5 tips to evaluate content marketing skills

To check content marketing skills, give the candidate a short piece of real work and score it against the competencies the job actually needs: writing and editing judgment, SEO application, distribution, analytics, and the ability to plan a set of related pages. A portfolio tells you what a team shipped. A scored work sample tells you what this person can do.

That distinction matters more in 2026 than it did two years ago. In the Content Marketing Institute's 2026 B2B content and marketing trends research (1,015 B2B marketers), 95% say their organization uses AI-powered applications and 89% use content creation tools to generate or optimize copy. Then the numbers split: 87% say productivity improved, 58% say content quality improved, and only 39% say content performance improved. Output got cheap. Judgment did not. So the skill worth testing has moved from producing copy to deciding whether copy is any good.

TL;DR

• Score a work sample, not a resume. Revised meta-analytic estimates put work sample tests at 0.40 operational validity against 0.31 for a general cognitive test.
• Test five things: writing and editing judgment, SEO application, planning related content, distribution, and reading analytics.
• Build the sample from a real brief your team has already run, cap it at 60 to 90 minutes, and tell candidates how it will be scored.
• Weight the competencies before anyone submits. Deciding weights afterwards is how a favorite candidate wins on the criteria that happen to suit them.
• Expect AI in submissions and design for it. Ask for the edit, the rejected version and the reasoning, because that is the part a model cannot hand over.

How do you check content marketing skills?

Set one brief, ask for one short deliverable, and score it against weighted competencies agreed on before submissions arrive. One 60-minute exercise and a 20-minute conversation about the choices behind it will separate candidates faster than a three-round interview loop, because you are reading work instead of reading claims about work.

The evidence on selection methods backs this up. Sackett and colleagues (2022) recalculated the validity of common hiring methods after finding that earlier meta-analyses had over-corrected for range restriction. In the revised estimates, job knowledge tests come in at 0.48, structured interviews at 0.42 and work sample tests at 0.40, while general mental ability drops to 0.31. A work sample plus a structured conversation about it is close to the strongest pair of signals available, and both are things a marketing team can run without a psychometrician on staff.

Why do resumes and portfolios fall short?

A content marketing portfolio is a team artifact. The post you are reading was probably briefed by one person, drafted by another, edited by a third and optimized by a fourth. Nothing in the byline tells you which of those four you are interviewing.

Titles are just as slippery. Across the hiring teams we work with, "content marketer" covers everything from a writer who takes briefs to a strategist who owns pipeline targets, and the pay bands reflect that spread. The U.S. Bureau of Labor Statistics puts the median wage for advertising, promotions and marketing managers at $165,780 as of May 2025, with employment projected to grow 6% from 2025 to 2035 and about 36,300 openings a year. Writers and authors sit at a $76,910 median with no projected growth and about 11,900 openings a year. Same two words on a lot of resumes, two very different jobs underneath.

There is a supply problem hiding in those numbers too. Flat demand for writing roles and growing demand for marketing management mean a large pool of candidates whose recent experience is production work, applying for jobs that are now mostly judgment work.

Which five skills should you actually test?

Start with the role, then map each competency to evidence you can collect. That mapping is the Testlify Competency-to-Evidence Matrix: define what success looks like for the role, connect every competency to a measurable source of evidence (an assessment, a work sample, a structured interview answer, a reference), and score candidates the same way against it. Do not start from a test and work backwards.

The five below are for an execution-heavy role. If you are hiring someone to own the program rather than produce it, weight content marketing strategy skills more heavily and shrink the writing exercise.

Writing proficiency and editing judgment

Stop asking for a writing sample. Ask for a rewrite. Hand over a genuinely weak 600-word draft your team has lying around and ask the candidate to cut it to 400 words without losing the argument. One rewrite tells you more than a polished sample ever will: what they cut first, whether they fix the order of claims, whether they notice the sentence that cannot be supported and flag it instead of quietly deleting it.

Score the reasoning, not the grammar. A candidate who writes in their second language and restructures the piece correctly is a better hire than one with clean commas and no argument. Scoring grammar first is also the fastest way to build adverse impact into a writing test for no predictive gain.

SEO knowledge and application

Give a target query and ask for a one-page brief. Strong candidates separate what the searcher wants from what the keyword tool reports, and they say which page on your site should own the query rather than proposing a new one for every variation.

Ask one question about Google's own rules, because most candidates have only absorbed the folklore. Google's spam policies define scaled content abuse as generating many pages "for the primary purpose of manipulating search rankings and not helping users", and name "using generative AI tools or other similar tools to generate many pages without adding value for users" as an example. The policy turns on value, not on whether a human typed it. A candidate who understands that will not pitch you 200 programmatic pages in week one.

How to evaluate related content and topic clusters

Ask the candidate to map five supporting pages around one pillar page, and to say which query each one owns. What you are testing is whether they group by search intent or by keyword variant. Grouping by variant produces four pages competing for the same query, which splits clicks and buries all four.

The tell is in how they handle overlap. A candidate who says "these two should be one page, and the older URL redirects to it" has run a real content program. One who adds a page per keyword has only read about one.

Social media management and distribution

Content that nobody sees is a hobby. Ask for a distribution plan for the piece they just wrote: which channels, how the piece gets reshaped for each, and what happens in the two weeks after publication. Vague answers about "building community" mean they have only ever handed finished work to somebody else.

If the role also touches paid and lifecycle channels, the same approach carries over to evaluating digital marketing skills, and a digital marketing test is a faster way to check channel breadth than adding another exercise.

