The secret to securing great talent is a first-rate candidate experience. If you have been in any way entangled in the aftermath of 2021’s Great Resignation, you know that even an attractive remuneration package, with compelling benefits, is not enough: Now, more than ever, prospective hires will want to see the best of your organisation, and that includes the best of you. You must be fast, decisive, and flexible, from the point of first contact.
This is a problem amplified by scale. If you’re responsible for hiring 100,000 employees per year, for instance, you may find you are required to provide a top-notch candidate experience for that many prospects. You could decide that it is better to do things the old fashioned way, but it is more and more likely that, in doing so, you will miss out on great talent. The cost of such losses is best avoided.
Automation, be it through an assessment tool, conversational Ai platform, or Applicant Tracking System (ATS), is the simple key to solving volume hiring in a chaotic market. However, understandably, many high-volume hiring managers tend to think that automation comes at the cost of personalisation and human contact. If, for instance, you’re processing 5,000 prospects to fit 300 job openings, how do you ensure your candidates are met with the high-touch journey they expect? Is an automated Ai conversation, in the minds of candidates, not just as impersonal as older methods of qualification?
What ‘high-touch’ actually means, and its purpose
On the face of it, ‘high-touch’ implies an emphasis on person-to-person, face-to-face contact in your hiring process. If you can see your candidates, if you can greet them warmly and exalt your free-breakfast policy, you can make them feel special. Sending an email or a link to a form is impersonal, outmoded, and risks alienating the people you want to attract.
What if, instead, high-touch is a stand-in for meaningful contact, instead of lots of contact? What if you could conduct a smooth, quick, and painless interview process that:
- Asked the best from candidates, and allowed them to provide thoughtful responses in their own time
- Explored the human aspects of their personality, and not just the line items on their CV
- Ignored, by design, the aspects of candidates prone to bias (such as appearance, ethnicity, age, and so on)
Is that not more effective than a by-the-book interview in which you smiled a lot, engaged in forgettable small talk, and discussed a laundry list of perks?
Woolworths, Australia’s largest private employer, adopted the smart-touch automated hiring approach, and won handsomely for it. They used our Chat Interview (chat-based) and Video Interview (video-based) solutions to assess nearly 9,000 candidates, achieving a candidate satisfaction score of 9.2 out of 10. We saved the hiring team time and money, helped give each of their candidates the fairest possible go, and best of all, helped them achieve their hiring targets.
Woolworths wanted the equivalent of a high-touch candidate experience, and judging by these candidate testimonials, they certainly got it:
“The chat makes you feel like you’re in a safe space – it gives everyone an equal opportunity instead of an in person interview as people can get extremely nervous”.
“I found the process to be reflective and I liked how they wanted to know about me”.
“Everything was amazing! By far the best interview system I’ve encountered! It allowed me to be comfortable and be myself, it really allowed me to take my time with my responses rather than stutter over my words”.
“It was great. I like the potential to retake videos and how quick you’ve responded”.
There you have it: That is how a small hiring team can process nearly 10,000 candidates, using conversational Ai, and offer a truly high-touch candidate experience. But the benefits don’t stop there.
With a smart-touch automation solution, Talent Analytics can heighten your touch
When you entrust your hiring process to Smart Interviewer, our smart interviewer, you automate the process of meaningful data collection. That data is then transformed into actionable insights that help you improve your hiring processes. With TalentInsights, you could learn:
- Your average time to hire
- Estimated time saving in hours (incidentally, we’ve helped our customers save a total of 530,000 hours that would have been spent in cumbersome, high-touch interviews)
- The quality of your candidate pool overall, or by gender
- Overall candidate engagement scores
And much more. Suddenly, you have the numbers to back your wider hiring strategies, be they focussed on DEI, or fairness, or another goal. You can show your business that you are making real, quantifiable strides, and leading the way in efficiency and social responsibility.
The appetite for good, actionable data in HR is higher than it has ever been. Hiring managers are waking fast to the realities of the Great Resignation – that we just don’t know as much as we should about what constitutes good talent and candidate experience. In other words: We don’t really know why people are leaving, and we don’t really know why they do or don’t choose us in the first place.
According to a recent study by Madeline Laurano, founder of Aptitude Research, only 50% of the companies that invest in Talent Analytics actually trust the source of their data. When you consider that around 80 million American workers are hourly workers, one of the hardest-to-recruit employment segments of the moment, it becomes clear that the need for useful data is absolutely critical.
What approach will you take? What kind of experience will you provide your candidates, before and after hiring? What kind of data will guide your decisions? Remember: The choice to do nothing is still a choice, and it has an indeterminate cost.
