UK

United Kingdom · Marketing · Entry Level (0-2 years)

Marketing Intelligence Analyst

Here is the whole job, in plain words. What it is, a real day, 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.

  • Experience bandEntry Level (0-2 years)
  • Direct reportsNo direct reports
  • Reports toMarketing Intelligence Manager
  • UK framework levelUsually someone starting out, or keeping a process running

Also advertised as Junior Marketing Analyst · Data Analyst, Marketing · Marketing Reporting Specialist

Built on an analysis of 43,079 real UK job descriptions · grounded in qualifications employers recognise

Start with a free Future Fluency check, tuned to Marketing Intelligence Analyst

Ten quick questions, one per Future Fluency, asked against this role rather than a generic one. About five minutes, and no card.

Start the check, free

1What this role really is

This role is all about getting your hands dirty with marketing data. You'll be the person pulling the numbers, building the reports, and making sure our dashboards are always up-to-date and accurate. Essentially, you're helping the wider Marketing team understand what's actually happening with our campaigns and customers, giving them the raw material for better decisions.

2What you'd actually use

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

TableauIntermediate

Building and maintaining standard marketing performance dashboards, creating new visualisations from clean data sources, using filters and calculated fields.

SQL (Google BigQuery)Intermediate

Writing SELECT statements with joins, aggregations (GROUP BY), and filtering (WHERE/HAVING) to pull specific marketing data from our data warehouse.

Google Analytics (GA4)Intermediate

Navigating the UI to pull standard reports on website traffic, events, and conversions, building basic explorations and audiences for campaign analysis.

Salesforce Marketing Cloud / Sales CloudBasic

Pulling reports and building simple dashboards on campaign performance, email engagement, lead sources, and basic pipeline stages. Understanding the basic object model.

Microsoft Excel / Google SheetsAdvanced

Performing complex data manipulation, cleaning, pivot tables, VLOOKUPs, and basic charting for ad-hoc analysis and data preparation.

3What 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 inWhere you are nowThe step above
Data Extraction MethodUse pre-approved SQL queries or UI exports. If a new method is needed, propose it to your manager for review and approval.Choose appropriate extraction methods for routine analyses. Consult manager for complex or novel data sources.Design and implement new data extraction pipelines. Approve methods for junior analysts.
Report/Dashboard DesignFollow existing templates and design guidelines. Any deviation requires manager approval.Adapt existing templates for new requests. Propose minor design improvements to manager.Design new report templates and dashboard structures. Set design standards for the team.
Data Interpretation & InsightsFocus on accurate reporting of 'what happened'. Any interpretation or 'why' should be discussed with your manager before sharing.Provide initial interpretations for routine analyses. Highlight key trends and potential drivers.Develop actionable insights and recommendations based on complex analysis. Present findings to stakeholders.
Tool/Software SelectionUse the tools provided (Tableau, SQL, GA4). Do not introduce new software without explicit manager approval.Suggest new features or minor tool integrations. Research and propose new tools for specific analytical needs.Recommend and evaluate new analytical tools or platforms for team adoption. Influence tech stack decisions.

4How you'll be judged

The scoreboard, honestly: the hard targets, how often each one is actually looked at, and the quiet human signals that never make it onto a dashboard.

Report Accuracy
The percentage of reports and dashboards delivered without errors or discrepancies.
Target · >99% accuracy on all standard reporting

You pull a weekly campaign performance report. If there are no incorrect figures or mislabelled charts, that's 100% accuracy. One small error, and it drops.

Ad-Hoc Request Turnaround Time
How quickly you complete urgent, one-off data requests from the team.
Target · Ad-hoc data pulls completed within 24-hour SLA (Service Level Agreement) for routine requests

A campaign manager asks for conversion rates from a specific email segment. If you deliver it within 24 hours, you've met the target.

