Generated from poli_bot's audit data
poli_bot scores 39/100 across 6 category checks, which indicates listing-quality gaps across 2 of 6 audited categories. Strengths: title optimization (50/100) is the strongest category — installing for evaluation is fine, long-term confidence needs the gaps below addressed. Watch-items: languages (0/100) and categories & discoverability (17/100) drag the average down; lifting languages is the single largest available lever. Per-category breakdown below.
This is an independent listing audit for poli_bot on Zoom. It scored 39/100 (grade D) on today's snapshot. Top strength: Visual Assets at 50/100. Biggest gap: Languages at 0/100. We re-audit every 24 hours from the canonical Zoom listing.
Six weighted areas, pass / warning / fail per check, tiers at 85 / 65. Full methodology · Glossary
Last updated: September 11, 2026
poli_bot's overall score of 39/100 is a result that signals significant listing weaknesses across multiple categories, computed as the weighted average of 6 category checks. The spread is highly polarized across categories — 4 categories score above the headline number and 2 score below. The strongest category is Title Optimization (50/100, +11 vs overall); the weakest is Languages (0/100), a 39-point gap below the headline score — the largest single lever. Top three by score: Title Optimization (50), Description & Content (50), Visual Assets (50).
Scoring criteria, category weightings, and the full rubric (identical across every Zoom App Marketplace listing AppRanks audits) are documented on the methodology page and the audit-score glossary entry. Disputes or data corrections: [email protected].
poli_bot scored 39/100 in the AppRanks listing audit — a result that signals significant listing weaknesses. The score is the weighted average of 6 category checks: Title Optimization 50/100, Description & Content 50/100, Visual Assets 50/100, Categories & Discoverability 17/100, Technical & Support 42/100, Languages 0/100. Each category is scored against a fixed rubric that is identical for every app on the platform, so scores are directly comparable across Zoom listings.
poli_bot's strongest audit area is Title Optimization, scored at 50/100. Of the 4 checks AppRanks runs in this category, 0 pass cleanly, with the remainder in warning rather than failing state. This is the dimension a competing listing would need to match before poli_bot loses its current edge in this category.
The weakest area in poli_bot's audit is Languages, scored at 0/100. The failing checks are language count, each with a concrete fix described below. Tightening this category is the highest-impact change available to the listing — its weight in the overall score makes it the lever most likely to move the headline number on the next refresh.