Skills to master

    • Gaining exposure to various marketing channels, understanding business objectives, and developing foundational data literacy and analytical thinking.

    You're ready to move on when

    • Successfully completed analytics-focused projects during internship/scheme.
    • Can articulate the 'so what' behind basic marketing metrics.
    • Shows initiative in seeking out data to answer questions.
    • Has a good grasp of our overall marketing strategy.
  3. 3

    Data Entry / Operations Role with Analytical Focus

    2-3 years

    Skills to master

    • Developing strong data cleaning and manipulation skills, understanding data integrity, and building foundational SQL or Excel expertise.

    You're ready to move on when

    • Proven ability to manage and clean large datasets.
    • Can write intermediate Excel formulas or basic SQL queries.
    • Has a keen eye for detail and data accuracy.
    • Actively sought out analytical tasks within their previous role.

15Where this role leads

The long view: This work starts with making marketing data useful. From there it can lead to a technical specialist role, a team leader role, or a strategic role shaping analytics direction.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Digital Analytics Analyst is actually changing.

Where it leads

Roles this leads to

The record names a next step, but the catalogue has no page for it yet:

  • Senior Digital Analytics Analyst (L3)
  • Marketing Channel Specialist (e.g., SEO Analyst, Paid Media Specialist)

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Digital Analytics, worked against Digital Analytics Analyst.

Digital Analytics Level 4

Applied to your work in Digital Analytics Analyst

This unit aims to provide learners with a comprehensive understanding of digital analytics principles, tools, and techniques. Learners will develop the skills to collect, analyse, and interpret digital data from various sources, enabling them to measure the effectiveness of digital marketing campaigns, improve strategies, and report findings to stakeholders, while adhering to data protection regulations.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

Start my Digital Analytics Analyst plan, free
See Your Progress Grow Illustration
Digital Analytics Analyst
  • UTM Tagging & Campaign Tracking Governance
  • A/B & Multivariate Testing Support
  • Customer Segmentation & Basic Cohort Analysis
  • Conversion Rate Optimisation (CRO) Principles
  • Attribution Modelling Concepts
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Digital Analytics Analyst is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. Senior Digital Analytics Analyst (L3)

    2-3 years

    This is the natural next step, where you'll move from owning routine reports to leading specific analytical workstreams and providing deeper, more strategic insights.

    • Designing and implementing complex A/B tests end-to-end.
    • Developing custom attribution models.
    • Advanced SQL for complex data manipulation and modelling.
    • Building and maintaining sophisticated dashboards in Tableau/Power BI.
    • Leading GTM architecture and governance.

  2. Marketing Channel Specialist (e.g., SEO Analyst, Paid Media Specialist)

    2-4 years

    This is a lateral move into a specialist role, where your analytical skills are applied directly to optimising a specific marketing channel. You'd become the expert for that channel's data.

    • Advanced platform skills (e.g., Google Ads, Facebook Ads Manager, SEMrush).
    • Keyword research and content optimisation.
    • Bid management and audience targeting strategies.
    • Creative testing and optimisation.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be honest, a big chunk of an analyst's job can be repetitive, time-consuming, and frankly, a bit tedious. But what if you could offload some of that grunt work to AI? Imagine spending less time on manual tasks and more time on the really interesting stuff – the deep insights and strategic thinking.

For a Digital Analytics Analyst in Marketing, AI isn't about replacing your job; it's about making you significantly more productive and effective. It's like having a super-smart assistant that handles the routine, spots things you might miss, and even helps you articulate your findings better. This means you can focus on the 'why' and the 'what next', rather than just the 'what happened'.

Automated Performance Summaries

Imagine AI tools connecting directly to your GA4 and Google Ads APIs. They can auto-generate the first draft of your weekly performance emails, flagging top-performing campaigns, pointing out anomalies (like a sudden traffic drop), and writing concise bullet-point summaries. You just review, refine, and send. It's a huge time-saver.

Accelerated Anomaly Detection

Instead of manually scanning dozens of metrics every day, you can feed daily performance data into an AI model. It'll proactively identify statistically significant deviations from the norm. You'll get an alert saying, 'Organic traffic from mobile in the UK is down 30% vs. the 4-week average,' letting you investigate immediately, rather than discovering it days later.

SQL Query Generation & Debugging

Stuck on a complex SQL query? Or just want to write one faster? AI assistants can translate natural language questions (e.g., 'Show me the conversion rate for users who came from Facebook ads in May and viewed the pricing page') into robust SQL. They can also help debug and optimise your existing queries that are running slowly, saving you a lot of head-scratching.

Data Storytelling & Chart Recommendations

Got a raw dataset but struggling to find the narrative for your next presentation? Provide the data to an AI tool and ask it to identify key trends and suggest the best chart types to visualise the information. It can even help structure a narrative, ensuring your key message isn't lost in a sea of numbers. It's like having a presentation coach on demand.

Common questions

Common questions

How do you become a Digital Analytics Analyst?

Common routes in include Junior Digital Analytics Assistant (1-2 years), Marketing Intern / Graduate Scheme (1-2 years) and Data Entry / Operations Role with Analytical Focus (2-3 years). Times vary with prior experience.

Where can a Digital Analytics Analyst progress to?

This role can lead on to Senior Digital Analytics Analyst (2-3 years) and Marketing Channel Specialist (e.g., SEO Analyst, Paid Media Specialist) (2-4 years), depending on the skills you build.

What new skills matter most for a Digital Analytics Analyst?

Increasingly, Advanced Data Storytelling & Visualisation. These are the skills our record of this role lists as growing.

Free tools

Want a read on where you stand?

Three free tools, no account needed. Each one ends with a role, a level and a way in.

Read the Zavmo manifesto to understand how you will be taught Meet your tutors

Or try another one

17Where to go from here

Other roles at Level 3

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in marketing

Stay in the field you know and move sideways rather than up.
If you leave this industry

Skills in data analysis, visualisation, SQL, and reading digital marketing performance transfer well. They can lead into broader Business Intelligence roles, Product Analytics, or Data Analyst positions in other industries such as e-commerce, finance, or tech. Data skills are in demand across sectors.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my Digital Analytics Analyst plan, free What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.