Dashboard Uptime & Freshness
Ensuring that key marketing dashboards are always available and showing the most up-to-date data.
Target · >99.5% uptime for managed dashboards; data refreshed daily by 9 AM

The 'Weekly Campaign Overview' dashboard is accessible and shows yesterday's data by 9 AM every morning. If it's down or showing old data, that counts against you.

Data Consistency Across Sources
How well you ensure that similar metrics (e.g., website visits) match up when pulled from different systems.
Target · Identified and reconciled >95% of minor data discrepancies before reporting

You notice Google Analytics and Salesforce Marketing Cloud show slightly different numbers for email clicks. You investigate, understand why, and document the difference or reconcile it.

Learning & Development
Your proactive effort to learn new tools, methodologies, and marketing concepts.
  • Regularly asking insightful questions, completing assigned training modules, actively participating in team knowledge shares, showing demonstrable improvement in skill assessments over time.
Adherence to Best Practices
Following established data governance, reporting, and documentation standards.
  • Your SQL queries are clean and commented, dashboards follow our design guidelines, documentation for new reports is always up-to-date, and you consistently use approved data definitions.
Proactive Issue Identification
Spotting potential data problems or reporting issues before they become bigger problems for the team.
  • You flag unusual data spikes or drops in a report before your manager asks about them, or you notice a data pipeline failure and alert the right people without being prompted.
Team Collaboration & Communication
How effectively you work with your immediate team and communicate your progress and findings.
  • You respond quickly to team messages, clearly explain your process when asked, ask for help when stuck, and contribute positively to team meetings. People feel comfortable coming to you with questions.

5Would you like it

The honest version. What people enjoy, and what grinds them down.

What people enjoy
Seeing Your Work Used

You'll get a real kick out of seeing a campaign manager change their ad spend based on a report you built, or a product marketer adjust their messaging because of your customer behaviour analysis.

You create a report showing which ad creatives perform best. The Head of Digital Marketing then uses that exact report to reallocate £50K of budget, and you see the impact.

Mastering New Tools & Techniques

You love diving deep into a new SQL function, figuring out a complex Tableau dashboard, or understanding how Google Analytics 4 actually tracks events. The process of learning and becoming proficient is a big driver for you.

You spend a Saturday morning playing with a new feature in Tableau, then bring that knowledge back to the team, showing them a more efficient way to visualise data.

Building a Solid Foundation

You're motivated by the idea of becoming an expert in marketing data. This role provides the perfect opportunity to build fundamental skills that will set you up for a long career in analytics.

You're proud of your clean, well-commented SQL queries because you know they're the building blocks of good data practice, and you're actively working towards a more senior role.

What frustrates people
  • Spending 60% of your time cleaning up messy data from different systems before you can even start analysing it.
  • Getting vague requests like 'can you just pull all the marketing data?' without clear definitions or objectives.
  • Having to explain the same basic data concept (like unique users vs. total sessions) multiple times to different people.
  • Building a detailed report only for it to be dismissed because someone 'has a gut feeling' that contradicts the data.
  • Dealing with legacy systems that are slow, clunky, and don't play nicely with modern tools.
What this role does not give you
  • Immediate strategic decision-making authority.
  • A quiet, predictable routine with no urgent requests.
  • The ability to completely ignore data cleaning; it's a core part of the job.
  • A role where you're always presenting to senior leadership (that comes later).
  • An environment where every single piece of your analysis leads to a major business change.

6Who you work with

Your work directly underpins the daily decisions of our marketing teams. Accurate and timely data means they can optimise campaigns, adjust strategies, and allocate budget more effectively. If the data's off, or late, it can lead to wasted spend and missed targets. You're a crucial part of making sure our marketing efforts aren't just guesses.

