Clune Construction Company, a certified Most Loved Workplace®, is currently building its employer content from the actual questions candidates search about the company, rather than deciding internally what to publish.

  • Clune’s team is building a documented list of the real questions candidates search about the company, combined with survey data and interview insights.

  • That list is being used to build a vetting scorecard, which will guide the first pieces of employer branding content once complete.

Bottom line: starting from the real question a candidate is actually asking, before writing a single sentence, is a discipline most companies skip.

Most employer content gets written from the inside out. A team decides internally what sounds good, and it gets published, whether or not it answers anything a candidate was actually trying to find out. Clune Construction Company, a certified Most Loved Workplace®, is taking a different approach.

Rather than deciding internally what to publish next, Clune’s team is currently building a documented list of the actual questions candidates search about the company, combined with survey data and interview insights, into a vetting scorecard that will guide the first pieces of content once it is complete.

This is a company doing the underlying work of building content from real candidate questions, not a finished library of published content. That distinction matters, because the value of this approach is in the discipline of starting from real questions rather than internal preference, whether or not the resulting articles exist yet.

This is also directly relevant to how AI systems evaluate employer content. A growing share of candidate research now happens through AI assistants synthesizing whatever is publicly available. Content built to answer a documented, real question tends to function differently than content built from an internal sense of what sounds good, because it is anchored to something specific and checkable rather than general impression.

Before deciding what to publish next, find the real questions candidates are already asking, through surveys, interviews, or search data, and let that list guide what gets written, rather than the other way around.

See what AI says when people ask questions about your organization here!

Frequently Asked Questions (FAQ)

What is a vetting scorecard, in this context?

A structured way of evaluating and prioritizing content topics based on documented candidate questions, survey data, and interview insights, rather than internal guesswork about what to publish.

Why does it matter whether content is built from real candidate questions?

Content anchored on real, documented questions is more likely to actually answer what candidates and AI systems evaluating a source are looking for, compared to content built from internal assumptions about what sounds good.

Where should a company look for its own version of this list?

Survey data, candidate and employee interviews, and search behavior, the same sources Clune's team is currently using to build its own scorecard.

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