Viktor Donner works in recruitment and talent acquisition. Donner's LinkedIn posts explain a candidate-centred approach Donner calls “candidate sales,” focused on presenting job opportunities clearly and treating applicants with respect.
Viktor Donner is most useful for LinkedIn posts about candidate sales and candidate-centred hiring.
Best for
Recruitment agencies or hiring software brands needing LinkedIn thought leadership on hiring experience.
Not for
Consumer home-goods campaigns needing video-first TikTok or Instagram product demonstrations and sales lift.
Key takeaways
Donner calls accepting a job offer a candidate's buying decision.
They argue rejected candidates deserve concrete feedback because treatment affects employer reputation.
A VECTARY project combined an HR audit, employee feedback, onboarding process and checklist.
Check first: Confirm recent LinkedIn analytics and audience details before contacting them.
Main ideas
Treat a job offer as something a candidate chooses · Respectful treatment of applicants affects the employer’s reputation · Use technology to ease overloaded hiring while keeping room for human contact
Viktor Donner works in recruitment and talent acquisition.
In LinkedIn posts, they are best known for advocating “candidate sales”: presenting jobs as opportunities candidates can choose, rather than treating recruitment as a company-led search.
They also write about respectful rejection feedback, hiring operations and how recruiting practices shape employer reputation.
Follow their work for practical arguments about making hiring clearer and more candidate-centred, illustrated by examples such as an HR audit and onboarding changes at VECTARY.
Donner connects candidate experience to how recruitment works in practice.
They argue that candidates weigh an employment offer much as customers decide whether to buy, so employers need to explain the opportunity and its value.
They call for useful feedback to rejected applicants and describe a VECTARY project combining an HR audit, employee feedback, an onboarding process and a checklist with named responsibilities.
Other posts extend this interest in service and process to recruiter workload, conversational AI, recruitment costs and ecommerce customer service.
The sample is weighted toward recruitment; the ecommerce posts show a related customer-service interest, not an equally developed second body of work.
Ask Donner whether they have signature books, shows or other earlier work that could help explain name searches.
Viktor Donner’s posts return to one central idea: hiring works better when employers treat candidates as people choosing an opportunity, not as entries to process.
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That leads to calls for clearer job offers, respectful rejection, and tools that reduce routine work without replacing human contact. They also apply a similar focus on service to posts about vintage-goods e-commerce.
Treat a job offer as something a candidate chooses
Donner calls this approach “candidate sales.”
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They argue that accepting a job is a buying decision: candidates trade time and knowledge for pay and an opportunity to contribute.
Employers should make that opportunity attractive and present jobs as opportunities, rather than simply recruiting for vacancies.
They also connect the approach to lower hiring costs and more predictable staffing.
In one post, Donner asks how attractive a company is to its ideal candidate and says recruiters should sell jobs as opportunities. In another, they argue that sourcing costs time and money, and link candidate sales to reducing cost per hire and supporting business growth.
Respectful treatment of applicants affects the employer’s reputation
Donner argues that recruitment should be candidate-centred.
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A rejection should explain why someone was not selected and offer concrete suggestions, rather than send a vague automated message. They argue that applicants remember how the process made them feel and connect that experience with the employer’s brand.
Donner points to candidates who have spent time preparing a CV and cover letter, and says they deserve specific feedback and recommendations for improvement.
Use technology to ease overloaded hiring while keeping room for human contact
Donner describes a hiring process where a flood of applications leaves recruiters only seconds for each CV and produces generic rejections.
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They present conversational AI as a possible way to screen applicants and prepare interview notes, freeing recruiters to focus on conversations. Ask how the team will automate volume without making applicants feel ignored, given Donner’s call for personal, useful feedback.
Donner’s scenario begins with more than 300 weekend applications, quick CV reviews, and vague rejection messages. They then imagine AI screening candidates, scheduling qualified applicants, and generating interview notes so recruiters can focus on human interaction.
The posts offer both a critique of impersonal automated rejections and a case for AI in screening. Ask how automated processes will still deliver the concrete feedback Donner advocates.
Transparency and organised work are part of a better hiring experience
In a post about recruiting for Neohunter, Donner describes naming the hiring company and salary range when contacting candidates.
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They also present a shared tool stack, automation, remote work, and fewer long meetings as ways to organise recruitment work. The emphasis is on making the process clear for candidates and manageable for the team.
The hiring post lists a recruitment CRM, Notion, Slack, video tools, Google Workspace, and design software, and says the agency uses automation platforms such as Zapier or Make.
