I built a simple site to aggregate all the free marketing SaaS reports

Hacker News

While doing a lot of reading around marketing I noticed that many popular marketing tools and SaaS businesses provide really interesting data in free reports. Mostly they do this to attract leads for their business - some do offer reports with no strings attached though. However I realised that quite often the data and research they provide in the reports is well worth giving an email address anyway. These reports are a mix of data that pertains to how users use their platforms for their marketing purposes and survey research of their customers and general consumers. For example large email marketing SAAS companies often release very interesting data on how their users are marketing, what the trends are in email marketing and what consumers are interacting with. Marketing based SaaS companies across all the difference facets of marketing release these kinds of reports - so I thought I would aggregate them all in once place. I also pulled an interesting quote from each report and summarised them briefly so interested readers can get an idea of if it’s a report they want to read.

Visit product View on Hacker NewsOct 29, 2024

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, email · Missing: mac, agents, macos

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released

29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

27%27% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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