Duolingo vs. Babbel — VOC Brand Study

duolingo-e2e · July 2026 · 364 records · Reddit · YouTube · TikTok

Insights — Analysis Methodology

Wave-0 Freeze

Corpus Profile

SourceDuolingoBabbelTotal
Reddit8360143
YouTube11388201
TikTok20020
Total216148364
Sentiment Scorecard
MetricDuolingoBabbel
Complaint rate (non-howto base)6.0%2.8%
Praise rate (non-howto base)26.5%34.0%
Cross-brand co-mentions11 records discuss both brands

Note: No star ratings in corpus — rates are keyword-incidence from organic text, not star-rating averages. Never compare these rates as if they are the same as review scores.

Corroboration — 7/7 findings confirmed
FindingPass 1 (mechanical)Pass 2 (blind)Agreement
Streaks = core identityHigh-freq unigram13 records (6%)
Free = top love driverProminent unigram13 records (6%)
Hearts = top complaintCluster detected3 records
Fluency gap = churnBigram cluster2 records (directional)
AI controversy signalProminent unigram8 records (4%)
Babbel = structuredTop unigram13 records (9%)
Babbel = expensive vs freeCluster detected10 records (7%)

No divergence detected. Confidence: medium — small corpus (364 records per brief spec); directional agreement holds; rates are indicative.

Source Review — 28/28 loci accepted

LLM judge ran autonomously (declared smoke run). All 28 source loci accepted. No false positives detected. 0 rejected, 0 unreviewed. See full table in L3 report Appendix.