Good service matters in e-commerce as well as recruitment
Donner also writes about customer experience in vintage-goods sales.
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They argue that reviews and the way customers are treated shape a business’s reputation, and that accepting a short-term loss can be worthwhile if it preserves the customer relationship. This is a separate thread from their recruitment writing, but echoes their focus on how people experience a transaction.
A post about a Pragotron clock sold to a UK customer mentions an insurance claim that Collecthor recovered in full and uses the story to make a point about service and customer reviews.
Start here to understand the phrase repeated across the sample and the recruiting philosophy behind it.
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Donner defines candidate sales as a talent-acquisition method that borrows from how businesses attract customers.
The key move is to treat an employment offer as a candidate's buying decision: candidates exchange their time and knowledge for money when they see a chance to affect the business or society through an attractive employee value proposition.
They ask how attractive the company is to the ideal candidate and argue recruiters should sell jobs as opportunities rather than recruit for them.
For brands planning a campaign
This is the clearest anchor for a content plan on candidate sales. Use it to brief a piece explaining employee value propositions, candidate decision-making, and how job marketing differs from traditional recruiting.
It shows the candidate-experience critique behind the candidate-sales idea and sets a concrete standard for rejection feedback.
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Donner argues that many HR and recruitment experiences are poor because the problem is structural: people are labelled as resources.
Recruiters should shift from a company-centred to a candidate-centred approach and act more like human sales representatives.
A rejected candidate who spent time on a CV and cover letter should receive concrete feedback and recommendations for improvement.
Candidates remember how the process made them feel and associate that feeling with the brand.
For brands planning a campaign
Use for content about candidate experience, rejection communication, and employer-brand risk. A recruiter audience can test its feedback templates against this argument.
It shows the process at a named company rather than describing candidate-sales ideas only in the abstract.
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Donner describes a cooperation with VECTARY that began with an HR audit to identify immediate challenges and diagnose organisational processes and team atmosphere.
The work included discussions with engineers, an HR roadmap with prioritised steps, employee feedback on motivation, a new adaptation process with clear goals and expectations, a checklist linked to responsible people, and a recommendation to hire an in-house HR representative.
The reported result was improved human-resources management and onboarding for new engineering team members.
For brands planning a campaign
This is the strongest case study for a content plan on diagnostic recruiting work. It can support a post or guide on running an HR audit and turning findings into an onboarding roadmap.
It explains what the day-to-day recruitment work looks like and which operating principles they promote to candidates.
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Donner invites candidates to contact them or Juraj Lovas to see if there is a fit and lists reasons to join Neohunter.
These include transparency with the hiring company and salary ranges; tools such as Recruit CRM, Notion, Slack, Bubbles, Loom, Google Workspace, Rebrandly, and Canva; and automation through Zapier or Make.
The projects include software engineers for microprocessors and AI-powered smart-energy solutions.
The stated principles are no corporate bureaucracy, few long meetings, remote asynchronous work, kindness, discipline, and a result-driven mindset.
For brands planning a campaign
Useful for briefs about recruitment operations, employer brand, and the tool stack behind modern hiring. It gives a recruiter audience concrete examples of transparency, async work, and candidate outreach workflows.
It shows how recruiting pain points connect to automation and why AI is part of this content territory.
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Donner describes a recruiter opening an ATS to more than 300 weekend applicants, giving each CV three to five seconds, and sending vague automated rejections.
They say this leads to a poor candidate hiring experience, a crumbling employer brand, and recruiter burnout.
The post then imagines conversational AI such as Humanly screening applicants, placing qualified candidates in the calendar, generating interview notes, and freeing recruiters for human interaction and better hiring decisions.
For brands planning a campaign
This is a ready topic for AI-in-recruiting content. Treat it as an argument about automation and candidate experience, not as an independent product endorsement.
It explains why a company should care about candidate sales beyond candidate experience.
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Donner argues that candidate sales can maximise return on talent acquisition.
Sourcing and active recruiting take time and money, and the goal is a lower cost per hire.
In their account, candidate sales lets a company predict its talent pool more safely, keep just enough team members, deliver better services and solutions, grow revenue, and scale.
For brands planning a campaign
Pair this with the candidate-sales definition for content aimed at hiring managers and finance-minded talent leaders. It gives the methodology a measurable business rationale.
Open it to see the same service-and-feeling argument applied to ecommerce.
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Donner draws ecommerce customer-service lessons from the sale of a Pragotron clock to a UK customer and a Collecthor insurance outcome.
