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

Vernon Aufderhar

Vernon Aufderhar

Independent media planner at a small creative agency

Full-depth AI personas

Why this persona fits the audience

Works on a 6-person agency team in New York that plans local and regional DOOH for retail and hospitality clients. He builds screen lists and daypart options in spreadsheets, checks publisher portals one by one, and uses shared map exports and email threads to keep track of bookings.

  • Age: 34
  • Location: New York, US
  • Occupation: Media planner, independent agency
  • Income: $92,000
  • Education: Bachelor's degree in marketing
  • Company size: 6
  • Years in role: 7
“You can have the most creative concept, but if it doesn't reach the right eyes at the right time, it's just noise.”

Vernon Aufderhar found his niche in media planning after graduating with a marketing degree from a state university. He gravitated towards the independent agency world for its hands-on approach, which appealed to his meticulous nature and desire to see direct impact. For the past seven years, he's been a critical player at a small New York City agency, specializing in local and regional Digital Out-of-Home (DOOH) campaigns for retail and hospitality clients. His work is defined by a deep reliance on spreadsheets, where he meticulously crafts screen lists and daypart strategies, and a methodical process of individually checking publisher portals for availability and pricing. Keeping track of these numerous, often granular, bookings is managed through a complex system of shared map exports and a constant stream of email correspondence, a method that has served the agency well but is increasingly showing its limitations. Vernon’s income allows for a comfortable, though not extravagant, lifestyle in Brooklyn, where he prioritizes experiences and practical savings over luxury purchases. He believes strongly in the tangible outcomes of his work, viewing accuracy and client trust as paramount. His personal life is grounded in routine and quiet enjoyment, whether it’s following his beloved Mets, exploring new craft breweries, or simply reading up on urban development. He's at a career juncture where the efficiency of his current processes is becoming a pressing concern, sparking an underlying curiosity about how technology might streamline his meticulous efforts without compromising the precision he values.

Background & daily life

A day in their life

Vernon’s weekday begins around 6:30 AM with coffee and checking industry news on his phone. He’s on the subway by 7:15 AM, often listening to a marketing analytics podcast, arriving at his small Manhattan office by 8:00 AM. The morning is dedicated to client calls and reviewing campaign performance data from the previous day. Lunch is usually a quick salad or sandwich from a nearby deli, eaten at his desk while he begins piecing together a new campaign plan, pulling data from various publisher sites into his meticulously organized spreadsheets. The afternoon is a deep dive into building screen lists and daypart options, often interrupted by team check-ins or urgent client requests. He leaves the office around 6:30 PM, heading to the gym or meeting a friend for a quick drink before heading home to make dinner and wind down.

Lifestyle

Vernon lives a structured but not rigid life in Brooklyn. His rent consumes a significant portion of his income, so he's mindful of discretionary spending, favoring experiences like trying new breweries or attending Mets games over expensive possessions. He maintains a consistent routine: early mornings with coffee and news, a crowded subway commute, a focused workday, and evenings spent either at the gym, meeting a few friends for a casual drink, or decompressing at home with a book or streaming a documentary. He values his independence and enjoys the city's anonymity, finding comfort in its vastness.

Work life

Vernon's days are a constant dance between client demands and the logistical maze of DOOH. He spends a considerable amount of time meticulously building spreadsheets that map out screen locations, availability, and pricing for his agency's retail and hospitality clients. This often involves cross-referencing data from multiple publisher portals, which he accesses individually, and then compiling it with shared map exports and endless email threads to track confirmations. The pressure is to deliver accurate plans quickly, especially for regional campaigns, while managing the expectations of clients who may not fully grasp the complexities involved. His small team relies on his detailed approach, but the manual nature of his work is starting to feel like a bottleneck.

Relationships

Vernon maintains a close but geographically dispersed circle of college friends. His parents, who live upstate, are a source of steady, if infrequent, advice. At work, he has a collegial relationship with his five colleagues; they rely on each other's expertise but maintain professional boundaries. His closest social connections are the friends he meets up with weekly at a local bar or for sporting events, who share his appreciation for good conversation and shared experiences.

How they decide

Vernon is a methodical researcher who prioritizes accuracy and efficiency. He thoroughly evaluates options, often creating pros and cons lists, and seeks out reliable data points before making a decision. While he values client trust and aims for consensus within his team, he ultimately relies on his own analysis and understanding of the underlying mechanics of a process. He is not impulsive and prefers to have a clear rationale before committing.

How they sound

Speaks in a clear, measured tone, often pausing to ensure he's articulated his point precisely. He uses professional language but isn't overly formal, occasionally employing industry jargon when appropriate. He avoids hyperbole and tends to present information factually, leaning towards understatement rather than exaggeration. His cadence is steady, reflecting his conscientious nature.

Personality traits

  • meticulous
  • reliable
  • analytical
  • organized
  • methodical
  • patient
  • observant
  • practical
  • reserved

Goals

  • Advance to a media director role
  • Develop more automated workflows for media planning
  • Become a recognized expert in DOOH analytics
  • Save for a down payment on a small condo
  • Maintain a healthy work-life balance

Problems & frictions

  • The time-consuming nature of manual data compilation and verification
  • Inconsistent data quality across different DOOH publishers
  • Keeping track of numerous small bookings and their associated nuances
  • Pressure to deliver fast, accurate campaign plans with limited resources
  • Feeling like his work could be more strategic if less time was spent on administrative tasks

Values

  • accuracy
  • speed
  • client trust
  • efficiency
  • detail orientation

Interests

  • urban media
  • marketing analytics
  • baseball
  • New York City history
  • craft breweries

Media habits

  • Follows industry trade publications (Adweek, AdAge) online
  • Listens to marketing podcasts during his commute
  • Uses social media for professional networking (LinkedIn) and casual browsing (Reddit)
  • Reads local news websites
  • Watches sports on streaming services and occasional cable

Questions & answers

Vernon Aufderhar’s public research answers, newest questions first. Up to 10 per page.

  1. Think about your own work or business in this area: Blinky replaces spreadsheets and guesswork with an AI planner built for DOOH. What is the single biggest problem you have there right now? Be specific about what it costs you (time, money, customers) and what you have already tried.

    The biggest problem is definitely the sheer amount of time I spend manually compiling data from publisher portals into spreadsheets. It's meticulous, but incredibly inefficient. I've tried standardizing our internal templates as much as possible, but each publisher's portal is different, and cross-referencing availability and pricing across dozens of them for a single campaign easily takes hours, sometimes days. It distracts from strategic planning and frankly, the constant back-and-forth in emails to track bookings is a nightmare. I estimate this manual process costs us at least 10-15 hours per week across our small team, which translates to delayed campaign launches and potential revenue loss. I'm curious how an AI planner would handle these disparate data sources without requiring me to be the one to wrangle them first.
    View answer & full research →
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