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AI Recommendation Footprint

Koala

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Average rank #5.3 across 15 sub-categories in 1 country.

Koala appears in 15 AI recommendation categories. Its strongest is Best Sofa Bed for Guests at #1. Its weakest is Best Linen Bedding at #22. That spread is Koala's Recommendation Gap.

Based on real buying questions across ChatGPT, Claude, Gemini and Perplexity. Latest run: June 2026.

Sub-categories ranked
15
Total AI mentions
117
Countries tracked
1
Highest rank
#1
Lowest rank
#22

Recommended alongside Koala

What this means for Koala

Koala ranks in the top 3 for 8 of 15 sub-categories where AI engines recommend brands. There are 7 sub-categories where Koala appears but ranks below top 3. This is the recommendation gap.

Why AI recommends Koala in some categories and not others

AI systems do not recommend brands on popularity alone. They favour brands with clear, structured and citable information for the specific questions buyers ask. Koala performs strongly where those signals are present, and weaker where they are limited. That difference is Koala's Recommendation Gap.

AI See You closes that gap by setting up an AI Knowledge Centre: a deep, defensible data asset structured so AI can read, trust and cite it. It is real, sourced, expertly structured information built for the way AI reads, and it is the opposite of generic AI content or short-term hacks.

See full ranking table

Full Koala ranking footprint by country.

Australia

Best rank #1
Rank Sub-category Share Mentions
#1 Best Sofa Bed for Guests
DTC Furniture
 100.0% 20
#1 Best Modular Sofa for Small Apartments
DTC Furniture
 70.0% 14
#1 Best Mattress for Couples
Mattresses and Bedding
 55.0% 11
#1 Best Bedside Table
DTC Furniture
 45.0% 9
#1 Best Coffee Table
DTC Furniture
 30.0% 6
#1 Best Bookshelf
DTC Furniture
 25.0% 5
#2 Best Mattress for Side Sleepers
Mattresses and Bedding
 55.0% 11
#3 Best Mattress for Hot Sleepers
Mattresses and Bedding
 45.0% 9
#5 Best Mattress for Back Pain
Mattresses and Bedding
 40.0% 8
#5 Best Mattress in a Box
Mattresses and Bedding
 40.0% 8
#6 Best Sofa
DTC Furniture
 35.0% 7
#6 Best Dining Chairs
DTC Furniture
 25.0% 5
#11 Best Bedding for Sensitive Skin
Mattresses and Bedding
 10.0% 2
#13 Best Bedding Bundle for a New Home
Mattresses and Bedding
 5.0% 1
#22 Best Linen Bedding
Mattresses and Bedding
 5.0% 1

About Koala

Koala is an Australian direct-to-consumer furniture and mattress company, founded in 2015, selling mattresses, sofas, sofa beds, bed bases, bedding, and homewares online. It is known for its bed-in-a-box model, sustainability initiatives, B Corp certification, and a partnership with WWF-Australia supporting koala and turtle conservation.

Founded by: Dany Milham, Mitch Taylor, Phil Johnson

Visit official website

Certifications

  • ✓ B Corp Certified
  • ✓ 1% for the Planet Member
  • ✓ FSC Certified Timber

Recognition

  • ★ Product of the Year — Consumer Survey of Product Innovation (Kirribilli Bed Base)
“To build better furniture experiences, designed with the world in mind — combining people-centric products, incredible customer service, and social good to create happier, healthier habitats.”

Where Koala is sold

Koala sells in 3 markets: Australia, Japan, United States.

Future-proof Koala for agentic commerce

When buyers ask AI who to trust, the brands that get chosen are the ones AI can understand, trust and cite. Koala already performs in some categories. The opportunity is to be the brand AI chooses across every category where buyers are deciding.

For brand teams

When buyers ask AI who to trust, Koala should already be the answer

AI See You sets up an AI Knowledge Centre for Koala: the deep, defensible data asset AI reads when it answers buying questions. It is how brands get chosen as AI becomes the way buyers decide.

We typically reply within one business day.

Proven on a live ecommerce brand

An Australian ecommerce DTC men's skincare brand increased its Recommendation Score from 18 to 34 in three weeks.

Track Koala's AI Recommendation Footprint

Get notified when Koala enters new recommendation categories, when its recommendation share changes and when new research is released.