The post argues that customer reviews enhance reputation, positive shopping experiences matter in ecommerce, and a temporary loss can bring future profits.
It also repeats that customers may not remember the writing but will remember how they were made to feel.
For brands planning a campaign
This shows a non-recruiting commercial thread. It can support content about customer experience, reviews, and service recovery, though it is less central to a recruiting brief than the hiring posts.
Candidate experience and the rejection letter problem2
Selling vintage industrial goods as a second commercial track2
Recruiting tools, automation, and how an agency actually runs1
HR audit and organisational work as a service1
Candidate sales: hiring reframed as selling
Donner's most repeated argument is that recruitment should borrow from sales.
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One post defines the term by treating acceptance of a job offer as a candidate's buying decision, then asks how attractive the employer is to the ideal candidate.
The proposed answer is to sell jobs as opportunities rather than recruit for them.
A companion post extends the idea into business terms, arguing that candidate sales lets a company predict its talent pool, reduce cost per hire, and get more value from each hire.
The idea is framed as a mindset shift, not a step-by-step method, but points to concrete changes such as leading with the employee value proposition.
Defines the term, then makes the commercial case: sourcing and recruiting cost money, so treat the offer as a purchase decision.
For brands planning a campaign
For a recruiting agency campaign, this is the strongest hook: a content plan can turn the candidate-sales framing into practical pieces on writing job offers, positioning the employer, and measuring return on talent acquisition. A creator partnership built on this theme should ask Donner to move from the slogan to worked examples, since their posts state the principle more than they demonstrate the process.
Candidate experience and the rejection letter problem
A second recurring theme is how applicants are treated.
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One post says too many people report a bad HR experience, argues that labelling people as "human resources" is part of the problem, and calls for recruiters to give concrete rejection feedback and improvement advice.
Candidates, it says, will associate their treatment with the brand.
Another post dramatises the same problem from the recruiter's side: hundreds of weekend applications, three to five seconds per CV, vague automated rejections, a tired recruiter, and an eroding employer brand.
It then shows conversational AI screening applicants, filling the calendar with qualified candidates, and generating interview notes so the recruiter can focus on human interaction.
Turns the complaint into a recognisable scene, then offers a before-and-after fix. Here, the fix is a named tool rather than a process readers can copy.
The AI post names a specific product as the solution, making this content a natural fit for software sponsorship. It also shows how Donner writes about brands that hire their agency.
For brands planning a campaign
A campaign can pair the criticism with usable material: rejection-feedback templates, screening workflows, and response-time standards. The named AI example gives a vendor a clear placement angle on the same theme.
Recruiting tools, automation, and how an agency actually runs
When recruiting for their agency team, Donner describes the working stack in detail: a recruitment CRM with a browser extension for tracking projects, Notion for projects and ideas, Slack for real-time chat, asynchronous video tools, video outreach to candidates, a workspace suite for simple job-ad landing pages, and design software for candidate profiles.
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They welcome automation platforms and frame day-to-day operations as remote, asynchronous, and free of long meetings, balanced by kindness and a result-driven mindset. The post also sets out a transparency commitment: naming the hiring company and salary range when approaching candidates.
Uses a numbered pitch to describe the role, then lists tools as proof of how the team works rather than making abstract claims.
For brands planning a campaign
This is the most concrete strand for a partnership on recruitment operations or software.
Pieces could compare agency stacks, show how naming salary ranges changes candidate response, or demonstrate automation inside a hiring pipeline.
Assess whether the brand wants a partner who names competing tools in the same post.
One post is a client-engagement case study under Analysis, Solution, and Result headings.
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The work starts with an HR audit to diagnose processes and team atmosphere, then moves into conversations with engineers about the technology and the profile needed.
It results in a prioritised HR roadmap, employee feedback on motivation, a new onboarding process with clear goals, a checklist tied to named owners, and a recommendation to hire an in-house HR lead.
The stated result is improved human-resources management and onboarding of new engineering hires.
Presents the engagement in a fixed three-part structure, taking the reader through the diagnostic, interventions, and outcome.
Before commissioning a case study, ask for figures, a timeline, and client confirmation. The post provides none and has no publication date.
For brands planning a campaign
This positions Donner beyond posting job ads, in employer-brand and onboarding consulting. A campaign could commission a fuller case study in the same structure; ask for measurable results before commissioning, since the example does not provide them.
Selling vintage industrial goods as a second commercial track
Alongside recruitment, the feed carries posts about an e-commerce business selling restored industrial items, including a Czech-made clock sold to a UK customer, customer reviews, and an insurance claim fully compensated after a loss.
