// AI RECOMMENDATION INDEX · 2026-W24 · n=30
What AI actually
recommends, measured weekly
We ask ChatGPT, Claude, Gemini and DeepSeek the questions real buyers ask — then publish exactly who they name, with sample sizes and the sources they cite.
> query the index — e.g. "best crm" ▍
[ 34 categories ][ 5 models ][ sources cited ][ csv export ]
reco --category accounting --week 2026-W24 open →
MENTION RATE · ALL MODELS · n=30
0190%
0290%
0370%
0463%
0560%
→ full_breakdown --accounting 34
categories tracked
5
AI models sampled
2026-W24
current week
Weekly
refresh cadence
THE_INDEX // 2026-W24
sort: mention_rate ↓ #CATEGORYTOP_PICKRATE%AGREEMENTΔWK
01 Meeting Scheduling Calendly ██████████ 100% ▮▮▮▮ HIGH new 02 CRM Pipedrive ██████████ 97% ▮▮▮▯ HIGH new 03 HR Software Gusto ██████████ 97% ▮▮▮▯ HIGH new 04 Customer Support Helpdesk Freshdesk █████████· 93% ▮▮▯▯ MED new 05 Accounting Software QuickBooks Online █████████· 90% ▮▮▮▯ HIGH new 06 Project Management ClickUp █████████· 90% ▮▮▯▯ MED new 07 Business Password Manager Bitwarden ████████·· 83% ▮▮▯▯ MED new 08 Email Marketing MailerLite ███████··· 73% ▮▮▮▯ HIGH new 09 Live Chat Software Tidio ███████··· 70% ▮▮▯▯ SPLIT new 10 Web Analytics Plausible ███████··· 67% ▮▮▯▯ SPLIT new MODEL_MATRIX // Accounting Software
Who each model recommends — mention rate per brand × model. Brighter = named more often. Every category page has its own matrix.
BRAND DS GEM KIMI GPT PPLX AVG
QuickBooks Online 831008310083 90%
Xero 100838310083 90%
Wave 10033836767 70%
FreshBooks 6767508350 63%
Zoho Books 10033336767 60%
Gusto 333350170 27%
TOP_CITED // Accounting Software
1 nerdwallet.com 15.6%
2 pcmag.com 15.1%
3 techradar.com 13.5%
4 businessnewsdaily.com 11.5%
5 synder.com 6.8%
METHODOLOGY.log read full →
[01] prompts/ fixed buyer-intent questions per category — what people actually ask.
[02] sampling/ each prompt × 5 models, repeated — frequency, never a single answer.
[03] publish/ every prompt, model & limitation public · raw data downloadable.
track_your_brand_
Weekly report of how often AI recommends you — and exactly what to do about the gaps.