Generated from In-gage – AI Quality Assurance, Surveys & Case Categorisation's audit data
In-gage – AI Quality Assurance, Surveys & Case Categorisation scores 65/100 across 6 category checks, which tracks in the middle band, with 3 of 6 categories below the headline. Strengths: title optimization holds at 88/100, so the listing isn't fundamentally broken — the lift is in tightening specific weaknesses. Watch-items: languages (50/100) and technical & support (50/100) drag the average down; lifting languages is the single largest available lever. Per-category breakdown below.
This is an independent listing audit for In-gage – AI Quality Assurance, Surveys & Case Categorisation on Salesforce. It scored 65/100 (grade C) on today's snapshot. Top strength: Title Optimization at 88/100. Biggest gap: Visual Assets at 50/100. We re-audit every 24 hours from the canonical Salesforce listing.
Six weighted areas, pass / warning / fail per check, tiers at 85 / 65. Full methodology · Glossary
Last updated: July 14, 2026
In-gage – AI Quality Assurance, Surveys & Case Categorisation's overall score of 65/100 is a mid-tier result — the listing is functional but multiple categories have headroom, computed as the weighted average of 6 category checks. The spread is highly polarized across categories — 3 categories score above the headline number and 3 score below. The strongest category is Title Optimization (88/100, +23 vs overall); the weakest is Languages (50/100), 15 points below the overall — a meaningful but not dominant gap. Top three by score: Title Optimization (88), Categories & Discoverability (75), Description & Content (71).
Scoring criteria, category weightings, and the full rubric (identical across every Salesforce AppExchange listing AppRanks audits) are documented on the methodology page and the audit-score glossary entry. Disputes or data corrections: [email protected].
In-gage – AI Quality Assurance, Surveys & Case Categorisation scored 65/100 in the AppRanks listing audit — a mid-tier result with room to improve. The score is the weighted average of 6 category checks: Title Optimization 88/100, Description & Content 71/100, Visual Assets 50/100, Categories & Discoverability 75/100, Technical & Support 50/100, Languages 50/100. Each category is scored against a fixed rubric that is identical for every app on the platform, so scores are directly comparable across Salesforce listings.
In-gage – AI Quality Assurance, Surveys & Case Categorisation's strongest audit area is Title Optimization, scored at 88/100. Of the 4 checks AppRanks runs in this category, 3 pass cleanly, with the remainder in warning rather than failing state. This is the dimension a competing listing would need to match before In-gage – AI Quality Assurance, Surveys & Case Categorisation loses its current edge in this category.
The weakest area in In-gage – AI Quality Assurance, Surveys & Case Categorisation's audit is Visual Assets, scored at 50/100. The failing checks are screenshot 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.