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The posts make the same point as the recruitment writing: customers may not remember the words, but they will remember how they were made to feel, so a good shopping experience matters more than a temporary loss.
Short, hashtag-led posts built around one customer story and one moral, rather than the numbered or structured formats used in the recruitment posts.
This is a separate business line from recruitment. The shared "how you made them feel" line appears almost word for word in both, reading as a reused formula rather than a topic-specific insight.
For brands planning a campaign
A recruiter assessing Donner should know the feed mixes hiring content with marketplace selling for vintage goods. Briefs should specify which track the campaign sits in; e-commerce or marketplace-experience brands have a second, smaller opening here.
Across Donner's posts, three formats recur: a numbered pitch or list, a short scene that builds a problem before offering a fix, and a labelled case study with analysis, solution, and result.
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The arguments also repeat across both business lines: recruitment should be run like sales, the candidate's experience decides the employer brand, and people remember how a transaction made them feel. The posts stay on LinkedIn, are text-only, and address the reader directly, often closing with a question or a call to get in touch.
Relies on a small set of structures and phrases rather than experimenting with new ones, making the writing predictable for a brand planning a series.
Donner's posts carry no publication dates, so the order in which these formats or arguments appeared, and any real shift over time, cannot be established from the posts.
For brands planning a campaign
A content plan can rely on the list, the problem-and-fix scene, and the case study as proven formats. It should also budget for the missing chronology: dating the existing corpus is a research gap a producer would need to close before claiming how Donner's thinking has developed.
Viktor Donner's posts document a client case study with VECTARY, a recruitment post for Neohunter, a product mention of Humanly, and promotion of Collecthor's vintage clock sales.
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Ask whether any of these posts involve a commercial relationship, sponsorship, affiliate deal, or investment.
VECTARY
Client
Donner's post describes an HR consulting engagement with VECTARY: an HR audit, roadmap, employee feedback, and a new onboarding process.
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It says "our cooperation" and links a case study, indicating VECTARY was a client. Ask whether the engagement is current.
Donner posts about selling vintage clocks and customer service under Collecthor, including a five-star review post, an insurance-compensated loss, and a link to industrial vintage products.
Donner’s work is easiest to explore in a few passes.
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Start with the candidate-sales argument: they ask how attractive a company is to the ideal candidate and treat accepting a job as a buying decision rather than a vacancy to fill.
Then read the posts on candidate experience: vague automated rejections, overloaded recruiters, and the case for concrete feedback sit alongside a post on using conversational AI to screen applicants and free up human contact.
A third strand covers how a recruitment agency actually runs, including naming the hiring company and salary range, a shared tool stack, automation, remote work, and an HR audit case study with analysis, solution, and result.
A smaller track applies the same service logic to selling vintage industrial goods.
The recurring question is how the employer looks from the candidate’s side, whether in a job offer, a rejection, or a purchase.
Cox writes about recruiting and talent acquisition from the practitioner’s side.
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They reference a TEDx talk on hiring mistakes, question the inherited linear hiring funnel, and ask how AI should change hiring rather than simply speed up old steps. That puts them close to Donner’s interest in candidate sales, current recruiting practice, and technology in hiring.
Cox tends to reflect on ideas, talks, and operating assumptions, while Donner states a named candidate-sales method and writes in more structured formats, such as numbered pitches and a labelled case study. Their posts also cover agency operations and vintage-goods e-commerce, which are outside Cox’s posts here.
Ricketts writes about applicant recruiting, the gap between a job description and the actual role, and how AI-generated candidate content affects hiring confidence.
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Like Donner, they start from hiring fundamentals and offer a workforce consultation, so readers interested in candidate quality and recruitment clarity have an obvious next follow.
Ricketts concentrates on organisational clarity, candidate verification, and consulting offers through Incipio Works.
Donner focuses more on candidate sales as a mindset shift, rejection feedback, and the internal tools and operations of a recruitment agency.
Their vintage e-commerce track has no counterpart in Ricketts’s posts here.
Clifford writes practical talent-acquisition content on job postings, employer branding, and AI in recruiting, including a staffing customer story about AI-sourced candidates and revenue.
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That overlaps with Donner’s recruiting-technology posts and interest in how automation changes hiring work.
Clifford is more tactical on job-ad copy and staffing outcomes, with a clear vendor and platform angle around LinkedIn and Hiring Assistant. Donner spends less time on posting structure and more on candidate sales, candidate experience, rejection feedback, and agency operations.
