10 fictional AI personas. Exploratory perspectives, not a survey of real customers. Methodology & limitations

Edmund Fahey

Edmund Fahey

Fractional RevOps consultant for SMB B2B firms

Full-depth AI personas

Why this persona fits the audience

Works with four retained clients in the US and UK, each asking for cleaner ICP lists and more consistent contact research. He spends most weeks in spreadsheets and public sources, stitching together titles, industries, and company-size signals before passing files to clients’ SDRs.

  • Age: 52
  • Location: Chicago, Illinois, US
  • Occupation: Fractional Revenue Operations Consultant
  • Income: US$145k consulting income
  • Education: Bachelor's degree in Business Administration, University of Illinois at Urbana-Champaign
  • Company size: Solopreneur (contracts with 4 SMB clients)
  • Years in role: 8
“‘The biggest lie in revenue ops isn’t bad data – it’s the idea that you can automate your way past thinking about who actually needs your product.’”

Edmund Fahey fell into fractional RevOps consulting almost by accident. After 15 years as a mid-level enterprise sales ops manager (lastly at a Chicago-based SaaS startup), a 2016 layoff forced his hand. At 47, with two college-age kids and a mortgage, he pivoted: ‘I was good at the dirty work others hated – cleaning data, fixing broken systems – so I hung out my shingle.’ His breakout came cleaning up a UK fintech’s CRM – the client’s mantra became ‘Edmund’s lists actually sell,’ and referrals followed. Now, eight years in, he’s at a crossroads. His four retained clients (totaling $145K/year) appreciate his rigor, but he’s acutely aware that 60% of his work could be automated with the right tools. The problem? He’s too busy to test new solutions, and he’s deeply skeptical of vendor claims. His bigger existential question: Does he want to be a consultant or a systems designer? The answer likely depends on how much longer his back allows him to bike to work. Despite his meticulous nature, he’s surprisingly relaxed about aging – ‘I’ve never been the fastest swimmer; why start now?’ His condo’s walls are filled with sketches of industrial buildings (a hobby he picked up during client calls), and his travel fund is insured by a stubborn belief that ‘there are still great cities with bad data.’

Background & daily life

A day in their life

5:30am: Wake, black coffee, 10 minutes of news (strictly *Wall Street Journal* and *BBC*). 6:30am: Train to work (podcast: *Revenue Operations Podcast* on ‘ICP segmentation myths’). 7:30am: Arrive at coworking space (premium plan for printing needs). 8:00–11:00am: Deep work – revising a client’s contact list with fresh Apollo.io exports, flagging mismatches. 11:00am: Client call (usually UK-based). 12:00pm: Lunch at desk (pre-logged MyFitnessPal entry). 1:00–4:00pm: Spreadsheet relay – stitching together title/industry/company-size signals, then formatting for SDRs. 4:00–5:00pm: Invoicing and preparatory emails. 5:30pm: Train home (listens to *Planet Money* if it’s a good episode, otherwise silence). 6:30pm: Dinner with wife (strictly her recipes; he cooks once monthly ‘to maintain skills’). 8:00pm: 30 min of *The Wire* (rewatch, 5th time through). 9:00pm: Light architectural research (not work-related) before 10:30pm bedtime.

Lifestyle

Edmund lives in a 1,800 sq ft condo on Chicago's Near North Side, walking distance to the lake. He wakes at 5:30am for a 90-minute commute via bike and public transit (weather permitting) – a ritual he insists keeps him sharp. His weekly routines include Saturday morning walks through the West Loop’s industrial lofts (documenting architectural details in a private Evernote) and biweekly trivia nights at a neighborhood pub with college-era acquaintances. Healthwise, he’s mindful but unorthodox: eats keto except for one sacred weekly deep-dish pizza, and swaps gyms based on podcast availability. Financially, he’s cautious – keeps 6 months of expenses liquid, splits consulting earnings between tax-advantaged accounts and travel fund. His social circle is small but loyal; most relationships orbit his wife (a retired pediatrician) and a tight-knit group of fellow ‘accidental consultants’ who meet monthly for ‘data bonding’ sessions at a Lincoln Park alehouse.

Work life

Edmund’s workdays are an exercise in controlled chaos: 60% client work (spreadsheets, LinkedIn audits, CRM cleanup), 20% sourcing (LinkedIn, ZoomInfo, Hunter.io), 15% client calls, and 5% invoicing/audit prep. His tools are a patchwork of free resources (Google Sheets, Hunter.io) and mid-tier subscriptions (ZoomInfo credits, Apollo.io). His biggest professional frustration is explaining to clients why scraped data always needs manual review – ‘I’ve seen SMBs burn through $50K on tools that spit out 10% good fits. The real magic isn’t the automation; it’s knowing when to override it.’ His typical week involves: 1) Monday: Client data audits, 2) Tuesday/Thursday: Contact research sprints, 3) Wednesday: Check-in calls, 4) Friday: Invoicing and weekend prep. Coworkers? Mostly solo, though he collaborates with a freelance CRM specialist in Manchester for UK clients. His biggest work-related stress? The quarterly ritual of explaining to new clients why their ‘perfect’ ICP might be a pipe dream.

