DDMarketerTags: saas, startup, indiehackers, business Everyone guesses what to build next. I built a pipeline...
Tags: saas, startup, indiehackers, business
Everyone guesses what to build next. I built a pipeline that reads public complaints — Reddit, GitHub, Stack Overflow, Hacker News, Trustpilot, app store reviews, product forums, X — and scores every recurring one for commercial intent. As of September 30, 2026 it has mined 3,539 raw complaints. 1,984 died in editorial review (rants, one-offs, solved problems). 1,555 cleared the gate and got scored 0–100 on buying intent. 698 of those score 80 or better; 629 are greenfield products — the fix is a new tool, not a feature someone's incumbent owes them. And 37 gaps max out the intent score at 100.
This post is 15 of those 37, hand-picked so you don't get fifteen developer tools in a row. Disclosure, because it's my house data: I run DDMarketer, the dataset behind this. Scores read intent-first — 100/80 means intent 100, confidence 80. The approved corpus runs GitHub 587, Reddit 460, Stack Overflow 209, Hacker News 108, Trustpilot 81, product forums 49, X 33, App Store 28 — developers over-index because they complain in public, in writing, on platforms with APIs. Anyone mining public text inherits this bias.
intent 100/100 · confidence 90/100 · Security/Compliance · surfaced from reddit · 1 source
Platforms using Stripe Connect report being shut down entirely over fraudulent connected accounts that Stripe's own Radar misses pre-transaction — no recourse, no prevention, business gone. The buyer doesn't need ROI math when the worst case is the whole platform; the buildable shape is a narrow pre-transaction fraud screen for marketplaces.
Read the problem and the evidence
intent 100/100 · confidence 80/100 · E-commerce · surfaced from appstore · 1 source
An App Store review cluster: merchants on Shopify Payments get logouts, delayed notifications, and fraud protection inadequate enough that they handle scams and disputes manually — and the complaint specifies the product itself: real-time alerts, stable access, dispute support. When a merchant writes your spec, the remaining risk is distribution.
Read the problem and the evidence
intent 100/100 · confidence 100/100 · Dev Tools / SaaS Infrastructure · surfaced from github · 1 source
Developers using AI CLI tools hit unpredictable token cost spikes, rate limits, and regressions that break core workflows — budget overruns plus wasted debugging time. This is the one of only two gaps here that max both scores. A metering-and-guards layer over existing CLIs is exactly what "micro" should mean.
Read the problem and the evidence
intent 100/100 · confidence 80/100 · Dev Tools / SaaS Infrastructure · surfaced from hackernews · 1 source
Owners of large static sites report massive hosting cost increases from AI bot traffic that bypasses standard bot protection and burns bandwidth. A second AI-cost gap from a different platform and a different angle — this one taxes people who aren't even AI users. The buyer already sees the line item on their hosting bill.
Read the problem and the evidence
intent 100/100 · confidence 100/100 · Real Estate / Local Operations · surfaced from github · 1 source
Field operations teams report losing $25,000–$40,000 a year per 10-crew operation to unaccounted equipment damage, with no defensible evidence to charge back costs. The dollar figures are the complainer's own — an anecdote, not verified market data — but a buyer who knows their shrinkage to the dollar has pre-written your ROI slide. Every worker already carries the required camera.
Read the problem and the evidence
intent 100/100 · confidence 90/100 · Real Estate / Local Operations · surfaced from reddit · 1 source
Property management firms cite after-hours coverage as their biggest staffing expense, with 40% of calls repeat inquiries that need no human — the complainer's figures, not a survey I ran. A triage-and-auto-answer layer for the routine 40% is scoped, boring, and billable: the good kind of boring.
Read the problem and the evidence
intent 100/100 · confidence 80/100 · Finance/Accounting · surfaced from trustpilot · 1 source
Small businesses describe payroll failures where funds are pulled but not disbursed, leaving owners covering wages from personal funds and losing employees over it. The complainer isn't requesting a feature — they're proposing your SLA and your pricing model: insurance thinking. Heavy regulatory surface, but the promise is pre-written.
Read the problem and the evidence
intent 100/100 · confidence 80/100 · Finance/Accounting · surfaced from reddit · 1 source
Contractors say they choose between QuickBooks' simplistic, buggy accounting and expensive, clunky ERPs like Sage 100 — manual workarounds, silos, no accurate job costing. Two named incumbents means switchers, not window-shoppers. Honest caveat: this is the one item only "micro" in ambition — ERP is a years-long company, and the intent score measures demand, not build cost.
