Original data - updated July 2026
The State of SaaS Gaps
DDMarketer is tracking 496 validated software opportunities across 12 categories, mined from real user complaints. Average commercial intent is 80/100, and E-commerce leads on commercial intent (avg 85). 97% show an explicit willingness-to-pay signal and 9% are trending up.
Validated gaps
Avg commercial intent
Willing to pay
Trending up
Category leaderboard
Ranked by average commercial intent.
| Category | Gaps | Avg CI | Avg conf | Trending |
|---|---|---|---|---|
| E-commerce | 24 | 85 | 85 | 21% |
| HR / Recruiting | 21 | 85 | 86 | 19% |
| Marketing Operations | 29 | 81 | 85 | 17% |
| Dev Tools / SaaS Infrastructure | 179 | 80 | 89 | 2% |
| Data / Analytics | 110 | 80 | 86 | 5% |
| CRM | 1 | 80 | 80 | 0% |
| No-Code / Automation | 39 | 79 | 85 | 10% |
| Security / Compliance | 16 | 79 | 86 | 31% |
| Real Estate / Local Operations | 15 | 79 | 84 | 33% |
| Finance / Accounting | 36 | 78 | 85 | 14% |
| Creator Operations | 24 | 76 | 86 | 13% |
| Sales / CRM | 2 | 75 | 83 | 0% |
Highest-intent gaps right now
- ZoomInfo's $12k outdated data and bad CSMarketing OperationsCI 100
- DTC email flows segmented by actual customer behaviorMarketing OperationsCI 100
- Correlate New Relic and What's Up Gold alertsData / AnalyticsCI 100
- Fix BigCommerce checkout and SEO-killing 404sE-commerceCI 100
- Merge MySQL, Elastic, REST APIs for data-opsDev Tools / SaaS InfrastructureCI 100
- No-Code / AutomationCI 100
- Dev Tools / SaaS InfrastructureCI 100
- Data / AnalyticsCI 100
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Where demand concentrates
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Frequently asked questions
- How many validated SaaS gaps does DDMarketer track?
- DDMarketer tracks a growing corpus of validated software opportunities mined from real user complaints, each scored for commercial intent and confidence and grouped into categories. The figures on this page reflect the current approved set and refresh as the weekly pipeline runs.
- Which categories have the highest commercial intent?
- The category leaderboard on this page ranks every category by average commercial-intent score, so you can see where people are most clearly willing to pay for a fix.
- Where does this data come from?
- From public, attributable complaints (Reddit, Hacker News, app store reviews, public forums), classified by a two-pass LLM pipeline and editorially approved. See the methodology page for the full process.