Related
Blog
What’s More Ethical: Measuring Skills or Guessing Them?
Barb Hyman, CEO & Founder, Sapia.ai
Why skills data matters for HR and CHROs
Every CHRO I speak to wants clarity on skills:
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What skills do we have today?
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What skills do we need tomorrow?
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How do we close the gap?
The skills-based organisation has become HR’s holy grail. But not all skills data is created equal. The way you capture it has ethical consequences.
Two very different approaches to skills analysis
1. Skills inference from digital traces
Some vendors mine employees’ “digital exhaust” by scanning emails, CRM activity, project tickets and Slack messages to guess what skills someone has.
It is broad and fast, but fairness is a real concern.
2. Skills measurement through structured conversations
The alternative is to measure skills directly. Structured, science-backed conversations reveal behaviours, competencies and potential. This data is transparent, explainable and given with consent.
It takes longer to build, but it is grounded in reality.
The risks of skills inference HR leaders must confront
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Surveillance and trust: Do your people know their digital trails are being mined? What happens when they find out?
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Bias: Who writes more Slack updates, introverts or extroverts? Who logs more Jira tickets, engineers or managers? Behaviour is not the same as skills.
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Explainability: If an algorithm says, “You are good at negotiation” because you sent lots of emails, how can you validate that?
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Agency: If a system builds a skills profile without consent, do employees have control over their own career data?
A more human approach: skills measurement
Skills define careers. They shape mobility, pay and opportunity. That makes how you measure them an ethical choice as well as a technical one.
At Sapia.ai, we have shown that structured, untimed, conversational AI interviews restore dignity in hiring and skills measurement. Over 8 million interviews across 50+ languages prove that candidates prefer transparent and fair processes that let them share who they are, in their own words.
Skills measurement is about trust, fairness and people’s futures.
Questions every HR and CHRO should ask
When evaluating skills solutions, ask:
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Is this system measuring real skills, or only inferring them from proxies?
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Would I be comfortable if employees knew exactly how their skills profile was created?
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Does this process give people agency over their data, or take it away?
The real test of ethics in the skills-based organisation
The choice is between skills data that is guessed from digital traces and skills data that is earned through evidence, reflection and dialogue.
If you want trust in your people decisions, choose measurement over inference.
To see how candidates really feel about ethical skills measurement, check out our latest research report: Humanising Hiring, the largest scale analysis of candidate experience of AI interviews – ever.
FAQs
What is the most ethical way to measure skills?
The most ethical method is to use structured, science-backed conversations that assess behaviours, competencies and potential with consent and transparency.
Why is skills inference problematic?
Skills inference relies on digital traces such as emails or Slack activity, which can introduce bias, raise privacy concerns and reduce employee trust.
How does ethical AI help with skills measurement?
Ethical AI, such as structured conversational interviews, ensures fairness by using consistent data, removing demographic bias and giving every candidate or employee a voice.
What should HR leaders look for in a skills platform?
Look for transparency, explainability, inclusivity and evidence that the platform measures skills directly rather than guessing from digital behaviour.
How does Sapia.ai support ethical skills measurement?
Sapia.ai uses structured, untimed chat interviews in over 50 languages. Every candidate receives
Blog
Mirrored diversity: why retail teams should look like their customers
Walk into any store this festive season and you’ll see it instantly. The lights, the displays, the products are all crafted to draw people in. Retailers spend millions on campaigns to bring customers through the door.
But the real moment of truth isn’t the emotional TV ad, or the shimmering window display. It’s the human standing behind the counter. That person is the brand.
The missing link in retail hiring
Most retailers know this, yet their hiring processes tell a different story. Candidates are often screened by rigid CV reviews or psychometric tests that force them into boxes. Neurodiverse candidates, career changers, and people from different cultural or educational backgrounds are often the ones who fall through the cracks.
And yet, these are the very people who may best understand your customers. If your store colleagues don’t reflect the diversity of the communities you serve, you create distance where there should be connection. You lose loyalty. You lose growth.
We call this gap the diversity mirror.
What mirrored diversity looks like
When retailers achieve mirrored diversity, their teams look like their customers:
- A grocery store team that reflects the cultural mix of its neighbourhood.
- A fashion store with colleagues who understand both style and accessibility.
- A beauty retailer whose teams reflect every skin tone, gender, and background that walks through the door.
Customers buy where they feel seen – making this a commercial imperative.
