She ran the ads before she wrote the articles. Now her content marketing framework is built for the AI-search era.

Pia Mikhael’s job was spending other people’s money. As a freelance media buyer, the British marketer was hired by companies to run their advertising on platforms like Facebook and Google: choosing what ads to show, who to show it to, and how to distribute budget. Done well, the client acquired new customers at a profit. Done poorly, the budget was gone within a week with nothing to show for it.

In early 2022 she read a blog post advising marketers on configuring their Facebook advertising accounts. Two paragraphs in, she suspected the writer had never actually run a campaign before. The author had confused two settings in Facebook’s ad manager that control how an advertising budget gets divided. A small distinction on screen; an expensive one in practice. It wasn’t the first time. Juggling clients across multiple industries, she read industry blogs constantly, and the more campaigns she ran, the more often the advice read as though it had been written at a distance from the work itself. So naturally, when the advertising analytics platform Triple Whale invited her to contribute to their blog, she jumped on the opportunity. It was a chance to write about campaigns from firsthand experience.

The article was about a Facebook ads setting called cost caps, which lets advertisers set the most they will pay to win a single customer. The obvious piece any generic content writer would have written was an explanation of how to enable the feature. Instead, Mikhael told readers to leave the setting alone until they had fixed their advertisements themselves — because the words and pictures in an ad matter far more than any budget setting does. Triple Whale came back for another article. Then another. Eight in total. It was not a business yet, but it was a signal, and the signal was not just that she wrote well. It was that she had actual experience running the campaigns she wrote about. That was reproducible, and, at the time, few others were building a service around it.

The default path in marketing software content was familiar to anyone who had been in the industry: hire a generalist writing agency and receive polished articles that often stopped short of practical, hands-on advice. The economics could be hard to justify. A software company would pay an agency for 20 articles per month, watch them rank in search engines, and count that alone as a win. What was rarely measured was whether any of it produced customers. Buyers arrived, read advice that was well written but hard to act on, and left. The budget was spent and the dashboard looked healthy, yet the sales pipeline often stayed thin. Because individual pieces of content were rarely tied to a revenue number, it was difficult to prove whether the exercise was working at all.

Mikhael spent four years as a freelance media buyer and in multiple agency roles, building funnels and managing ad spend. Months after she wrote that first set of articles for Triple Whale, she founded Saasy Media on a discovery she had made the hard way: the people writing about how to run marketing campaigns should have run marketing campaigns themselves. At the time, few were.

Writers who have done the job

Mikhael’s approach represents a shift in how content gets made in the B2B SaaS world. Instead of generalist writers, her own operator expertise anchors every piece. The result, she says, is content that resonates with readers because it comes from lived experience.

Content with a number attached to it

The second half of her framework comes straight from Mikhael’s media-buying years. Every asset has a job and is tied to a metric, the way an ad campaign does. Educational playbooks are lead engines. Case studies are sales tools. Editorials are search assets. Nothing gets created without an answer to what metric it is supposed to move. This framing is what lets content be treated as a performance channel rather than defended like a branding exercise.

The results her clients point to are specific. According to Social Snowball, an influencer marketing platform, a gated playbook campaign Mikhael ran for the company produced more than 1,500 leads and over $180,000 in sales pipeline in under a month — where earlier campaigns, the company says, had rarely generated more than 100 leads. Zach Murray, founder of ad creative research platform Foreplay, says one of her campaigns “generated over 400 leads and $140K in pipeline in 19 days”.

Adapting to the AI-search era

Mikhael’s framework predates the industry’s current turn. When AI platforms began answering the questions that once sent readers to generic blogs, expertise-led content moved from a nice-to-have to a priority for many marketing teams — because the sources AI engines keep citing are the ones with demonstrable expertise behind them. A Princeton-led study presented at KDD 2024 found that content grounded in citations, quotations from relevant sources, and statistics was over 40% more visible in AI-generated answers — precisely the kind of substantiation, Mikhael says, that operator-written content produces naturally, and that Saasy Media built into its workflows from the start. Mikhael argues that agencies and content teams that optimised for generic content spent 2025 rethinking their strategy, while her clients were already positioned for the shift.

She now teaches the model publicly, through keynotes such as her talk at Techtonic 2025 in Toronto and frameworks published on her LinkedIn. Mikhael says more than 100 software companies have approached her in the past year about implementing her strategies. The pitch has not changed since she founded the company: when an operator searches for how ad attribution works, or how to run an affiliate program, the answer they read should have been written by someone who did the thing first.