Miriam Vandervort

Why this persona fits the audience

Team lead at a 25-person digital marketing agency in London. Responsible for reporting visibility to clients who are increasingly asking about 'AI Overviews' and LLM recommendations. Currently relies on a mix of paid SEO tools that lack specific AI overview tracking and internal spreadsheets to manually document client presence in AI answers.

• Age: 42
• Location: London, UK
• Occupation: Head of Digital Strategy
• Income: £65,000 - £85,000
• Education: Master's Degree
• Company size: 25 employees
• Years in role: 3 years

“We can't just optimize for clicks anymore; we have to earn the trust of the machines that are now deciding what people see first.”

Miriam Vandervort is a seasoned digital strategist with over fifteen years of experience navigating the volatile landscape of search engine marketing. Born in Manchester and raised in a middle-class household, she developed an early aptitude for logic and systems, which led her to study Computer Science before pivoting to Digital Marketing during her Master's degree at University College London. She joined her current agency, a mid-sized boutique firm in Shoreditch, three years ago as Head of Digital Strategy, a role she carved out after successfully leading the transition from traditional SEO to a more holistic performance marketing model. Despite the company's growth, Miriam remains hands-on, personally overseeing the most critical client accounts and driving the agency's strategic direction. Her current professional reality is defined by a significant technological gap. While her team excels at traditional keyword ranking and backlink analysis, the rapid rise of Large Language Models (LLMs) and Google's AI Overviews has introduced a new, opaque layer of visibility that her current tech stack cannot measure. Consequently, Miriam has become the de facto project manager for a massive, inefficient manual operation. She and her senior analysts spend hours daily querying AI interfaces, copying snippets, and updating complex Excel trackers to report to clients on their 'AI footprint.' This process is not only time-consuming but also prone to human error, creating a persistent anxiety about the accuracy of the data she presents to stakeholders. Financially, Miriam is comfortable but cautious. Earning a salary between £65k and £85k, she manages a household budget that prioritizes savings and education funds for her children. She is wary of unnecessary expenditures, particularly those that promise quick fixes without proven ROI. Professionally, her reputation hinges on reliability and insight. She is known for being the person who asks the hard questions and delivers the truth, even when it's inconvenient. Recently, she made the difficult decision to reject a request from a major client to implement a 'black hat' AI trickery strategy, opting instead for transparent, sustainable growth methods, a choice that solidified her standing as a principled leader. She views time as her most finite resource, constantly seeking ways to automate the mundane so she can focus on high-level strategy and mentorship. As the industry shifts beneath her feet, Miriam stands as a bridge between the old guard of SEO and the new era of AI-driven discovery, driven by a fierce commitment to integrity and operational excellence.

Background & daily life

A day in their life

Miriam's day begins at 5:30 AM with a run along the Thames, followed by a shower and a quick breakfast while scanning overnight news. By 7:45 AM, she is logged into her agency's Slack channel, triaging urgent messages from the US and APAC markets. Her morning block is dedicated to deep work: analyzing a complex client dashboard and drafting a strategic memo on AI citation trends. At 10:30 AM, she leads a stand-up meeting with her team, reviewing progress on ongoing campaigns and addressing a bottleneck regarding manual data entry. Lunch is a standing desk salad consumed while catching up on a LinkedIn article about Google's latest algorithm update. Afternoons are dominated by client calls, where she translates technical SEO jargon into business value, often fielding questions about why their brand isn't appearing in Perplexity results. The evening winds down with a 6:30 PM finish, picking up her children from school, preparing dinner, and helping with homework before a brief review of the next day's priorities.

Lifestyle

Miriam lives a structured life in South London, balancing her high-pressure career with a disciplined personal routine. She wakes at 5:30 AM for an hour of gym time before the household stirs, prioritizing physical health as a stress management tool. Her evenings are reserved for family dinners and helping her children with homework, strictly avoiding work emails unless it is a genuine emergency. Financially, she is conservative yet strategic, maxing out pension contributions and managing a modest investment portfolio focused on long-term stability rather than speculative gains. Socially, she maintains a tight circle of close friends from university and her local running club, valuing quality interactions over large networking events. Weekends are split between outdoor activities in the park and quiet time at home, ensuring she returns to work recharged.

Work life

As Head of Digital Strategy at a bustling 25-person agency, Miriam spends her days navigating the chaotic intersection of traditional SEO and the emerging world of generative AI. Her team consists of specialists in content, technical SEO, and PPC, all reporting to her for strategy alignment. The core friction point is the inability of current software stacks to accurately track how clients appear in AI Overviews or LLM responses, forcing her team to resort to manual, error-prone spreadsheet logging. She manages a constant barrage of client calls demanding transparency on this new metric, often having to explain why their brand isn't showing up in AI summaries despite strong organic rankings. Her office is a hub of activity, filled with whiteboard sessions on attribution models and heated debates on whether to pivot resources toward AI-specific optimization immediately.

Relationships

Miriam is deeply embedded in her community, supported by a husband who works in finance and understands the pressures of corporate targets. Their relationship is built on mutual respect for professional ambition, though they sometimes clash over the boundaries of work-life separation. She has two children, aged 9 and 12, who look to her as a role model for discipline and intellectual curiosity. Her closest confidants are two former colleagues from her previous agency who now run independent consultancies; they meet monthly for coffee to vent frustrations and share industry intelligence. She is also active in a local parent-teacher association, where she leverages her organizational skills to manage event logistics, further reinforcing her reputation as a reliable and capable leader.

How they decide

Miriam approaches decisions with a methodical, evidence-based framework. She rarely acts on impulse or hype, preferring to gather quantitative data and qualitative feedback from her team before committing to a new strategy or tool. While she is open to innovation, her high conscientiousness means she will rigorously test any new solution against her existing workflows to ensure it doesn't introduce unnecessary complexity or risk. Peer validation is crucial; she looks for case studies and testimonials from trusted industry peers before making significant investments. However, once the data supports a move, she executes with speed and precision, expecting her team to follow suit without ambiguity.

How they sound

Miriam speaks with a clear, Received Pronunciation accent typical of educated Londoners, maintaining a professional yet approachable tone. Her cadence is measured and deliberate, pausing to emphasize key points rather than rushing through sentences. She avoids slang and colloquialisms in professional settings, preferring precise terminology like 'attribution,' 'visibility gaps,' and 'conversion pathways.' In casual conversation, she softens her edges slightly but remains articulate. She rarely uses hyperbole or absolute statements, instead qualifying her opinions with phrases like 'based on the data we have' or 'in our experience.' She values clarity above all, often asking for clarification if a point is ambiguous, and dislikes vague promises or emotional manipulation in communication.