Sales Data Analyst

A sales data analyst turns a company's sales figures into things the sales and commercial teams can act on: which products are selling, which customers are slipping away, whether the team is on track for target, and why. They spend most of their time pulling data out of company systems, checking it makes sense, building reports and dashboards, and explaining the findings to sales managers and directors who usually aren't technical.

Approximate graduate salary

Typically around GBP 25,000-33,000 to start, though this varies widely - London and technology or financial-services employers sit at or above the top of that range, while smaller firms and roles outside major cities can start below it. Some roles include a small bonus linked to company or team performance.

What you'd actually do

Pulling sales data out of a CRM (customer relationship management system - the software that logs every customer, deal and contact) or a data warehouse, usually by writing SQL queries
Building and maintaining dashboards and weekly reports in tools like Power BI, Tableau or Looker so managers can see performance without asking for it
Chasing down why the numbers look wrong - duplicate customer records, deals logged in the wrong month, a rep who hasn't updated their pipeline - which takes up more time than most people expect
Sitting in on sales meetings or pipeline reviews to present figures, then fielding questions like 'why is the North region down?' and going away to find out
Doing ad-hoc analysis on request: pricing and discount patterns, customer churn, sales territory sizing, the effect of a promotion, forecast accuracy versus what actually landed
Helping produce the numbers behind sales targets, quotas and commission calculations, often working with finance
Cleaning and restructuring data in Excel or SQL so that a one-off request can be repeated next month without starting from scratch

How graduates get in

Direct entry into a junior or graduate analyst post advertised as 'sales analyst', 'commercial analyst', 'business analyst' or 'reporting analyst' - this is the most common route and many employers hire ad hoc rather than through a scheme
Structured graduate schemes in commercial, data or finance streams, common at large retailers, consumer goods companies, telecoms, media and software firms; these often rotate you through several teams before you settle
Moving internally from a sales support, sales operations or account coordinator role once you've shown you can handle the reporting side - a very common path, and a realistic one if you can't land an analyst job straight away
Industrial placement years or summer internships in commercial or data teams, which frequently convert into graduate offers
Conversion from a non-quantitative degree via a data analytics bootcamp or a master's in data science, business analytics or similar - workable, but employers will still want to see a portfolio or real project work rather than just the certificate
Starting in a generalist analyst role at a data or market research agency and moving client-side later; less direct but it builds the toolkit fast

What employers ask for

A degree in almost any subject can work, but numerate ones - economics, maths, statistics, business, geography, engineering, computer science, psychology - are the usual background because employers want evidence you're comfortable with data. A humanities graduate with demonstrable Excel and SQL work does get hired.
Most employers ask for a 2:1, though plenty of smaller companies and internal-promotion routes are flexible about class and won't screen on A-levels at all. Larger graduate schemes are more likely to have fixed grade filters.
Strong Excel is close to non-negotiable: pivot tables, lookup functions, and ideally Power Query. Many employers test this at interview stage.
SQL is asked for in the majority of adverts and is the single most useful thing to learn before applying. Some junior roles will teach it, others expect you to arrive with it.
Experience of a business intelligence tool (Power BI, Tableau, Looker, Qlik) is often listed as desirable rather than essential at graduate level - a self-taught dashboard project counts.
Python or R appear on some job specs, particularly at tech and e-commerce employers, but a lot of sales analyst work is done entirely in SQL, Excel and a BI tool. No formal professional qualification is required for the role.

Skills that matter

SQL

It's how you get the data out of the company's systems in the first place, and without it you're dependent on someone else to answer every question.

Excel modelling and data manipulation

Sales teams live in spreadsheets, so a large share of your outputs and requests will arrive and leave as Excel files.

Data cleaning and scepticism about the numbers

Sales data is entered by busy humans and is routinely incomplete or miscoded, so spotting that a figure is implausible before it reaches a director is a big part of the job.

Explaining findings to non-technical people

A sales director wants three sentences and a recommendation, not your methodology, and analysts who can't compress their work get ignored.

Commercial understanding of how the business makes money

Knowing the difference between revenue, margin, pipeline and booked orders - and which one the question is really about - is what separates useful analysis from a correct but pointless chart.

Dashboard design

Most of your work gets consumed as a self-service report, so laying it out clearly determines whether anyone actually uses it.

Handling competing requests

Several managers will want 'a quick number' at once, and judging what's genuinely urgent versus what can wait is a daily decision.

Where it leads

Junior or graduate analyst: you're mostly running existing reports, fixing data issues and answering defined questions. Typically a year or two, though this varies widely by employer size.
Sales or commercial analyst: you own areas of reporting outright, get asked open-ended questions, and start being consulted before decisions rather than after them.
Senior analyst or sales operations manager: you design how the sales team is measured - territories, targets, forecasting process, CRM data standards - and may manage one or two junior analysts. Timeframes here vary enormously; some people reach this in three or four years, others take longer or move sideways first.
From there the paths fork. Common destinations are commercial or revenue operations management, finance business partnering, data analytics or data science (if you've kept building technical skills), category or pricing management, or moving into sales or account management itself, where analysts often do well because they already understand the numbers.
Longer term, the commercial route can lead to head of sales operations, commercial director or similar; the technical route leads to analytics manager or data lead. These are genuinely different careers and it's worth knowing which one you're building towards by about the senior analyst stage.

What people get wrong

“It's a sales job, so you'll be selling or need to be an extrovert.”

You don't sell anything and you don't carry a target. You support the people who do. That said, you'll be presenting to sales teams regularly, and they are typically a direct, impatient audience, so it isn't a role where you can hide behind a screen either.

“The work is mostly building sophisticated models and predictions.”

A large share of the job is unglamorous data plumbing - reconciling systems that disagree, fixing records a rep entered wrongly, rebuilding a report that broke. Getting trustworthy numbers is usually the hard part; the analysis on top is often fairly simple.

“You need a data science master's or strong programming skills to get in.”

Many sales analyst roles never touch Python. Excellent Excel plus solid SQL plus the ability to explain things clearly will get you hired at a lot of employers, and those skills are learnable on your own in months.

“Your job is to produce the analysis and the business will act on it.”

Analysts routinely produce work that nobody uses. Getting a finding acted on means knowing who makes the decision, framing it in terms they care about, and following up - influence matters as much as accuracy.

Where this varies

The job title covers quite different jobs depending on where you work. At a large retailer or consumer goods company you may be close to a category or trading analyst, working with EPOS and market share data. At a software or subscription business the role often sits inside 'revenue operations' and is heavily focused on CRM pipeline hygiene, forecasting and renewals. At a small company you may be the only analyst, doing everything from building the dashboard to maintaining the database, with far less supervision but more freedom. In heavily regulated sectors the work is more reporting-driven and process-bound. Team structure varies too: some analysts sit inside the sales function reporting to a sales director, others sit in a central data or finance team and serve sales as an internal client - which changes how much say you have and how technical the environment is.

General guidance about the role across the UK market, not about any specific employer. Entry routes and requirements vary — always check the individual job advert.