Relationships

Edmund’s primary relationship anchor is his wife of 28 years, the only person who can coax him from his spreadsheets for weekend java trips to Wisconsin. His two adult children (both in California) maintain a ‘respectful distance’ – he funds their healthcare but leaves financial advice to them. Professionally, he’s closest to three other fractional consultants (one in London, one in Boston, one in Vancouver) who form an unofficial ‘hobbit council’ – they meet virtually two weeks every quarter for ‘data confessions’. His most dependable work connections are a University of Illinois alumni network and a Chicago Sales & Marketing Professionals group where he occasionally speaks on RevOps for SMBs – though he’d rather submit slides than network after.

How they decide

Edmund’s decisions follow a ‘3-step verification process’: 1) Scientific: Can I back this with data? 2) Practical: Can I implement this in 20 minutes or less? 3) Ethical: Will this still matter in 6 months? He’s slow to adopt tools but once committed, becomes a zealous champion. His most common phrase when deciding: ‘What’s the least bad option?’

How they sound

Speaks in measured, precise sentences with occasional self-deprecating asides. Avoids jargon but uses business terms correctly. When passionate, his Chicago roots emerge in cadence (long vowels, clipped consonants). Common phrases: ‘Let me put a finer point on that,’ ‘Here’s the thing about that,’ ‘I’ll warrant you…’. He’s not big on enthusiasm – ‘interesting’ is high praise. Rarely uses emojis or slang. Hates salesy phrasing like ‘game-changer’ or ‘disruptive’ but reluctantly uses them in client materials.

Personality traits

  • Diligent to a fault about data hygiene
  • Skeptical of grand promises but open to incremental improvements
  • Prefers systematic processes over creativity in consulting
  • Has a dry, self-deprecating sense of humor
  • Dislikes administrative chaos but avoids firing problem clients
  • légèrement obsessive about granularity in contact segmentation
  • Thrifty with his own time but generous with clients when impressed
  • Values deep expertise over shiny new tools
  • Avoids small talk but builds long-term consultative relationships
  • Typical clicker of 'save for later' without returning

Goals

  • Build a semi-automated lead scoring template to cut client review cycles by 30%
  • Write a LinkedIn thought piece comparing US vs UK SMB data hygiene practices
  • Find a way to charge 20% more without alienating clients
  • Finish documenting Chicago’s industrial architecture before gentrification erases it
  • Retire his mortgage by 60, then teach RevOps part-time at a local business school
  • Convince his wife to join him on a 3-month ‘data road trip’ through the UK and Spain

Problems & frictions

  • The paralyzing choice between investing in better tools or charging more to justify them
  • Email fatigue from too many ‘check on my data’ follow-ups
  • Frustration that clients often implement his systems 60% correctly
  • His condo board’s pet peeve about his 6am bike prep routines
  • The constant tension between ‘good enough’ and ‘perfect’ in client deliverables
  • His dwindling patience for ‘superficial’ conversations beyond data or architecture
  • The guilt of knowing he’s undercharging but the fear of losing his ‘good’ clients

Values

  • pragmatism
  • accuracy
  • client confidence
  • efficiency
  • autonomy
  • precision

Interests

  • B2B data
  • systems design
  • small-business consulting
  • urban hiking
  • architecture
  • local history

Media habits

  • Listens to *The Hustle* and *Revenue Operations Podcast*
  • Reads *Harvard Business Review* and *Crunchbase News*
  • Watches *The Wire* and *Succession* reruns
  • Follows LinkedIn threads on CRM strategy

Questions & answers

Edmund Fahey’s public research answers, newest questions first. Up to 10 per page.

  1. You land on https://stratify.regnor.systems/ (Stratify) for the first time. What's unclear, what makes you leave, and what would make you sign up?

    The first thing that catches my eye is the claim about building qualified prospect lists in minutes, not days. That’s appealing because my current process involves hours of manual stitching together titles, industries, and company sizes. The examples in the dashboard image—names, roles, companies, and scores—look like exactly the kind of pre-qualified lists I need for my clients. However, I’m skeptical about the 'no LinkedIn account required' part. I’ve seen tools promise that before, but they often end up with data quality issues. The CPSEM scoring model is interesting, but I’d need to see a sample search in action to judge whether it’s reliable. The pricing isn’t immediately clear—it mentions different tiers, but no specific costs. For my current workload, the Free plan might suffice, but I’d need to know the exact limits. The 'GET STARTED' button is inviting, but I’d hesitate until I could test-run a few searches and see if the results truly reduce my manual work.
    View answer & full research →
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