UK

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

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

Also advertised as Commercial Analyst · Revenue Analyst · Business Analyst (Sales)

Built on 43,079 real UK job descriptions we analysed · grounded in what real qualifications cover

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

NOCN Level 4 certificate for Data Analysts NOCN · Level 4 · covers 3 of 8 standards
BCS Level 4 Diploma - Digital Modular Programme for Data Analysts BCS, The Chartered Institute for IT · Level 4 · covers 2 of 8 standards
Highfield Level 3 Diploma for Team Leaders and Supervisors (RQF) Highfield Qualifications · Level 3 · covers 2 of 8 standards
Pearson BTEC Level 4 Higher National Certificate in Computing for England Pearson Education Ltd · Level 4 · covers 2 of 8 standards
Focus Awards Level 4 NVQ Diploma in Customer Service (RQF) Focus Awards Limited · Level 4 · covers 1 of 8 standards
Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 3 of 8 standards

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

The units you would start with

Data Analytics Primer NOCN Level 4 certificate for Data Analysts
Data Analysis BCS Level 4 Diploma - Digital Modular Programme for Data Analysts
Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England
Obtaining and analysing sales-related information Focus Awards Level 4 NVQ Diploma in Customer Service (RQF)

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
Your Plan Illustration

Built for Sales Analyst

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

  1. Data Analytics Primer NOCN · covers 3 of 8 standards Level 4
  2. Data Analysis BCS, The Chartered Institute for IT · covers 2 of 8 standards Level 4
  3. Data Analytics Pearson Education Ltd · covers 3 of 8 standards Level 5
  4. Obtaining and analysing sales-related information Focus Awards Limited · covers 1 of 8 standards Level 4
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 Sales Analyst?

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

The new skills this role is being asked for

  • Prompt Engineering & LLM Integration (for Sales Narratives)
  • Advanced Data Visualisation & Storytelling
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 Sales Analyst plan as you set up, starting with the free AI Fluency module. No card.

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

Ready to pay? Subscribe for £70 a month

Keep this read. One email with what AI is changing in this job, the new skills it asks for and where to start free. Nothing else follows unless you confirm your address.

3What this role really is

A Sales Analyst pulls together sales data and turns it into reports sales teams can act on. The work involves pulling numbers from CRM systems and pipeline stages, and checking daily, weekly and monthly sales performance. It means working with data every day, keeping figures accurate and easy to understand.

4What you'd actually use

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

Salesforce (or Dynamics 365) Intermediate

Building standard reports and dashboards, navigating objects to find specific data points, understanding field dependencies for data extraction.

Microsoft Excel Advanced

Proficient with VLOOKUP/INDEX-MATCH, PivotTables, complex nested formulas. You'll build clean, functional trackers and perform detailed data manipulation.

Tableau (or Power BI) Basic

Connecting to clean data sources (like Excel or CSVs), building simple visualisations, and assembling them into pre-defined dashboard layouts. You'll be maintaining existing dashboards.

SQL (PostgreSQL / T-SQL) Basic

Writing `SELECT` statements with `WHERE`, `GROUP BY`, and simple `JOIN`s to pull specific data for ad-hoc requests and to validate CRM data.

Gong (or SalesLoft) User

Pulling reports on rep activity, listening to calls to understand deal context, and extracting basic call metrics for analysis.

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
Data Extraction & Reporting Methodology Follows established procedures and templates; seeks guidance for any deviation. Independently chooses the best method for routine data pulls and report generation, adapting existing templates. Consults manager on novel or complex data requirements. Designs new reporting methodologies and data extraction processes. Makes technical decisions on tool usage and data transformation for complex projects.
Prioritisation of Ad-hoc Requests Escalates all requests to supervisor for prioritisation. Prioritises routine ad-hoc requests based on urgency and impact, within agreed SLAs. Escalates conflicting 'urgent' requests to manager. Manages and prioritises a queue of complex ad-hoc requests, negotiating timelines with stakeholders and delegating to junior analysts.
Identification & Resolution of Data Discrepancies Identifies obvious discrepancies and escalates to supervisor. Independently investigates and identifies the root cause of common data discrepancies. Proposes solutions to manager for approval. Proactively identifies systemic data quality issues, designs and implements processes to prevent future discrepancies, and works with IT/Sales Ops on solutions.

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 percentage of sales reports and dashboards you produce that contain zero data errors or calculation mistakes.
Target · Maintain <1% error rate across all published reports

You publish 20 reports in a month. If one has a minor calculation error, that's a 5% error rate – we're aiming for much lower. Ideally, zero errors.

Reporting Cadence Adherence
The proportion of scheduled weekly and monthly reports that are delivered on time, as per the agreed-upon schedule.
Target · 98% of all scheduled reports delivered on time

If the weekly pipeline report is due by 9 am every Monday, hitting that deadline consistently counts. Missing it even once in a quarter means you're not at 100%.

