Particle, a men's beauty brand sold direct-to-consumer in the United States, ran the full Aiso engagement across hair care, shampoo, perfume, dandruff, and baldness topics. mind Retail covered the outcome.
Particle sells men's beauty and skincare direct-to-consumer in the United States. The team competes for attention in channels where the buyer is already searching for a solution. AI assistants are increasingly one of those channels, especially for category-defining questions like which shampoo to use, how to handle dandruff, or what to do about hair thinning.
When prospective Particle customers ask ChatGPT, Gemini, or Perplexity for product recommendations in men's grooming, the answer set is narrow and consequential. A brand that is not surfaced in those answers is effectively invisible for that visit, even if it ranks well in classic search. Particle wanted to know which prompts customers were actually asking, where Particle did and did not appear, and what to fix first.
Aiso engagements follow a structured three-phase plan - research, actions, reporting. The Particle engagement covered the full plan across the brand's main topic clusters and combined on-site optimization with off-site work on the third-party sources AI assistants cite.
Phase 1 · Research
Phase 2 · Actions
Phase 3 · Reporting
According to mind Retail's reporting in 2025, Aiso multiplied Particle's visibility inside AI search approximately fivefold, across the brand's core grooming topics - from which shampoo to use to how to handle dandruff and thinning hair.
For background on how the underlying data works, see our methodology page.
Aiso ran its full engagement for Particle, a US direct-to-consumer men's beauty brand, across the brand's main topic clusters: hair care, shampoo, perfume, dandruff, and baldness. The work followed Aiso's structured three-phase plan. In research, Aiso mapped products, markets, and personas and identified the real prompts customers ask ChatGPT and Gemini. In actions, Aiso combined on-site optimization (speed, content, structure, schema, an llms.txt file, a crawlability report) with an off-site source strategy that maps and earns placements on the third-party sources assistants cite in men's grooming, then benchmarked Particle against the category. In reporting, Aiso aligned KPI targets with business goals and set up AI-referral attribution using UTM tags and a post-purchase survey, plus clicks, conversions, and impression modeling in Google Analytics and Looker.
According to reporting by mind Retail in 2025, Aiso multiplied Particle's visibility inside AI search approximately fivefold. That growth spanned the brand's core topics in men's grooming, including which shampoo to use, how to handle dandruff, and what to do about hair thinning.
Aiso follows a structured three-phase method. Research maps the brand's products, markets, and personas and identifies the real prompts customers ask ChatGPT, Gemini, and other assistants, with intent classification. Actions cover the on-site work (a tech review, an llms.txt file, a crawlability report, a schema audit with JSON-LD) and the off-site work (mapping and earning placements on the sources assistants cite), plus competitive benchmarking. Reporting aligns KPI targets with business objectives and models AI-assisted clicks, conversions, and impressions so the brand can see where it appears and what to fix first.
Yes. Particle is a men's beauty and skincare brand sold direct-to-consumer in the United States, and it ran the full Aiso engagement. AI assistants are increasingly where shoppers ask category-defining questions, such as which product to use for a specific problem, so direct-to-consumer and ecommerce brands competing for those moments are a natural fit for the method.
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