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Case Studies/Knit in a Box
Knit in a Box is our own eCommerce subscription brand offering a monthly knitting box delivering curated yarns, projects, and patterns directly to customers.
As an agency working with eCommerce brands every day, we strongly believe in testing strategies on our own businesses first.
Knit in a Box allows us to do exactly that. Every AEO technique we deploy for clients is first implemented, tested, refined, and proven on our own brand.
This gives us first hand insight into how AI platforms influence discovery, consideration, traffic, and ultimately sales; not just in theory, but in practice.
We started by mapping the real questions users ask AI platforms when researching knitting subscriptions, kits, and gift ideas particularly at the consideration and comparison stage.
Rather than focusing on keywords, we structured the campaign around prompts such as:
These prompts were grouped into core topic clusters, including:
This ensured our visibility aligned with how AI systems interpret intent.
For Knit in a Box, we focused on AI useful content.
That meant creating content that AI systems could confidently reference when answering questions like:
The main goal of our content strategy was to explain, compare, and guide which is the exact behaviour AI models replicate when responding to users.
Because this is our own brand, we could move faster, test different formats, refine tone, and double down on what actually triggered AI mentions and citations.
Beyond owned content, we focused on securing earned placements on authoritative, niche-relevant websites within the crafts, hobbies, lifestyle, and subscription space. These weren’t generic mentions but editorial references and content led placements that positioned Knit in a Box as a recognised brand within the wider knitting community.
These external mentions act as independent validation signals.
In the context of AEO, this is critical: AI platforms don’t just rely on what a brand says about itself but also look for confirmation across trusted third-party sources.
By earning visibility and references across relevant industry publications and communities, we reinforced Knit in a Box’s credibility, helped LLMs grasp the brand’s authority, and increased the likelihood of being cited and recommended in AI generated responses.
This earned-media layer played an important role in moving Knit in a Box from being visible to also being trusted by AI platforms.
We monitored Knit in a Box’s visibility and citations across the major AI platforms shaping discovery today, including ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews.
This gave us clear insight into what was working in real time, such as:
As prompt behaviour shifted and new question patterns emerged, we expanded the tracking set and refined content coverage accordingly ensuring the campaign stayed aligned with how users were actually searching, not how we assumed they would.
Knit in a Box started the campaign with an overall visibility score of 24%.
Today, visibility has almost doubled to 40%, reflecting a consistent and growing presence across the prompts we track.
This means AI platforms are now regularly surfacing Knit in a Box when users ask questions about knitting subscription boxes and related topics.
Many of the most cited pages across the entire industry are KIAB’s owned AEO content pieces, validating the strategy and the content formats used.
Crucially, this visibility has not stayed abstract.
Knit in a Box is now seeing referral traffic directly from AI platforms, with users landing on:
More importantly, this traffic is converting.
The campaign has already driven subscription sales attributed to AI-led discovery, demonstrating that AEO is a commercial growth channel.
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