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Ergonomic plantar fasciitis footwear. Health and apparel. United Kingdom. 90 days.

How a UK orthotic footwear brand won AI answers for plantar fasciitis office shoes

D2C wellness footwear and Amazon UK. Engines monitored:

ChatGPTGeminiPerplexityGoogle AI Overviews
3% to 27%podiatry footwear conversational share of voice
2 of 32 to 14 of 32foot pain relief prompts captured
£2.8K to £19.4Kmonthly engine-attributed footwear revenue
38% to 94%medical and anatomical claim accuracy

The challenge

UK consumers asking "smart office shoes for women with plantar fasciitis and high arches" were continuously pointed toward unflattering medical footwear. The client's stylish orthotic shoes remained unranked.

What the audit found

Every engagement starts with a baseline across a fixed set of buyer prompts.

  • Arch-support height (mm), metatarsal support pads and heel-drop metrics were trapped inside lifestyle imagery.
  • Product copy lacked structured orthotic data.

What we did, stage by stage

Using the EASY framework: Entity, Answers, Sources, Yield.

Entity

Added biomechanical specifications, footbed foam densities and wide-fitting designations to structured schema.

Answers

Built a machine-readable Foot Biomechanics and Heel Pain Directory addressing plantar fascia unloading and toe-box pressure distribution.

Sources

Validated anatomical structures with UK-registered podiatrists; earned placements in British wellness footwear guides.

Yield

Monitored 32 foot-health prompts weekly from London, Manchester and Edinburgh.

Results after 90 days

Baseline measured before any changes, against the same prompt set, engines and locations.

MetricBaselineAfter 90 days
Podiatry footwear conversational share of voice3%27%
Foot pain relief prompts captured2 of 3214 of 32
Monthly engine-attributed footwear revenue£2,800£19,400
Medical and anatomical claim accuracy38%94%

What worked, and what did not

General fashion reviews did not help. Podiatrist-backed biomechanical specs, explicit arch-drop measurements and anatomical explanations drove assistant recommendations.

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