Inside the business
  • Marketing Intelligence Manager (your direct boss, for guidance and review)
  • Campaign Managers (they'll ask for performance reports)
  • Product Marketing team (they'll want to see how new features are landing)
  • Digital Marketing Specialists (for SEO/SEM data)
  • Sales Operations (occasionally, for lead quality data)
Outside the business
  • Digital Agencies (for data on paid media campaigns, though you won't directly manage them)

7What you need before you start

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

  • A genuine interest in data and how it can be used to make business decisions.
  • Some prior experience (even academic or personal projects) with data analysis using tools like Excel, SQL, or a BI platform.
  • A foundational understanding of basic statistics and quantitative methods.
  • The ability to communicate clearly, both in writing and verbally, especially when explaining data.
  • A degree in a quantitative field (e.g., Marketing, Business, Economics, Maths, Statistics, Computer Science) or equivalent demonstrable experience.

8What to practise next

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

Advanced SQL for Data Modelling

As our data grows and becomes more complex, you'll need to move beyond simple SELECT statements. Building more efficient and robust data models directly impacts the speed and reliability of our reporting.

Common Table Expressions (CTEs) · Window Functions · Subqueries & Derived Tables · Indexing & Query Optimisation

  • This quarter: Find online tutorials or courses specifically on advanced SQL (e.g., DataCamp, Udemy).
  • Next quarter: Start refactoring some of your existing simple queries using CTEs or window functions.
  • Month 6: Take on a small project to build a new, slightly more complex data view using advanced SQL.
  • Month 9: Get your manager or a senior analyst to review your advanced SQL for feedback and best practices.

Quick win: Start by rewriting one of your longest SQL queries using a CTE. You'll immediately see how much cleaner it looks.

Introduction to Python for Data Analysis

While SQL and Tableau are great, Python opens up a whole new world for more sophisticated data manipulation, statistical analysis, and even basic machine learning. It's becoming the lingua franca for serious data work.

Pandas Library · NumPy Library · Basic Data Visualisation (Matplotlib/Seaborn) · Jupyter Notebooks

  • This quarter: Complete an 'Introduction to Python for Data Science' course online.
  • Next quarter: Start using Python for simple data cleaning tasks that you currently do in Excel.
  • Month 6: Try to connect Python to one of our data sources (e.g., Google Analytics API) to pull data directly.
  • Month 9: Build a simple, automated report in Python that generates a CSV or basic chart.

Quick win: Install Anaconda and Jupyter Notebooks. Try to load a CSV file into a Pandas DataFrame and perform a simple aggregation.

9Staying current once you are in

What people here do to keep up
  • Enrolling in online courses for SQL, Tableau, or Python (we often cover costs for relevant training).
  • Attending industry webinars or virtual conferences on marketing analytics trends.
  • Participating in internal knowledge-sharing sessions with the wider Marketing team.
  • Reading industry blogs and publications to stay up-to-date on new tools and methodologies.
  • Working on personal data projects to experiment with new techniques and build your portfolio.

10How the AI economy is changing work like this

Before we ask anything of you, here's what we can already say about AI and work of this kind:

The new skill this role is being asked for: Basic Prompt Engineering for Marketing Data

AI language models (LLMs) are already changing how we summarise and interpret data. Competitors are using tools like ChatGPT to draft initial report narratives in minutes. Analysts who can 'talk' to these AIs effectively will be significantly more productive.

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

Your PlanIllustration

Built for Marketing Intelligence Analyst

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

  1. Analyse market research dataCity and Guilds of London Institute · covers 3 of 10 standardsLevel 3
  2. Marketing ResearchAIM Qualifications · covers 3 of 10 standardsLevel 2
  3. Analyse and report dataAIM Qualifications · covers 2 of 10 standardsLevel 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.

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.

Basic Prompt Engineering for Marketing Data

AI language models (LLMs) are already changing how we summarise and interpret data. Competitors are using tools like ChatGPT to draft initial report narratives in minutes. Analysts who can 'talk' to these AIs effectively will be significantly more productive.

