From Gut Feel to Hard Data: How Fundraising Direct Rebuilt Hiring with HiringBranch

HiringBranch and Fundraising Direct showed how skills-based hiring cut interviews, boosted quality, and protected human empathy

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Skills based hiring, Hiringbranch, Bell Canada, Fundraising Direct
Contact Center & Omnichannel​News

Published: February 6, 2026

Rob Wilkinson

As automation handles more simple customer journeys, many CX leaders are asking where humans now create the most value.

At Customer Contact Week, HiringBranch CEO Stephane Rivard and Fundraising Direct Operations Director Sarah Wise argued that the answer lies in changing how contact centers hire.

Their session showed how skills-based hiring, powered by AI simulations, helps identify fundraisers and agents who can truly communicate, handle objections, and stay resilient, instead of just looking good on a CV.

“You hire for hard skills or for CVs, you fire for soft skills. This goes away,” said Rivard.

Using a live case study from Fundraising Direct, plus results from Bell Canada, they set out a clear path for CX leaders who want better performance and less recruiter strain.

Fundraising Direct: High-Stakes, Human Conversations

Fundraising Direct is a specialist telephone fundraising agency that supports charities such as the Red Cross and UNICEF. The team runs hundreds of fundraisers and hires 150 to 200 people a year, often students and early-career workers.

Wise stressed how human the work is:

“We are a telephone fundraising agency. We fundraise on behalf of the charities we work for. The client and supporter relationship is really important.”

Agents must build rapport fast and handle emotional topics. “We are asking people for money, which is never easy to do,” she said. “They need to have very human conversations. It must not sound impersonal. It cannot be anything less than a human interaction.”

Old Process: Time-Heavy and Gut-Led

Before HiringBranch, hiring relied on:

  • CV reviews
  • Group assessment centers
  • One-to-one interviews
  • A three day training program, then time in a monitored “grad bay”

The full process could take up to two weeks.

“We are a very small enterprise, and historically, we spent a lot of time and resource on trying to find the right candidates,” Wise said.

Recruiters spent hours screening, even though the real success factors were soft skills on live calls.

Switching to Skills-Based Hiring

From CVs to Job Simulations

HiringBranch built a custom assessment that mirrors real fundraising calls. Candidates complete an online simulation that tests:

  • Fluency
  • Ability to build rapport
  • Objection handling
  • Emotional control during tough calls

The platform scores performance and links it to the outcomes Fundraising Direct cares about, such as decision-made contacts and pledge results.

Fundraising Direct assumed empathy would be the key predictor. The data showed a different picture.

“They thought that empathy would be the most important skill,” said Rivard. “There was no correlation.”

Instead, fluency, rapport building, and objection handling showed the strongest link to performance across campaigns.

Reducing Bias and Surfacing Hidden Talent

The assessment runs without demographic or background data.

“When they run these candidates through the platform, we have no background about them,” Rivard explained. “It is really based on the skills they can demonstrate.”

This gives Fundraising Direct a clearer view of who can succeed, not just who presents well on paper.

“Somebody could be technically qualified on paper, but if they do not have the skill set, it is a personality thing we are looking for,” Wise noted.

Cutting Out Interviews, Speeding Time to Hire

With clear benchmarks, Fundraising Direct removed most manual steps.

The new flow:

  1. Candidate applies and receives a HiringBranch assessment link.
  2. If the candidate scores above a set threshold, they go straight into training.
  3. HiringBranch flags “perfect fit” and “trainable” candidates, plus target skills to coach.

“The first thing that we were able to do was just stop screening by telephone,” Wise said. “We actually are able now to just eradicate interviews altogether. We do not have to see them, just get them straight into training.”

The assessment is also mobile friendly.

“It is a nice layout, a nice format. People can do it from their cell phones,” she added.

The impact on operations has been direct:

“It has given me the gift of time,” Wise said. “My team is able to spend more time with the fundraisers, coaching them, mentoring them. We are not caught up elsewhere in the business.”

Results: Higher Quality, Better Fit

Since adopting skills-based hiring, Fundraising Direct has seen clear gains.

Wise highlighted:

  • Training pass rates now “consistently above 85 percent.”
  • Around a 10 percent uplift in overall call quality, with variation by campaign.

“Because we have the skill set at point of recruitment, the minute the new telephone fundraiser hits the phones, the quality is fantastic,” she said. “That does directly translate to revenue and just getting aid out to where it needs to be.”

The team also sees fewer mis-hires who quickly decide the work is not for them.

“We are not having people after two weeks say, ‘I cannot do this role,’” Wise shared. “We just do not hear that anymore. We know it is a good fit personality type.”

Bell Canada: Scale Proof for Skills-Based Hiring

To show that this approach scales, Rivard pointed to Bell Canada, which hires around 8,000 agents a year for its contact centers.

Before HiringBranch, Bell used long, non mobile assessments and saw high drop off between hiring stages. Around a quarter of candidates failed training due to weak communication skills.

Bell integrated HiringBranch into its applicant tracking system and shifted to AI scored, soft skills simulations that measure empathy, communication, and problem solving in realistic scenarios.

According to Veronique LaCasse, Senior Recruiting, Training and Onboarding Manager at Bell Canada :

“We now rely on AI and skills oriented scenarios demonstrating the skills and behaviors of candidates that determine if they are the best fit for the roles available.”

Reported outcomes include:

  • Early attrition down to about 10 percent at day 90.
  • Around 45 percent of agents reaching the top two performance quartiles within 30 days.
  • Less recruiter time spent in interviews due to strong score and performance correlation.

“The impact on our business is very positive,” LaCasse said. “It is a win on cost, efficiency, and productivity.”

What CX Leaders Can Learn

The CCW session highlighted four practical lessons for CX and contact center leaders.

Start with outcomes.
Define 1 or 2 core KPIs, such as decision-made contacts, early attrition, or quality scores. Use data to see which soft skills link to those measures, rather than guessing.

Test real work, not abstract traits.
Open ended, job-like simulations capture how people respond in live calls. They reveal fluency, rapport building, and objection handling in context, not just test scores.

Use AI to free up people, not replace them.
In both case studies, recruiters now spend less time screening and more time partnering with operations and training. They use assessment data to tailor onboarding instead of running basic filters.

Keep humans at the center of complex CX.
Automation can handle simple tasks, but donors and customers still want a human for emotional or complex questions.

“At some point someone wants to talk to somebody, and you need to find a way to find these great communicators,” Rivard said.

For Wise, the link between hiring and impact is now clear.

“If we are improving and cultivating people in their performance, then we do get campaign extensions from huge charities like UNICEF,” she said. “If the quality is there, it does directly translate to revenue and impact.”

As contact centers evolve, the message from CCW is simple. The organizations that win will not be those that hire the fastest, but those that can reliably place the right people in the right conversations, backed by hard data on what great actually looks like.


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