How myPOS got AI-search ready across 4,000 content pieces with Demand Genius

myPOS had built a serious organic search operation over years, with around 10,000 URLs, 4,000 unique pieces of content in its library and substantial organic traffic the business depended on. AI search was putting that investment under a new kind of pressure.

Acting without a clear picture of how AI systems were treating the brand meant making decisions on assumption rather than evidence. With this much organic traffic at stake, that wasn’t a position they could be comfortable with.

The scale made the challenge more complex. On paper, they had a content library of around 10,000 pages, built through years of consistent publishing. Once legal pages, sign-up flows, pagination and structural URLs were separated out, the real content footprint was still around 4,000 pieces that needed assessing and acting on.

There was also clear internal awareness that content debt had built up over time. The content was well-optimised, created by teams doing the right work in a search-first environment. But that was exactly the issue. The content had been built for a world where search behaviour, rankings and performance signals were easier to read. AI search made the picture less clear.

myPOS didn’t have a clear view of how AI systems were representing the brand, where they were visible, or which pieces of content were actually being surfaced. A manual audit of thousands of pages would take months and be out of date before it landed.

The real challenge was understanding a business-critical content estate well enough to decide where to focus. They needed a way to see what was happening, where the gaps were, and what needed attention first.

myPOS needed a way to assess the full content estate quickly, against the criteria that matter in the AI era, then turn that evidence into a plan that made sense for their business.

Scoring the full content footprint

Our content intelligence agents scored every relevant myPOS URL against the Demand Genius audit framework. The analysis covered five dimensions and twenty attributes per piece.

The AI-led analysis did the heavy lifting overnight. That mattered because myPOS had thousands of pages to work through, and the team needed a full picture before deciding where to focus.

Turning scores into strategy

The real work was human. That meant capturing myPOS’s ICP, positioning, competitive context and strategic priorities. It also meant understanding which parts of organic search were working, what value the team had already built, and what AI search now required. The goal was to decide what needed to be kept, improved, refreshed or reviewed for removal, in the right order.

The audit also benchmarked myPOS’s content against the patterns we see across our wider research into AI search behaviour, citation dynamics and content performance. A score is useful, but it becomes much more useful when you can compare it with the kind of content AI systems tend to cite and surface.

myPOS’s content was genuinely well-optimised, built through years of teams doing the right work in a search-first world. Search-era content was designed to concisely answer common questions, and it did that well. Information Gain wasn’t part of that equation. But even the strongest pieces in the library averaged only 1.05 out of 2 on it. Information Gain measures whether a piece gives AI systems and readers something they can’t get elsewhere, and that’s now a core requirement for being cited and surfaced.

The finding gave the work a clear direction: move from well-optimised content towards genuinely differentiated content, while protecting the search value already in place.

myPOS came away with a tactical workbook covering around 4,000 pieces of content. Each URL had a clear recommendation: keep, improve, refresh or review for removal. That gave the team something practical they could work through themselves.

Alongside that, we built a strategic gap analysis showing where the bigger content opportunities sat. This covered narrative ownership, information gain, authority signals and seven net-new commissions that filled strategic gaps the audit revealed in their content library.

We then sequenced the work into a 12-month roadmap. The roadmap was designed to lift differentiation progressively, while reflecting real-world constraints on capacity. It gave myPOS a way to improve the content estate in stages, with the highest-priority work first.

The audit became the entry point into a live system. Through the Demand Genius platform, myPOS can now monitor qualitative KPIs continuously.