  • Clear Instruction Giving
  • Context Provision
  • Output Validation
  • Iterative Prompting

What you’ll use

Skills this role draws on

Technical

  • Data Cleaning & Pre-processing
  • Basic Statistical Concepts
  • Data Visualisation Principles
  • Report Automation Basics

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

    Graduate Programme (Marketing/Data Analytics)

    0-1 year

    Skills to master

    • Foundational data analysis, basic SQL, Excel mastery, understanding of marketing fundamentals, strong communication.

    You're ready to move on when

    • Successfully completed all graduate rotations with positive feedback.
    • Delivered at least one end-to-end analytical project during the programme.
    • Demonstrated ability to work independently on routine data tasks.
  2. 2

    Junior Data Analyst (Non-Marketing Specific)

    1-2 years

    Skills to master

    • SQL querying, data cleaning, basic BI tool usage (e.g., Tableau, Power BI), strong attention to detail, ability to translate data into simple narratives.

    You're ready to move on when

    • Proven track record of accurate data delivery in a previous role.
    • Can demonstrate how their analytical skills apply to marketing scenarios.
    • Eagerness to learn specific marketing tools and metrics.
  3. 3

    Marketing Coordinator / Assistant (Data-Focused)

    1-2 years

    Skills to master

    • Deep understanding of marketing campaign mechanics, strong Excel skills, exposure to Google Analytics or similar tools, ability to identify data needs.

    You're ready to move on when

    • Actively sought out data-related tasks in their previous marketing role.
    • Can articulate how data improved a marketing outcome they were involved in.
    • Has started learning SQL or a BI tool in their own time.

11Where this role leads

The long view:Your journey starts here, building a rock-solid foundation in marketing data. We're excited to see where your curiosity and drive take you within our team and beyond.

Pay & demand

Pay and demand for this role will appear here, each figure traced to a named authoritative source (e.g. the ONS Annual Survey of Hours and Earnings, under the Open Government Licence). We don’t show numbers we can’t attribute.

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 Marketing Intelligence Analyst is actually changing. In about two minutes, the free confidence check asks where you stand on each of the ten. That's the whole check, and it's what makes the plan yours rather than generic.

Where it leads

Roles this leads to

12The team that's yours

No two people are taught the same way. This is one-to-one, not one-to-many.

Zavmo is a hyper-personalised AI learning platform. Twelve virtual tutors, each with a different way of teaching, and one orchestration agent that picks the right one for the moment. So every single lesson is shaped around you, your role, and the way you learn. Not a course everyone sits through. A conversation built for you, and no one else.

…and nine more, matched to you after your first chat. Meet all twelve

Start free and meet yours

13What it feels like

A conversation, not a course

Because your tutor knows your role, your projects and your last session, learning sounds like this. And it's different for every single person:

Analyse market research dataLevel 3

Applied to your work in Marketing Intelligence Analyst

This unit aims to provide learners with the knowledge and skills to analyse market research data using appropriate techniques and software tools. The objective of this unit is to enable learners to interpret market trends, understand the limitations of the data, and present findings in a clear and concise manner.

How the thinking builds
  1. Remember
  2. Understand
  3. Apply
  4. Analyse
  5. Evaluate
  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.

One to one, not one to many

No two people run this the same way

A course is written once and handed to everyone. This is assembled around you, and keeps changing as it learns you. Five things it reads, and what each one changes.

  1. Your actual work Every lesson is taught against a live piece of your own work, not a worked example from a textbook.
  2. What you already know The first conversation finds your starting point, so you skip what you can already do and spend the time on what you cannot.
  3. The conditions you learn under Not a learning-styles quiz. The evidence does not support those. The dimensions the research does back, read once and used to shape the plan.
  4. How far you got last time It picks up mid-thought. The tutor knows what you said, what you struggled with, and what it asked you to try.
  5. Which tutor suits the moment Twelve of them, each for a different kind of thinking. The one who walks you through a first idea is not the one who stress-tests it.

See how you learn, free. Eight questions, no sign-up. A directional taster; the diagnostic inside Zavmo goes deeper and keeps adapting.