Analytics and data interpretation

Hand over a small, slightly messy extract of real numbers and ask one question: what would you change? Good candidates read the metric against the goal, name the confound (a seasonal dip, a tracking change, a single post carrying the whole month) and commit to one change rather than five. Weak candidates describe the chart back to you.

Portfolio and past performance evaluation

Keep the portfolio, but use it as an interview prompt instead of a score. Pick two pieces and ask three questions: what was your specific contribution, what did it achieve, and what would you change now? The third question does the most work. Anyone who has owned content for a year has a piece they would rewrite, and they usually explain exactly why within thirty seconds.

How do you design a content marketing work sample?

Use a brief your team has already run, so you can compare the submission against what actually happened.

1. Pick one real deliverable: a rewrite, a brief, a cluster plan or an analytics read. One, not four.
2. Cap it at 60 to 90 minutes and say so in writing. Anything longer is unpaid work, and strong candidates with options will decline.
3. Publish the scoring criteria with the task. Candidates who know what you value produce work you can compare.
4. Collect it in a format you can score consistently. Testlify's practical questions accept a file upload, a URL or both, and the Office-app question types run the exercise inside Google Docs, Google Slides, Microsoft Word, PowerPoint or Excel, so you see the document rather than a pasted block of text.
5. Follow it with a 20-minute structured conversation about the choices in the submission, using the same questions for every candidate.

Pro tip: ask candidates to justify one choice in writing alongside the deliverable. Testlify's comment-justification setting ("Ask candidates to provide a comment justifying their option selection") can be made mandatory, and the justification is usually more diagnostic than the answer it defends.

How do you score what you get back?

Agree on the weights before the first submission lands. With weighted scoring you can set a weight from x0 to x5 per test, so a rewrite exercise can carry five times the influence of a tool-knowledge quiz. Here is a starting matrix for a mid-level content marketing hire, worth adjusting to your own role.

Two scoring habits are worth stealing. Score each competency independently before looking at the total, because one strong rewrite otherwise colors every other judgment. And use percentile benchmarking rather than a raw score once you have a handful of candidates, since "72 out of 100" means nothing until you know what the other applicants did with the same brief.

If you run the exercises through an assessment platform, item-level reporting tells you whether the questions are working. A difficulty index and a discrimination index show which questions separate strong candidates from weak ones, and a quality-risk flag marks questions with very low accuracy or high skip rates. A question every candidate gets right is not measuring anything.

What about AI-written work samples?

Assume AI is in the submission. Given the adoption figures above, a ban tests honesty rather than skill, and it is unenforceable anyway. Design around it instead.

Three moves work. Ask for the version they rejected and why. Ask them to fact-check a draft you supply that contains two plausible but wrong claims. And run the structured conversation, where the follow-up question "why did you cut that paragraph?" gets an immediate answer from someone who made the choice and a vague one from someone who did not.

Tooling helps at the margin. Testlify's AI checker classifies an answer as human, AI-generated or mixed, and AI scoring reads open-ended submissions including documents, spreadsheets, presentations, images and content at a URL. Treat the flag as a prompt for a conversation, never a verdict. The product says so itself: AI scores and insights are for guidance only, and human judgment makes the final decision. Reviewers can also keep AI scores out of the final average entirely and route any question to a named human for manual review.

Where teams get this wrong

The failure is rarely the test. It is everything around it.

• Unpaid spec work. A four-hour "sample campaign" is a free deliverable, and word travels. Either keep it under 90 minutes or pay for it.
• Testing tools instead of judgment. Which keyword research tool a candidate has used matters far less than whether they can tell a query worth chasing from one that is already answered on the results page.
• Scoring after the fact. Weights set after submissions arrive bend to whoever the hiring manager already liked.
• Auto-rejecting on a flag. An integrity flag is evidence, not a conclusion. Testlify's own yellow flag says a quick manual review is recommended, which is the right posture.
• Small question banks. If you randomize questions from a small pool, candidates see overlapping sets. The product warns about this directly, and the fix is a bigger bank, not more randomization.
• One reviewer. Writing quality is the most subjective thing on the list. Two reviewers scoring independently, then reconciling, catches taste masquerading as standards.

Hire content marketers on evidence, not adjectives

Pick one role you are hiring for this quarter, write the competency matrix for it, and replace the first interview round with a 60-minute scored exercise. Testlify's Content Marketer assessment covers content strategy, creation, distribution and measurement if you would rather start from a built library than from scratch, and results sync into the ATS your team already runs. Teams hiring for marketing and advertising roles can pair it with a custom work sample in the same assessment. Book a 30-minute walkthrough to see how the scoring and reviewer workflow fit your process.

Key Takeaways

• A work sample carries about the same predictive weight as a structured interview. At 0.40 revised operational validity it sits just under structured interviews (0.42) and well above a general cognitive test (0.31), so the cheapest upgrade to a content hiring loop is turning one unstructured conversation into one scored exercise.
• AI changed what is scarce. 87% of B2B marketers report better productivity from AI-assisted content while only 39% report better performance, so a hiring process that measures output speed is measuring the part that is no longer hard to buy.
• Weights decide the hire, so set them first. Assigning a weight from x0 to x5 per competency before submissions arrive is what stops the scoring rubric from being rewritten around a favorite candidate.
• Portfolios are team artifacts. Use them as interview prompts and ask what the candidate would change now, because that single question separates people who owned the outcome from people who were handed a brief.
• Job titles hide two different jobs. A $165,780 median for marketing managers against $76,910 for writers tells you "content marketer" spans production and strategy, so define which one you are buying before you write the test.
• Design for AI rather than banning it. Ask for the rejected version, the fact-check and the reasoning, and keep any AI flag as a prompt for a human conversation instead of an automatic rejection.

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