Your first marketing job: how to break in with no experience

By Miguel Maio · Published 17 October 2026

The rejection machine: how your application gets filtered

1. 1Parsing: the ATS breaks your file into fields
2. 2Keyword search: the recruiter filters the database
3. 3Knockout questions: automatic elimination
4. 4Human scan: 7.4 seconds (Ladders, 2018)
5. 5Proof of work: what makes it through the filter

Proof of work is what survives the funnel.

"I need experience for the job, but I need the job to get experience." Everyone breaking into digital marketing hits this wall.

The wrong reading is to treat it as a merit problem, an "I'm not good enough". It isn't. It's a filtering and risk problem. An employer hiring a junior is buying risk, and the only thing that lowers it is verifiable proof of work. The rest, motivation, "passion for marketing", one more certificate, doesn't move the needle.

I've taught this since 2009 and I mentor people starting out. The pattern repeats: candidates stacking certificates and never getting past the first filter, next to the handful who break in fast because they arrive with something the others don't have, their own results, measured, verifiable in two clicks. The certificate opens the ATS door. The portfolio wins the interview.

First, calibrate with data, not with LinkedIn ads

Before you search, anchor your expectations in numbers, not in inflated aggregator averages. Use live sources to check junior bands for your market, national salary guides, Glassdoor for order of magnitude, Levels.fyi (with the caveat that its sample skews to tech and total comp), and never a loose aggregator average. Always ask for the annual gross and exactly what the package includes.

And there's a requirement nobody writes in the ad but that eliminates you at the door: English, and increasingly a second language in multilingual hubs. In most markets the digital hubs publish and work in English, so treat language as a requirement, not an extra.

Why the paradox exists, and what breaks it in 2026

An employer hiring a junior isn't buying proven competence. They're buying potential, and that's risk. You lower the risk by showing you've already done the thing, on your own, with a result. It's the difference between saying "I know SEO" and showing a site of yours that went from zero to 1,200 organic sessions a month in five months.

There's a new lever in 2026 that almost no junior uses in their favour. Article 4 of the EU AI Act requires organisations, since 2 February 2025, to ensure the AI literacy of the people dealing with these systems. Translated: a junior who already brings real AI fluency, not "I used ChatGPT" but workflows with quality control, solves a compliance problem for the employer instead of creating one. That flips the game. You stop being the one who needs training and become the one who brings it.

The machine that filters you before a human sees you

Your application is rarely read by a person first. It enters an ATS (Workday, Greenhouse, SmartRecruiters, Lever), which parses the file into fields; the recruiter searches the database by keywords; knockout questions eliminate automatically; and only then comes the first human look, a 7.4-second scan (Ladders eye-tracking study, 2018; it's an industry study and some dispute it, but the direction is right: it's a clock of rejection, not of reading).

The cost is real: 88% of employers admit their filters screen out qualified candidates who don't exactly match the ad's criteria (Harvard Business School and Accenture, "Hidden Workers", 2021; for middle-skills profiles it rises to 94%). And there's a 2026 layer: AI-driven candidate screening is classed as high-risk in the EU AI Act (Annex III), and Article 22 of the GDPR gives you the right to human review of a fully automated rejection.

The craft reading, which is where you have the edge: the ATS keyword match is SEO applied to you. If the ad asks for "Google Ads", you write "Google Ads", not "AdWords"; acronym and full form once. Single column, standard headings, a text-generated PDF, no tables, text boxes or "skill bars" that break the parsing. And a typo in a marketing CV isn't a slip. It's a sample of your work. A failed one.

The human is the last filter, not the first. Write for the machine without lying, and put the proof at the top.

The proof that beats the paradox

This is the core, and it's what separates those who get in from those who keep applying for a year. With no formal experience, your proof is what you generate on your own.

First, an asset of yours that's live, a WordPress site on a topic you know, with GA4 and Search Console installed from day one. No measurement, no proof. Optimise it for 20 to 50 specific keywords; expect 3 to 6 months to see a result. Then turn it into a documented case study: problem, strategy, keywords, traffic before and after with screenshots, what went wrong and what you learned.

This is where you put the 2026 lever to work: document an AI-assisted content pipeline as a case. Intent clustering with an LLM over your Search Console data, briefs generated with your own prompt template, an LLM draft, mandatory human editing with fact-checking, publication. Measure before and after: organic sessions, keywords in the top 10, time per article (from 4h to 1h30, say). What impresses isn't "I used AI". It's the system, with quality control and numbers. Finish with a GEO test: ask ChatGPT, Perplexity and Gemini about your topic and document when your site starts getting cited.

This isn't theory to pad the article. It's the same method I apply and teach. Keyword research, GEO and GA4 show each piece in detail.

The first contract in practice

Entry schemes and apprenticeships. Many markets have a subsidised route in, an apprenticeship, a graduate scheme or a government-backed internship, where the employer's cost drops and you get a real contract and social security. Agencies and SMEs often hire juniors almost exclusively through these. Ask, in your application, whether the company uses one, and what it converts into afterwards.

Employee versus contractor. You'll find roles offered on a self-employed or contractor basis. That status exists for genuinely autonomous work. If you have fixed hours, direct management and use the company's tools, it's a misclassification, and in most jurisdictions it's challengeable. Taking it can make sense as a first experience, but know what you're trading: no paid leave, no immediate unemployment safety net, and you pay your own contributions.

The salary band is a right, not a cheek. Across Europe, the EU Pay Transparency Directive (2023/970) gives candidates the right to know the initial pay range before the interview, and it's making advertised bands the norm. Even where it doesn't bind your market, asking for the band has stopped being bold. It's expected.

Where to aim, the move almost nobody makes

The best digital employers often don't live on the job boards. The move almost nobody makes: go through the portfolio directories of incubators and science-and-technology parks and apply directly to the incubated companies, not to the incubator. An incubated startup hires its first marketer early and, often, with no public ad.

The same goes for the big brands' digital hubs: apply directly on the career site, don't wait for the job board. Set up job alerts, in English and in your local language, for the roles you want. The method is this one; the specific names, hubs, incubators and parks are in my job-search guide.

What to do this week

You don't need one more course to start. You need proof. This week: put the site live with GA4 and Search Console, pick the 20 to 50 keywords, and start the case study, including the documented AI workflow. In parallel, a one-page CV in ATS format (the .txt test done) and a LinkedIn aligned with it in detail, because they cross-check the two.

And the rule that holds everything up: small true numbers beat big numbers that collapse at the interview's second question. Everything you put on the CV has to survive five minutes of questions.

Sources

• EU AI Act - Article 4 (AI literacy)
• EU AI Act - Annex III (high-risk, employment)
• Directive (EU) 2023/970 - Pay Transparency
• Harvard Business School / Accenture - Hidden Workers (via HR Dive)
• The Ladders - Eye-tracking study (via HR Dive)

Frequently asked questions