DemonstrateIllustration

Evidenced on your work in Marketing Intelligence Analyst

You do not finish by watching something. You finish by showing it on the work you already do, against the measures this job is judged on.

  • Report AccuracyThe percentage of reports and dashboards delivered without errors or discrepancies.You pull a weekly campaign performance report. If there are no incorrect figures or mislabelled charts, that's 100% accuracy. One small error, and it drops.>99% accuracy on all standard reporting
  • Ad-Hoc Request Turnaround TimeHow quickly you complete urgent, one-off data requests from the team.A campaign manager asks for conversion rates from a specific email segment. If you deliver it within 24 hours, you've met the target.Ad-hoc data pulls completed within 24-hour SLA (Service Level Agreement) for routine requests
  • Dashboard Uptime & FreshnessEnsuring that key marketing dashboards are always available and showing the most up-to-date data.The 'Weekly Campaign Overview' dashboard is accessible and shows yesterday's data by 9 AM every morning. If it's down or showing old data, that counts against you.>99.5% uptime for managed dashboards; data refreshed daily by 9 AM
  • Data Consistency Across SourcesHow well you ensure that similar metrics (e.g., website visits) match up when pulled from different systems.You notice Google Analytics and Salesforce Marketing Cloud show slightly different numbers for email clicks. You investigate, understand why, and document the difference or reconcile it.Identified and reconciled >95% of minor data discrepancies before reporting
These are this job's own measures, with its own targets. Nothing is marked evidenced, because nobody has started this yet. Yours would fill in from the work you bring.

Your passport

This isn't a certificate you file away. It's a passport to the life you're designing.

Every credit you earn and every fluency you build adds up: evidence where it counts, carried with you. Zavmo keeps the map: where you are, where you're heading, and the next step, at your pace, around your life. From Marketing Intelligence Analyst to Marketing Intelligence Specialist (Level 002), and whatever you decide comes after.

Level 2 · in progressAI Fluency→ Marketing Intelligence Specialist (Level 002)→ your design
Where this takes you

Your journey starts here, building a rock-solid foundation in marketing data. We're excited to see where your curiosity and drive take you within our team and beyond.

See Your Progress GrowIllustration
Marketing Intelligence Analyst
  • Data Cleaning & Pre-processing
  • Basic Statistical Concepts
  • Data Visualisation Principles
  • Report Automation Basics
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.

14The 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

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

  1. Marketing Intelligence Specialist (Level 002)

    2-3 years in current role

    From executing tasks to owning well-defined analytical projects independently.

    • Advanced SQL: Using CTEs and window functions for more complex data pulls.
    • Advanced Tableau: Building more interactive dashboards, using parameters and sets.
    • Basic A/B Testing Analysis: Interpreting results and understanding statistical significance.
    • Data Storytelling: Translating numbers into clear, actionable insights for non-technical audiences.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, a big chunk of data analysis can be repetitive. Imagine cutting down those hours spent on mundane tasks, freeing you up for more interesting, deeper dives. That's exactly what AI can do for you in this role.

As a Marketing Intelligence Analyst, you're constantly pulling numbers, cleaning data, and drafting summaries. AI isn't here to replace you; it's here to be your smart assistant, automating the grunt work so you can focus on learning, problem-solving, and actually understanding the 'why' behind the data. Think of it as having a tireless intern who never complains about cleaning spreadsheets.

Automated Performance Commentary Drafts

Use a tool like GPT-4, connected to our data, to automatically generate the first draft of your weekly or monthly performance summaries. The AI can highlight key trends, spot anomalies, and even draft initial explanations for percentage changes, giving you a solid starting point to refine, rather than writing from scratch. It's like having a ghostwriter for your reports.

Smart Data Cleaning & Transformation

AI-powered tools can help you identify and fix inconsistencies in your datasets much faster. Imagine an AI suggesting how to standardise product names or merge similar customer entries, saving you hours of manual spreadsheet work. It's not perfect, but it's a huge head start on the 'data janitor' tasks.

