How March Consultants Made AI Matching Finally Deliver for Executive Search
Company: March Consultants
Who: Executive search boutique founded in 2017, working remote-first from the UK
What: Senior searches across investment and finance leadership
Before Spott: Loxo, plus separate tools for interview notes and outsourced CV formatting
Executive search firms have heard the "intelligent matching" pitch from every CRM vendor for a decade. March Consultants, a UK boutique placing senior investment and finance leaders, had lived the gap between pitch and product: they moved to Loxo two years before, and key capabilities they had been promised never arrived.
So when co-founder Charles Peck evaluated Spott, he did it the search-firm way: methodically, with his research team in the room, assuming nothing.
"Spott delivers intelligent matching and automation that finally lives up to what other CRMs promise."
Charles Peck, Co-Founder & CEO, March Consultants
What the evaluation looked like
Charles brought researchers and an external advisor into the demos and went after the bottlenecks one by one:
- Candidate reports. March presents candidates in meticulously formatted, branded documents. Producing them ate hours of researcher time per candidate, and part of the formatting was outsourced to a separate company.
- Bulk sourcing flow. A long list of 40 profiles in LinkedIn Recruiter had to become 40 complete records in the database without copy-paste. ("That's a massive saving," Charles noted when he saw the bulk import.)
- Matching that earns trust. The team had tested AI matching tools before that took months of tuning and still underdelivered. They pushed on reliability, on how it learns, and on whether it reads the whole picture: CVs, deep-dive interview transcripts, and notes, not keywords.
- A mobile app that does something. Their previous app was "basically a directory." Charles wanted to move candidates through a pipeline from a train seat. A remote-first team lives or dies on that.
What changed
March went live on Spott in early 2026, and the wins are specific:
- The outsourced CV formatting is gone. Spott now generates March's candidate reports and reformatted CVs in their own branded templates, one per search type, refined with Spott's team until they were right. As one of the team put it in a recent session: "We're happy with how they've been formatted, so we don't have to use the other company anymore."
- Deep-dive interviews feed everything. Interview transcripts and intake notes live on the system, so reports and matching draw on what candidates actually said, not just what their CV claims.
- One inbox, all channels. Email, LinkedIn, and WhatsApp sync into the candidate record, with personal messages kept fully private per user.
- The whole team works one system. Spott's customer success team runs training cohort by cohort as March brings people on, and the firm's operating rule is the one Charles set himself: get all the relevant information onto the system, because that is what makes the AI useful.
That last point is the real lesson of this case study. March Consultants did not buy magic. They bought a platform that rewards good data discipline with matching and automation that actually work, and then they put in the discipline.
Tired of CRM promises that never ship? See matching built for executive search. Book a demo.
Frequently Asked
Yes. Spott generates candidate reports and reformatted CVs in your own templates, with a separate template per search type if you want one. Reports draw on the CV, interview transcripts, and notes already in the platform, and export as editable PowerPoint or Word files, so consultants always keep the final say.
Accuracy tracks data quality more than model choice. On a database where calls and messages are captured automatically, contextual matching routinely surfaces qualified candidates keyword search misses; on a database of stale CVs, every engine underperforms. Evaluate any vendor by running your own hardest live role through their matching, not a demo dataset.
No, and it shouldn't: under GDPR and emerging US rules, auto-rejecting candidates without human review is where legal exposure concentrates. Good systems rank and explain; the recruiter decides. The win is compressing the find-and-rank phase from hours to minutes, not removing the human.
Outp(l)ace everyone.
You can’t win tomorrow’s placements
with yesterday’s tools.