Read the problem and the evidence
intent 100/100 · confidence 80/100 · Sales/CRM · surfaced from stackoverflow · 1 source
A Stack Overflow user specced the whole thing: a lightweight local database for customers, offers, and invoices with basic CRUD, CSV/XML export, password protection — no web-CRM bloat. A requester technical enough to have specced it wanted it badly enough to start building it themselves, which is the strongest demand signal there is. The hard part is unglamorous offline sync, not features.
(archived signal: evidence dates 2014-2018 — not current demand, so no live page)
intent 100/100 · confidence 80/100 · HR/Recruiting · surfaced from stackoverflow · 1 source
Certification bodies need registration, documentation, payment, quizzes, approval, renewal, and issuance — and report that course-delivery tools like Moodle lack the administrative workflow. Recurring renewals make it a subscription by nature, and it's boring and vertical enough to be unrepresented on build-in-public timelines.
(archived signal: evidence dates 2014-2018 — not current demand, so no live page)
intent 100/100 · confidence 80/100 · Data/Analytics · surfaced from stackoverflow · 1 source
Managed service providers compile weekly health reports across customer servers — uptime, disk, RAID, security events — by hand-rolled scripts that break and delay compliance reporting. The MSP angle matters: the report is compiled for someone who pays them, so your tool defends their revenue, not just their time.
(archived signal: evidence dates 2014-2018 — not current demand, so no live page)
intent 100/100 · confidence 90/100 · Dev Tools / SaaS Infrastructure · surfaced from stackoverflow · 1 source
Enterprises want one view aggregating disparate monitoring tools — health by application and location, custom alerts, root-cause linking — because the patchwork creates noise and duplicate pages. An aggregation and correlation play over tools that already exist is a classic thin-wedge architecture, and related observability complaints are among the most repeated shapes in the corpus.
(archived signal: evidence dates 2014-2018 — not current demand, so no live page)
intent 100/100 · confidence 80/100 · No-Code/Automation · surfaced from trustpilot · 2 sources
Small business owners and freelancers report being forced to pay hidden extra fees to export or host sites built on certain no-code platforms, with no clean exit path. One of only two items here corroborated by two independent sources. An "exit insurance" tool — clean export, one-time pricing — attacks the exact moment a customer is angriest.
Read the problem and the evidence
intent 100/100 · confidence 80/100 · E-commerce · surfaced from trustpilot · 1 source
Enterprise BigCommerce users describe checkout flaws, order-deletion bugs, and automatic URL changes that generate SEO-damaging 404s, with slow vendor response. The gap isn't "build a BigCommerce killer" — it's a monitoring-and-recovery layer that catches broken funnels and 404 regressions before revenue and rankings bleed. Detection tools are smaller than platforms and sell to the same anger.
Read the problem and the evidence
intent 100/100 · confidence 80/100 · Marketing Operations · surfaced from twitter · 2 sources
B2B sales teams report paying exorbitant prices to monopolistic prospect-data providers for data that is often outdated — wasted outreach, poor conversion. The other double-sourced item here, and the complainer discloses their spend. Capturing an existing line item beats creating a budget; the caution is that data businesses have brutal cold-start economics, so the wedge is a segment, not a ZoomInfo killer.
Read the problem and the evidence
Every number above comes from live queries, run September 30, 2026. The pipeline: two LLM scoring passes per complaint, deduplication across distinct authors so one loud thread doesn't masquerade as a market, then a human editorial gate. 1,984 of 3,539 raw rows — 56% — didn't survive review.
The 0–100 intent score estimates how buyer-like a complaint reads. Its inputs: how often the pain recurs (a one-off versus a common or emerging pattern), willingness-to-pay language, emotional intensity, how much evidence backs the row, and whether the fix is a new product or a feature of something that exists. This list is filtered to greenfield products only — 629 of the 698 gaps scoring 80+ qualify — then to the 37 that max out intent at 100, from which I picked 15 for category spread. That hand-picking is editorial judgment, not a ranking. Confidence is the paired score for how settled the evidence is, which is why it varies while intent doesn't.
Three limits you should hold me to. First, 13 of these 15 gaps trace to a single report each; across the whole approved corpus, only 21 of 1,555 gaps are corroborated by two or more sources — roughly 1.4%. The two here with two sources are marked. Single-source gaps are labeled exactly as that: signals, not validated demand. Second, these scores are snapshots with no velocity in them — nothing here tells you a pain is rising, only that it read as high-intent when scored. Third, a complaint is not a contract. Anger on Trustpilot doesn't mean they'll pay you to fix it; it means they might, which narrows where to look.
Talk to the complainers before writing code. The score earns the conversation, not the skip of it.
Where this data lives: ddmarketer.com — 1,500+ scored SaaS gaps mined from real user complaints across 8 public sources, every gap free to read, no email gate. Want them inside your editor? Free MCP server, no key, no account:
claude mcp add --transport http ddmarketer https://www.ddmarketer.com/api/mcp