How to recruit seasonal employees with mirrored diversity
The challenge for HR leaders is that most hiring systems are biased by design. CVs privilege pedigree over potential. Multiple-choice tests reduce people to stereotypes. And rushed festive hiring campaigns only compound the problem.
That’s where Sapia.ai changes the equation: Every candidate is interviewed automatically, fairly, and in their own words.
- Bias is measured and monitored using Sapia.ai’s FAIR™ framework.
- Outcomes are validated at scale: 7+ million candidates, 52 countries, average candidate satisfaction 9.2/10.
- Diversity can be measured: with the Diversity Dashboard, you can track DEI capture rates, candidate engagement, and diversity hiring outcomes across every stage of the funnel.
With the right HR hiring tools, mirrored diversity becomes a data point you can track, prove, and deliver on. It’s no longer just a slogan.
Retail recruiting strategies in action: the David Jones example
David Jones, Australia’s premium department store, put this into practice:
- 40,000 festive applicants screened automatically
- 80% of final hires recommended by Sapia.ai
- Recruiters freed up 4,000 hours in screening time
- Candidate experience rated 9.1/10
The result? Store teams that belong with the brand and reflect the customers they serve.
Read the David Jones Case Study here 👇
Recruiting ideas for retail leaders this festive season
As you prepare for festive hiring in the UK and Europe, ask yourself:
- How much will you spend on marketing this Christmas?
- And how much will you invest in ensuring the colleagues who deliver that brand promise reflect the people you want in your stores?
Because when your colleagues mirror your customers, you achieve growth, and by design, you’ll achieve inclusion.
See how Sapia.ai can help you achieve mirrored diversity this festive season. Book a demo with our team here.
FAQs on retail recruitment and mirrored diversity
What is mirrored diversity in retail?
Mirrored diversity means that store teams reflect the diversity of their customer base, helping create stronger connections and loyalty.
Why is diversity important in seasonal retail hiring?
Seasonal employees often provide the first impression of a brand. Inclusive teams make customers feel seen, improving both experience and sales.
How can retailers improve their hiring strategies?
Adopting tools like AI structured interviews, bias monitoring, and data dashboards helps retailers hire fairly, reduce screening time, and build more diverse teams.
Blog
The Diversity Dashboard: Proving your DEI strategy is working
Why measuring diversity matters
Organisations invest heavily in their employer brand, career sites, and EVP campaigns, especially to attract underrepresented talent. But without the right data, it’s impossible to know if that investment is paying off.
Representation often varies across functions, locations, and stages of the hiring process. Blind spots allow bias to creep in, meaning underrepresented groups may drop out long before offer.
Collecting demographic data is only step one. Turning it into insight you can act on is where real change and better hiring outcomes happen.
What is the Diversity Dashboard?
The Diversity Dashboard in Discover Insights, Sapia.ai’s analytics tool, gives you real-time visibility into representation, inclusion, and fairness at every stage of your talent funnel. It helps you connect the dots between your attraction strategies and actual hiring outcomes.
Key features include:
- Demographic filters – Switch between gender, ethnicity, English as an additional language, First Nations status, disability, and veteran status. View age and ethnicity in standard or alternative formats to match regional reporting needs.
- Representation highlights – Identify the top five represented sub-groups for each demographic, plus the three fastest-growing among underrepresented groups.
- Track trends over time – See month-by-month changes in representation over the past 12 months, compare to earlier periods, and connect the data back to your EVP and attraction spend.
- Candidate experience metrics – Measure CSAT (satisfaction) and engagement rates by demographic to ensure your hiring process works for everyone. Inclusion is measurable.
- Hiring fairness – Compare representation in your applied, recommended, and hired pools to spot drop-offs. Understand not just who applies, but who progresses — and why.
From insight to action
With the Diversity Dashboard, you can pinpoint where inclusion is thriving and where it’s falling short.
- See if your EASL candidates are applying in high numbers but not progressing to live interview.
- Spot if candidates with a disability report high satisfaction but have lower offer rates.
- Track the impact of targeted campaigns month-by-month and adjust quickly when something isn’t working.
It’s also a powerful tool to tell your success story. Celebrate wins by showing which underrepresented groups are making the biggest gains, and share that progress with boards, executives, and regulators.
Built on science, backed by trust
Powered by explainable AI and the world’s largest structured interview dataset, your insights are fair, auditable, and evidence-based.
Measuring diversity is the first step. Using that data to take action is where you close the Diversity Gap. With the Diversity Dashboard, you can prove your strategy is working and make the changes where it isn’t.
Book a demo to see the Diversity Dashboard in action.