Ad-hoc Request Fulfilment Rate
The percentage of urgent, one-off data requests from sales teams that are completed within the agreed 48-hour service level agreement (SLA).
Target · 95% of ad-hoc requests fulfilled within 48 hours

A Sales Director needs a list of all accounts without a deal in the last 6 months by Friday. Delivering that by Thursday afternoon would be a win.

Dashboard Usage & Adoption
The number of unique users regularly accessing the dashboards you own, indicating their perceived value and usefulness to the sales team.
Target · Increase average weekly unique users by 10% quarter-on-quarter for owned dashboards

If your 'Team Attainment' dashboard usually gets 50 unique views a week, we'd want to see that creep up to 55-60 over the next three months, showing people find it genuinely helpful.

Clarity of Insights
How well you translate complex data into clear, understandable narratives and actionable recommendations for non-technical sales professionals.
  • Sales managers consistently tell your manager that your reports are easy to understand and directly help them make decisions. You're able to simplify complex charts into a few key takeaways in presentations. People don't ask for clarification on your reports
  • they just act on them.
Proactive Issue Identification
Your ability to spot anomalies, discrepancies, or potential problems in the sales data before they become bigger issues or are noticed by others.
  • You flag a sudden drop in lead conversion for a specific region before the Marketing team does. You identify inconsistent data entry patterns in the CRM and bring them to Sales Ops' attention. You catch a potential reporting error from another team because you know the data so well.
Stakeholder Trust & Reliability
The level of confidence sales leaders and managers have in your data and analysis, and their willingness to rely on your reports for critical decisions.
  • Sales leaders routinely reference your reports in their team meetings. People come to you directly for data validation or a 'second opinion' on numbers. Your manager doesn't feel the need to double-check your work before it goes out to senior leaders.

7Would you like it

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

What people enjoy
Solving Puzzles with Data

You get a real kick out of taking a messy dataset, cleaning it up, and then finding the 'aha!' moment that explains a sales trend or solves a business question. It's like being a detective, but with spreadsheets instead of fingerprints.

Spending an afternoon digging into why a specific product's sales suddenly dropped, only to discover a CRM data entry error that, once corrected, shows the product is actually doing fine.

Direct Impact on Business Decisions

You love seeing your reports and analysis being used by sales managers to make actual decisions – whether it's re-prioritising leads, adjusting coaching strategies, or understanding why a territory is underperforming.

A sales manager tells you that your weekly pipeline health report helped them identify a team that was struggling with early-stage conversions, allowing them to intervene and provide coaching.

Continuous Learning & Improvement

You're always looking for better ways to do things, whether it's learning a new Excel trick, optimising a SQL query, or finding a more efficient way to present data. You enjoy mastering tools and techniques.

Discovering a new feature in Tableau that allows you to build a more interactive and insightful dashboard, then sharing that knowledge with your team.

What frustrates people
  • The CRM is a Lie: Your analysis is only as good as the data in the CRM, and let's be frank, reps often treat updating it as their last priority. Expect to spend a decent chunk of your time (maybe 20-30%) cleaning data or chasing reps for updates. It's not glamorous, but it's essential.
  • Forecast Whiplash: You'll put together a data-driven forecast, but then leadership might ask you to 'tweak' the model until it magically matches the optimistic number they want to present to the board. You can end up owning a number you don't fully believe in.
  • The 'Urgent' Fire Drill: The VP of Sales needs a new data cut for a meeting that starts in 30 minutes, completely derailing your planned work on a bigger project. This happens weekly, sometimes daily. You'll need to be good at reprioritising on the fly.
  • Blame Catcher, Credit Deflector: When the team misses its number, your forecast accuracy is often the first thing questioned. When the team crushes it, the reps are celebrated, and your accurate forecast is, well, forgotten. It's just how it goes sometimes.
  • Shifting Goalposts: The rules can change mid-game. A new commission plan might be rolled out mid-quarter, or territories realigned, forcing you to recalculate everything and manage the fallout from confused reps. It's rarely a static environment.
  • Explaining Nuance to the Impatient: Trying to explain why a simple-sounding request ('Just show me our win rate by industry!') is actually incredibly complex due to data quality issues, to a sales leader who just wants the number now. Patience is key here.
What this role does not give you
  • A perfectly predictable day-to-day schedule – urgent requests will pop up.
  • Complete ownership of strategic decisions – you'll provide the data, others make the call.
  • A role where you don't have to chase people for data – you absolutely will.
  • A quiet, solitary environment – you'll be interacting with sales teams constantly.

8Who you work with

Your work directly impacts the daily decision-making of our sales force. Accurate and timely reporting means sales managers can coach their teams effectively, identify underperforming segments, and allocate resources where they'll make the biggest difference. Get it wrong, and we could be chasing the wrong leads or misinterpreting market signals, which ultimately affects our bottom line. You're essentially the eyes and ears of the sales leadership, giving them the real picture, not just the 'happy ears' version.

