Editor Interview Questions

I start by being very specific about what the voice is not, because that is often clearer than a positive description. For one publication I managed, the brand voice was direct and slightly irreverent but never dismissive: smart readers who did not need things oversimplified. I articulated this in a two-page voice guide with annotated examples of copy that was on-voice and off-voice, and I used it in the onboarding of every new writer. To protect the voice I read a random sample of published content each week, not just the flagged pieces, so I could see whether standards were drifting. When I commissioned freelancers I included voice notes in every brief rather than sending them to a generic style guide, because generic guides are rarely specific enough to be useful. I also ran quarterly sessions where the team read and discussed pieces that exemplified the voice well, so the standard was shared and debated rather than handed down.

My commissioning process runs on three parallel tracks. The first is reactive: what are readers asking for, what are they sharing, and what search queries are bringing people to us that we are not yet answering well? I use analytics and search data to answer this. The second is proactive: what should our audience know about before they know they need to know it, and who is the right writer for that piece? The third is strategic: what gaps in our archive or coverage area do we need to fill over the next quarter, and how do we plan against that? For writer selection I maintain a pool of regulars I trust for speed and reliability, but I also actively seek out new voices, particularly for topics where the established pool is homogeneous. A brief from me always includes the angle, the audience assumption, the word count, the deadline, and a note on tone. I give detailed feedback on every first draft because that investment in development reduces problems on future commissions.

I start by diagnosing the specific weakness rather than giving general feedback. There is a big difference between a writer whose structure is strong but whose prose is flat, and one whose prose is vivid but who buries the lead. Generic feedback like "needs improvement" is useless. My approach is to sit with the writer and read a piece together, annotating specifically what is working and what is not. I then give them one focused thing to work on in the next piece, not five things. I check in at draft stage rather than waiting for the final version, because catching a structural problem early is much cheaper than unpicking it at the end. For writers who are consistently late or whose copy is consistently under-par, I have a direct conversation early rather than managing around the problem. I have also found that writers develop fastest when they can see excellent examples of what they are trying to do, so I build a small library of reference pieces for each section of the publication.

Audience development is an editorial responsibility, not just a marketing one. The content decisions I make determine who finds us, what they share, and whether they come back. I look at audience data weekly with three questions in mind: what is bringing new readers in, what is making them stay and return, and what is the gap between our intended audience and our actual audience? If those two things are diverging, it is an editorial signal, not a distribution problem. I have also worked closely with SEO and social teams to understand how format and headline choices affect reach, but I am careful to use those signals as inputs to editorial judgment rather than letting them drive it. A publication that optimises entirely for clicks tends to erode the trust that makes readers come back. The balance I aim for is a majority of content that serves the core audience well, with a smaller proportion designed to bring in new readers who might become regulars.

A senior commercial partner had contributed a bylined opinion piece as part of a content partnership agreement. When I read it before publication I found that two of the central claims were not supported by the sources cited, and a third was a contested interpretation presented as established fact. The commercial team was anxious because the partner had already been promised publication. I contacted the partner directly, explained exactly what the editorial concerns were with the specific passages, and offered two options: a revised version that addressed the factual issues, or a different format that did not make the contested claims. I was clear that the piece as written could not run, regardless of the commercial arrangement. The partner chose to revise. The revised version ran two weeks later and the relationship was preserved. The commercial team initially felt I had created a problem, but I think that outcome proved the approach right. A published piece with a factual error would have been a much bigger problem than a two-week delay.

I led a team of eight through a transition from a predominantly long-form print-focused operation to a digital-first, mixed-format model. The biggest challenge was not the technical upskilling: most writers adapted to shorter formats faster than I expected. The harder problem was cultural. Several senior writers felt that shorter digital formats were a diminishment of the craft, and that anxiety was expressed in subtle ways, including reluctance to pitch digital stories and a tendency to produce long pieces for short slots. I tackled this by being very explicit about the value I placed on each format: the digital explainer was not easier than the long-form essay, it was a different discipline with its own craft. I also made sure that the most respected writer on the team was the first person to do the new formats well, which shifted the internal perception significantly. I checked in individually with each team member over the first two months to understand concerns that were not being raised in group sessions.

A reporter brought me an investigation into a private company that included a claim that the company had knowingly mis-sold a financial product to elderly customers. The sourcing was solid: three named sources with direct knowledge and supporting documents. But the claim directly imputed deliberate wrongdoing to named individuals, which is the highest-risk category for defamation. Before seeking right of reply I sent the relevant sections to our media lawyer for a quick read. The lawyer identified that the phrasing in one paragraph was stronger than the evidence supported and suggested a modification that made the claim more precise without weakening the story. We also extended the right-of-reply window slightly to give the subjects a reasonable amount of time. The story ran without legal challenge. The lesson I took is that legal review is not about caution for its own sake: a well-constructed piece with tight sourcing and precise language is more legally safe and also more credible to readers.

Quality management at volume requires systems, not just good editors. I run a tiered review process: senior staff copy gets a standard sub-editing pass, new staff copy gets a more detailed review with feedback, and new freelancers always get a first-draft review before the final edit, because problems caught at first draft are much cheaper than last-minute rewrites. I also maintain a shared corrections and standards log so that recurring issues are visible across the team: if three different writers are making the same error, that is a training issue, not three individual mistakes. For volume periods I triage by risk rather than by order received: a piece that makes contested factual claims gets priority in the review queue regardless of its publication time. I also hold a short weekly content review meeting where recent pieces are discussed, which serves as an informal quality benchmark and creates space for the team to raise concerns before they become patterns.

I use analytics as a diagnostic tool rather than a decision-making tool. I look at which topics and formats are performing above or below expectation, and I ask why, not just what. When an article significantly outperforms I want to understand whether it was the topic, the format, the headline, the timing, or a distribution factor like a newsletter feature. When something underperforms I ask the same questions before drawing conclusions. I set up a weekly dashboard with the four metrics I care most about: organic sessions, scroll depth, return visit rate, and social referral. I share this with the team once a week with brief annotations so that data literacy is a shared capability rather than sitting with one person. I am also careful about what I do not let data drive: decisions about which stories matter, which voices to commission, and what the publication stands for are editorial judgments that data can inform but should not replace.

I treat right of reply as a journalistic obligation, not a legal formality, and that distinction matters for how it is done. When a piece makes specific factual allegations about an individual or organisation, right of reply goes to the specific claim, not to the article as a whole. I write or approve the right-of-reply letter myself so the framing is precise and the deadline is reasonable: typically 48 hours for a standard story, longer for an investigation. I keep a record of every right-of-reply letter sent and the response received, including non-responses, so there is a clear audit trail. If a subject provides information that changes the factual picture, I always review the piece before publication rather than treating the right-of-reply process as a box-ticking exercise. I also separate right of reply from pre-publication review of full articles, which I do not offer as a rule, because allowing subjects to see the full text before publication changes the dynamic significantly.