Placement decision for a campaign aimed at recruiting agencies: Viktor Donner's LinkedIn audience is real but effectively unmeasured.
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The only audience figure published here is a follower count for the linked profile — 4,754, observed 11 October 2026.
That establishes a modest, active-looking account.
It does not establish who those followers are, what they do, or where they work, so it cannot by itself support a paid placement decision.
Who the writing is aimed at.
The posts are written for people doing hiring.
One hiring post describes working at Neohunter, naming transparent salary ranges in outreach, a Recruit CRM stack, and software-engineering and smart-energy placements (selected example).
Several others argue a thesis the author calls "candidate sales" — treating an accepted job offer as a candidate's buying decision — and aim it at recruiters and talent-acquisition teams (selected examples).
One post walks through a day with 300+ weekend applicants in an ATS and pitches conversational AI screening as the answer.
A separate strand addresses e-commerce and vintage-retail customers and sellers, using a Pragotron clock sale and a five-star review as the material.
The content addresses hiring practitioners and agency owners, with an occasional small-business/retail audience.
What the posts do not show.
There is no platform demographic data, audience survey, or published reach, impression, or engagement data.
Nothing measures geography, age, gender, employer, occupation, or job seniority.
The LinkedIn follower count is the sole measured audience number.
Recency matters here.
The eight posts are dated 4 April 2018 through 6 May 2023.
No post is later than May 2023, so roughly three and a half years separate the most recent writing from the follower snapshot.
The account may have been active since then, but the posts do not show it.
A buyer should ask for recent activity and analytics rather than assume the 2026 follower base matches the 2018–2023 readership.
Before committing budget, ask Donner for (1) recent post analytics covering impressions, reach, and engagement for the last six to twelve months; (2) an audience survey or comparable documented source covering job function, seniority, industry, and country — YouTube-style demographic data would answer geography, age, and gender, but not employer, occupation, or seniority; and (3) recent results for the specific topics, depth, and formats the campaign would use, such as candidate-sales explainers, hiring-experience critiques, or ATS and screening-tool walkthroughs.
Request results at the same depth and format as the planned deliverable, since accumulated totals on older posts say nothing about future sponsored delivery.
The posts contain no published sponsorship package, rate card, media kit, or partnership inquiry route.
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Donner's content focuses on how the recruitment service Neohunter hires and works, how they handle candidate experience, and how the vintage-industrial retail shop Collecthor serves buyers.
The April 2023 post presents conversational AI Humanly (humanly.io) as a way to screen large applicant volumes, without stating whether the recommendation is paid or affiliate.
Buyers should negotiate terms directly and ask about disclosure, format, and pricing in the first conversation.
Recruitment agency need: a recruitment agency is hiring a talent-acquisition content creator to run a thought-leadership programme on candidate sales and hiring experience, aimed at recruiters, hiring managers, and agency owners, mainly on LinkedIn.
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Donner's posts are built for this programme.
Candidate sales is not a passing mention: one post defines accepting an offer as a candidate's buying decision and asks how attractive the employer is to the ideal candidate; a companion post makes the business case in terms of cost per hire and talent-pool planning.
That gives the programme a named angle, a definition, and a commercial argument recruiters already debate.
The candidate-experience strand supplies practical material.
One post calls for concrete rejection feedback and improvement advice because candidates carry their treatment into how they see the brand.
Another dramatises the recruiter's side of the problem: hundreds of weekend applications, three to five seconds per CV, and vague automated rejections.
A brand selling screening or hiring software can use that scene directly: Donner presents the problem, then shows conversational screening as the fix and names a tool.
Services buyers get the softer version: a creator who argues for process and standards rather than product features.
Two more pieces support the programme.
The Neohunter hiring post documents a working stack and a commitment to naming the hiring company and salary range in outreach—operational detail that resonates with an agency audience.
The VECTARY post presents a client engagement as analysis, solution, and result, a structure that transfers to a commissioned case study.
For contracting, ask for recent reach, engagement, and impression data and audience demographics; one LinkedIn account shows 4,754 followers, so the posts alone do not establish this as a reach play.
No sponsorship package, rate card, or media kit appears in the posts, so negotiate terms directly and agree disclosure before naming a product.
When to choose a specialist
Consumer home-goods brand need: a consumer home-goods brand wants a video-first creator to demonstrate products in short-form video across TikTok and Instagram and show measurable sales lift from the campaign.
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Donner is a poor fit on channel, format, evidence, and commercial precedent.