Inside the business
  • Sales Managers (Regional & Team Leads)
  • Sales Operations Team
  • Marketing Team (for lead conversion analysis)
  • Finance Team (for revenue reconciliation)

9What you need before you start

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

  • Proven experience (2-5 years) in a data-focused role, ideally within a commercial, sales, or finance environment, where you were responsible for reporting and analysis.
  • Demonstrable experience building reports and dashboards using CRM data (e.g., Salesforce) and visualisation tools (e.g., Tableau, Power BI).
  • A solid track record of cleaning, validating, and transforming messy datasets into clear, usable information.
  • The ability to clearly communicate complex data insights to non-technical audiences, both verbally and in writing.

10What 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 warehouse grows, you'll need to pull more complex, joined datasets for your analysis. Moving beyond simple SELECTs to building more efficient and robust queries will be key for speed and accuracy.

Common Table Expressions (CTEs) · Window Functions · Query Optimisation · Database Schema Understanding

  • This week: Identify one of your most frequently used SQL queries. Can you rewrite it using a CTE?
  • This month: Practice using window functions to calculate a running total of sales or rank reps by performance.
  • Month 2: Take an online course specifically on advanced SQL concepts and query optimisation.
  • Month 3: Work with a senior analyst or data engineer to review and optimise some of your more complex queries.

Quick win: Whenever you write a new SQL query, try to break it down into logical steps using comments. This makes it easier to read and debug, and helps you think about optimisation.

Anaplan (or similar EPM tool) Familiarity

While you might not be building models from scratch yet, understanding how our enterprise planning tools work will be crucial for providing accurate data inputs and interpreting planning outputs for sales.

Model Navigation · Data Input & Update · Basic Logic & Data Flows

  • This week: Ask your manager for a demo of our Anaplan models (if we use it) and how they relate to sales planning.
  • This month: Shadow a Sales Operations team member who uses Anaplan to understand their daily tasks and challenges.
  • Month 2: Request access to view (read-only) some of the key sales planning models in Anaplan and familiarise yourself with the interface.
  • Month 3: Take an introductory online course on Anaplan (or our equivalent EPM tool) to learn the basics.

Quick win: Simply asking 'How does that number get calculated in Anaplan?' whenever you see a figure from the tool will start building your knowledge.

11Staying current once you are in

What people here do to keep up
  • Regularly participate in online forums or communities for Salesforce, Excel, and Tableau/Power BI users to learn new tips and tricks.
  • Attend webinars or virtual conferences on sales analytics best practices and emerging trends.
  • Take advantage of internal training programmes on our CRM or BI tools to deepen your expertise.
  • Read industry blogs and articles on sales operations and analytics to stay informed about new methodologies.

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.

Prompt Engineering & LLM Integration (for Sales Narratives)

Competitors are already using AI like ChatGPT or Claude to draft report summaries, email follow-ups, and even initial QBR narratives in minutes, not hours. Analysts who master this will significantly outproduce their peers.

  • Effective Prompt Construction
  • Context Windows & Token Limits
  • Output Validation & Hallucination Detection
  • Retrieval-Augmented Generation (RAG)

Advanced Data Visualisation & Storytelling

As data becomes more complex, the ability to distil insights into compelling visual stories is becoming non-negotiable. Simply showing charts isn't enough; you need to guide the audience to the 'so what?'

  • Dashboard Design Principles
  • Pre-attentive Attributes
  • Narrative Flow in Dashboards
  • Interactive Storytelling

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Sales Forecasting & Modelling (Basic)
  • Territory Planning & Quota Allocation (Data Support)
  • Pipeline Velocity Analysis (Basic Interpretation)
  • Sales Performance Management (Report Building)

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 Analyst / Associate Analyst

    1-2 years

    Skills to master

    • Mastering data extraction, basic reporting, data cleaning, and understanding core business metrics. Getting really good at Excel and learning the basics of our CRM.

    You're ready to move on when

    • Consistently delivers accurate basic reports on time.
    • Can independently troubleshoot simple data issues.
    • Demonstrates a solid understanding of our sales data structure.
    • Proactively seeks to learn new analytical techniques.
  2. 2

    Sales Operations Coordinator

    2-3 years

    Skills to master

    • Deep understanding of sales processes, CRM administration, basic reporting, and supporting sales teams directly. Often involves a lot of data entry and process adherence.

    You're ready to move on when

    • Has a strong grasp of how our sales team operates day-to-day.
    • Can identify areas where data quality impacts sales efficiency.
    • Is comfortable working with CRM systems and basic reporting tools.
    • Shows initiative in improving sales processes through data.
  3. 3

    Graduate Programme (Analytics/Business)

    2-3 years

    Skills to master

    • Structured learning in various business functions, including analytics. Developing foundational analytical skills, business acumen, and project management basics.