AI-Assisted Research & Learning

Need to quickly understand a new marketing metric or a complex SQL function? Use AI tools to summarise articles, explain concepts in simple terms, or even generate example code snippets. It's like having an expert tutor on demand, helping you learn faster and more efficiently.

Initial Dashboard Layout Suggestions

While you'll follow templates, AI can sometimes suggest initial dashboard layouts or chart types based on your data and the questions you want to answer. It won't build the whole thing, but it can give you ideas for visualising complex information more effectively, especially when you're just starting out.

Common questions

Common questions

How do you become a Marketing Intelligence Analyst?

Common routes in include Graduate Programme (Marketing/Data Analytics) (0-1 year), Junior Data Analyst (Non-Marketing Specific) (1-2 years) and Marketing Coordinator / Assistant (Data-Focused) (1-2 years). Times vary with prior experience.

Where can a Marketing Intelligence Analyst progress to?

This role can lead on to Marketing Intelligence Specialist (Level 002) (2-3 years in current role), depending on the skills you build.

What level is a Marketing Intelligence Analyst in the UK?

This role aligns to RQF Level 2 on the UK framework, a guide to the depth of qualification it maps to, not a hard entry bar.

What new skills matter most for a Marketing Intelligence Analyst?

Increasingly, Basic Prompt Engineering for Marketing Data. These are the areas where the higher-paid, future-proof work is heading.

The honest bit

You’ve started things before

Most of them were built for a room full of people who aren’t you. A cohort moves on whether or not your week allowed it, and by the third week the thing you’re behind on becomes the reason you stop opening it.

There’s no cohort here, and no timetable to fall behind. Before anything starts, Zavmo asks when you’re sharpest and how long you can realistically sit down for, then builds the sessions around those answers. A bad fortnight changes your pace. It doesn’t put you behind.

And you only pay once you start learning. Searching and planning are free, and you can cancel any time — so the cost of finding out is an afternoon, not a year.

What it costs

Less than one coaching session. Every month.

A single career-coaching hour costs more than a month of this, and it ends when the hour does. Zavmo doesn't. It's £70 a month, about £2.30 a day, for a companion that knows a Marketing Intelligence Analyst, works on the job you actually do, and keeps going at your pace rather than a timetable's.

  • Searching and planning stay free. You only pay when you start learning.
  • Your credits are yours. Regulated, and they don't vanish when a subscription ends.
  • Cancel any time and billing stops. No notice period, no minimum term.

Your path, personalised

You have the map. Walking it is the part we do together.

This route runs to 10 national skill standards. That is a real journey.

Zavmo shapes a learning experience as unique as you are. It fits how you learn, your pace and the work you already do. Every step stays benchmarked to recognised national standards. That’s the plan for becoming a Marketing Intelligence Analyst: personal to you, and it still counts. The first steps are free.

Independent research finds well-designed intelligent tutoring performs nearly as well as one-to-one human tutoring: VanLehn (2011), Educational Psychologist.

A private tutor in the UK averages £35–40 an hour . Zavmo is £70/month.

A real plan on learn.zavmo.ai: Ofqual-regulated units, credits, and a three-month run at your own pace.
Start free No commitment. See your first steps free.

15Where to go from here

Other roles at Level 2

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

Other roles in Marketing

Stay in the field you know and move sideways rather than up.

If you leave this industry

The skills you'll gain here in data analysis, visualisation, and understanding business metrics are highly transferable. You could move into broader Business Intelligence, Sales Operations, or even Finance analytics roles in other industries, should your interests shift. Data is everywhere, and good data people are always in demand.

Not sure this is the right direction?

Work out what you actually want from work first, then come back and see which roles fit it. Takes about ten minutes.

This role profile is © 2026Growth 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. Build my plan, free Here's the first ten minutes: a 2-minute confidence check → your personalised roadmap → meet the tutors matched to you. No card, cancel any time. 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.