Iterable vs Qualtrics
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Iterable and Qualtrics both appear on the Smoower Developer Ecosystem Index.
Iterable (rank #317) holds a modest lead over Qualtrics (rank #693) on the overall Smoower ecosystem score (44 vs 31). The gap of 13 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), Iterable is clearly ahead of Qualtrics. On education (docs, guides and learning material for developers), Iterable is ahead of Qualtrics. On community (issue response, PR reviews and discussion health), Iterable is clearly ahead of Qualtrics. On reach (how visible the ecosystem is beyond its own repos), Qualtrics is clearly ahead of Iterable. On momentum (release cadence and how fast the ecosystem moves), Iterable is clearly ahead of Qualtrics.
Iterable carries 269 GitHub stars across 100 public repos, with 16 repositories active in the last 90 days and 10 external contributors on record. Qualtrics shows 20 stars across 20 public repos, 7 active in the last 90 days and 3 external contributors. The star gap on its own does not decide the comparison, but Iterable's footprint is roughly 13.4x larger, which usually shows up in downstream signals like inbound issues and third party integrations.
Iterable is the stronger read for anyone weighting momentum. Qualtrics looks better where reach is the deciding factor. The table below breaks the scores down pillar by pillar; the linked profiles cover the underlying repos, docs and community signals in full.
Side-by-side metrics
| Metric | Iterable | Qualtrics |
|---|---|---|
| Ranking | ||
| Overall rank | #317 | #693 |
| Pillars | ||
| Overall | 44 | 31 |
| Code | 51 | 27 |
| Education | 59 | 40 |
| Community | 35 | 14 |
| Reach | 16 | 82 |
| Momentum | 58 | 18 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 269 | 20 |
| Forks | 212 | 13 |
| Public repos | 100 | 20 |
| Active repos (90d) | 16 | 7 |
| External contributors | 10 | 3 |
| Avg polish | 53 | 28 |
| Avg AI-readiness | 34 | 19 |