AI Recommendation Footprint
MAAP
Is this your brand? Claim or correct it.
Average rank #5.1 across 7 sub-categories in 1 country.
MAAP appears in 7 AI recommendation categories. Its strongest is Best Premium Cycling Brand at #1. Its weakest is Best Cycling Apparel for Women at #12. That spread is MAAP's Recommendation Gap.
Based on real buying questions across ChatGPT, Claude, Gemini and Perplexity. Latest run: June 2026.
- Sub-categories ranked
- 7
- Total AI mentions
- 62
- Countries tracked
- 1
- Highest rank
- #1
- Lowest rank
- #12
Recommended alongside MAAP
What this means for MAAP
MAAP ranks in the top 3 for 2 of 7 sub-categories where AI engines recommend brands. There are 5 sub-categories where MAAP appears but ranks below top 3. This is the recommendation gap.
Why AI recommends MAAP 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. MAAP performs strongly where those signals are present, and weaker where they are limited. That difference is MAAP'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.
Where MAAP leads
Sub-categories where MAAP ranks in the top 3 of AI recommendations.
See full ranking table
Full MAAP ranking footprint by country.
Australia
Best rank #1| Rank | Sub-category | Share | Mentions |
|---|---|---|---|
| #1 | Best Premium Cycling Brand
Cycling Apparel
|
85.0% | 17 |
| #1 | Best Cycling Jersey for Summer
Cycling Apparel
|
75.0% | 15 |
| #4 | Best Cycling Jacket for Cold Weather
Cycling Apparel
|
40.0% | 8 |
| #5 | Best Cycling Kit for Indoor Training
Cycling Apparel
|
35.0% | 7 |
| #5 | Best Cycling Apparel for Beginners
Cycling Apparel
|
25.0% | 5 |
| #8 | Best Cycling Bib Shorts for Long Rides
Cycling Apparel
|
25.0% | 5 |
| #12 | Best Cycling Apparel for Women
Cycling Apparel
|
25.0% | 5 |
Where MAAP could grow
Sub-categories where MAAP appears in AI recommendations but ranks below the top 3. Each is an opportunity to expand share.
-
#4
Best Cycling Jacket for Cold Weather
Cycling Apparel · Australia
40.0% shareof 25 brands -
#5
Best Cycling Kit for Indoor Training
Cycling Apparel · Australia
35.0% shareof 24 brands -
#5
Best Cycling Apparel for Beginners
Cycling Apparel · Australia
25.0% shareof 22 brands -
#8
Best Cycling Bib Shorts for Long Rides
Cycling Apparel · Australia
25.0% shareof 25 brands -
#12
Best Cycling Apparel for Women
Cycling Apparel · Australia
25.0% shareof 30 brands
About MAAP
Premium performance cycling apparel and accessories brand engineered to excel in all conditions, designed for ambitious cyclists with a focus on aesthetic and technical detail.
“We're performance driven. Gear that elevates the ride is our obsession. We work with hand selected athletes, teams and events across the globe to design, refine and test the most technically advanced apparel available, for the most ambitious cyclists.”
Where MAAP is sold
MAAP sells in 1 market: Australia.
Future-proof MAAP for agentic commerce
When buyers ask AI who to trust, the brands that get chosen are the ones AI can understand, trust and cite. MAAP 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, MAAP should already be the answer
AI See You sets up an AI Knowledge Centre for MAAP: 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 MAAP's AI Recommendation Footprint
Get notified when MAAP enters new recommendation categories, when its recommendation share changes and when new research is released.