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WebEngage - online surveys with targeting

Hacker News

WebEngage - online surveys with targeting

Hello. I am Avlesh - co-founder and ceo at WebEngage (http://webengage.com) We have done a small experiment with online surveys. We added the capability of, what we call as, "targeting" these surveys to specific visitors on your website. So, when you create a survey using WebEngage and want to display it to visitors on your website (via a WebEngage widget), we let you choose from a bunch of conditions. E.g. you can say, "this survey should only be displayed to visitors coming from Google search and staying on my home page for at least 30 seconds". Have a look at a demo survey on http://webengage.com (please wait for 10 seconds for a survey to pop).

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
59%59% 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: google, using · Missing: mac, agents, macos
55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
16%16% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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