The posts are text posts on LinkedIn.
There is no video, transcript, short-form performance data, or content outside LinkedIn.
A campaign built around filmed demonstrations and platform-native short video cannot be assessed or delivered from this material.
The retail thread is not a substitute.
Donner writes about Collecthor, a business selling restored industrial items: a clock sold to a UK customer, customer reviews, and a compensated insurance claim.
Those posts are built for marketplace selling and reuse the same “how you made them feel” line as the recruitment writing.
This is a small, secondary strand, with no consumer reach data, product-demonstration format, or sales attribution.
Measurement is another problem.
The posts provide no impressions, reach, engagement, conversion figures, or audience demographics.
The only audience number is 4,754 followers on one LinkedIn account.
A campaign promising measurable sales lift would require baselines and reporting; ask whether the creator can establish and deliver those before committing.
Commercial precedent is also limited.
The posts include no sponsorship package, rate card, or inquiry route.
The one named commercial product—the screening tool in the AI post—is presented as the writer's recommendation, with no disclosed paid relationship.
There is no documented example of paid brand work, so a buyer cannot assume a standard offer, disclosure, or deliverable set.
A consumer brand seeking packaging, usage rights, and paid-media integration would need to negotiate each from scratch.
An online marketplace or small-retail campaign that values written customer-experience content could still work.
The reach-led video campaign is a poor fit.
A worked campaign example
Worked campaign angle for a recruitment thought-leadership programme: a three-post LinkedIn series plus one case-study piece, built on the idea that an offer is a buying decision.
Post one defines candidate sales and makes it concrete.
Take one job opening and rewrite the approach to candidates around the employee value proposition: what the work is, what the pay range is, why the role matters, and what a candidate is actually choosing between.
Donner's posts supply the definition; the campaign version should go a step beyond the slogan and show the rewrite.
Post two is a rejection-feedback teardown.
Take one vague automated rejection and rewrite it as a short, specific reply with reasons and improvement advice, then explain how that changes the employer brand.
This draws on Donner's argument that candidates remember how a process made them feel and connect that feeling to the brand.
Post three is a recruiter's Monday, told as a scene: an overflowing applicant queue, seconds per CV, and what a screening step should handle so the recruiter can spend time with people. Treat any named tool as their own recommendation unless the brand and creator first agree on a disclosed paid placement; the posts do not show disclosure.
The case-study piece follows the analysis, solution, result structure already used in Donner's VECTARY post: the hiring problem, diagnostic step, changes made, and outcome. Before commissioning it, agree what results can be shown; the example describes the outcome in words but provides no figures, timeline, or client confirmation.
Structure and handoff: budget for one plan, three posts, one long piece, and a comment-reply window.
Before committing, ask for post performance over the last six to twelve months, documented audience details on job function, seniority, industry, and country, results for this depth and format, and confirmation that the posts remain representative.
The posts have no reliable chronology or confirmed output after them.
Set the campaign baseline from the supplied data rather than accumulated totals on older posts.
The outreach message and full campaign plan belong in a later section; this angle is the input to them.
Choose Cox for a brief on improving the hiring process.
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In one post, Cox points to vague role requirements, similarity bias and resumes that can hide strong candidates, then makes the case for more structured tools.
In another, Cox asks whether AI should prompt teams to rethink inherited hiring steps rather than simply automate them.
These ideas can broaden a candidate-experience campaign into process design and fairness.
Cox’s examples focus on diagnosing hiring practices rather than candidate sales or the experience of receiving rejection feedback—the distinctive emphasis in Viktor Donner’s work.
Choose Ricketts for a campaign about recruiting fundamentals and retention.
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Ricketts’s posts connect clarity across the job description, interview and first day with a stronger employee relationship.
Another addresses concerns about misleading candidate information and recommends clearer success profiles, stronger interviews and verification.
This makes Ricketts a fit for guidance aimed at organizational leaders.
These examples take an advisory approach to workforce strategy rather than centering Donner’s candidate-sales framing or call for useful feedback to rejected candidates.
Choose Clifford for practical job-posting advice or a recruiting-technology story.
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One post recommends clear job titles, concise requirements, growth opportunities, and visible pay and flexibility information.
Another describes a recruiting team using AI and reports placement revenue attributed to AI-sourced candidates.
Together, they suit a campaign linking candidate-facing job copy with recruiting operations.
The reviewed examples give less attention to candidate treatment after rejection and do not center candidate sales. The revenue figure appears in a customer-story post and has not been independently verified here.