    You're ready to move on when

    • Successfully completed rotations with strong analytical components.
    • Received positive feedback on data analysis projects.
    • Demonstrates strong problem-solving skills and a desire to specialise in data.
    • Has a good understanding of how different business functions interact.

15Where this role leads

The long view: This work can lead to managing a team of analysts, running sales operations, or leading business intelligence across a whole organisation.

16Pay and demand

Pay & demand

Typical pay £38,572 a year Source: ONS Annual Survey of Hours and Earnings, 2025 (provisional), under the Open Government Licence v3.0

The figure is the median for full-time employees in the ONS occupation this job title codes to (Data analysts), from the April 2025 survey, about six months old when published, as ASHE always is. It is that occupation's middle, not this role's. Half earn more.

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 Sales Analyst is actually changing.

Where it leads

Roles this leads to

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 Data Analytics Primer, worked against Sales Analyst.

Data Analytics Primer Level 4

Applied to your work in Sales Analyst

This unit aims to equip learners with a foundational understanding of data analytics, including its applications and the stages of the data analysis lifecycle. Learners will explore various data types and structures, understand the role of data within an organisation, and recognise the importance of GDPR and compliance requirements in data handling.

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.

See Your Progress Grow Illustration
Sales Analyst
  • Sales Forecasting & Modelling (Basic)
  • Territory Planning & Quota Allocation (Data Support)
  • Pipeline Velocity Analysis (Basic Interpretation)
  • Sales Performance Management (Report Building)
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.

17The 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

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

  1. Senior Sales Analyst (L3)

    3-5 years in current role

    Leading projects, mentoring juniors, owning more complex analytical workstreams.

    • Advanced Sales Forecasting & Modelling (building predictive models, scenario planning)
    • Territory Design & Optimisation (using data to create balanced territories)
    • Commission Plan Modelling (analysing impact of different incentive structures)
    • Advanced Tableau/Power BI (LODs, complex calculations, performance optimisation)
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be honest, a big chunk of a Sales Analyst's job can feel like grunt work – cleaning data, pulling standard reports, or trying to summarise hours of sales calls. But what if you could offload a lot of that to AI? Imagine spending less time on the tedious bits and more time on the really interesting stuff: finding those 'aha!' insights that actually help us sell more. That's exactly what AI is starting to do for sales analytics.

We're not talking about robots taking over your job; we're talking about smart tools that become your personal assistant. These aren't just for the future; they're here now, and they're already making a huge difference to how our analysts work. We're building an internal AI Productivity Hub, and as a Sales Analyst, you'll be at the forefront of using these tools to supercharge your daily tasks. It's about working smarter, not harder, and frankly, making your job a lot more interesting.

CRM Data Janitor

Use AI tools to automatically scan Salesforce for duplicate records, incomplete fields, and inconsistent data (e.g., 'United States' vs. 'USA'). The AI can flag these entries for reps to correct or even auto-correct them based on a high confidence score. Imagine not spending hours manually scrubbing data!

Predictive Forecaster

Leverage AI models that analyse historical deal data, rep activity metrics, and deal characteristics to generate a baseline, unbiased forecast. You can then use this AI-generated forecast as a statistical sanity check against the reps' manual forecasts, helping you spot 'happy ears' earlier.

Call Summary Synthesizer

Instead of listening to hours of Gong calls to understand deal context, use AI to generate concise summaries of sales conversations. It can automatically identify key competitor mentions, budget objections, and next steps, accelerating your qualitative deal inspection and saving you loads of time.

QBR Narrative Drafter

Feed key performance data (like attainment, pipeline generation, and win rates) into an AI model to generate the first draft of the narrative for your Quarterly Business Review (QBR) deck. It can highlight key trends, wins, and areas for concern, giving you a massive head start on your presentations.

Common questions

Common questions

How do you become a Sales Analyst?

Common routes in include Junior Analyst / Associate Analyst (1-2 years), Sales Operations Coordinator (2-3 years) and Graduate Programme (Analytics/Business) (2-3 years). Times vary with prior experience.

Where can a Sales Analyst progress to?

This role can lead on to Senior Sales Analyst (3-5 years in current role), depending on the skills you build.

What new skills matter most for a Sales Analyst?

Increasingly, Prompt Engineering & LLM Integration (for Sales Narratives) and Advanced Data Visualisation & Storytelling. 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

18Where 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.
This job at other levels
More jobs in sales

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

The skills built as a Sales Analyst apply across industries. Any business with a sales team needs someone who can make sense of its numbers. This can lead to analytics roles in marketing, finance or product, since the core analytical skills carry across.

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 free AI Fluency module 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.