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Asklayer's answer:
Asklayer is built by a team of experts from Japan and was created out of frustration with low response rates associated with traditional surveys. We found that most users hate surveys, however they are willing to answer a few questions.
So we created Asklayer, a micro-survey tool that presents itself as simple questions to the user to reduce friction and increase response rates. Unlike traditional surveys we collect data after every question so even if the user abandons part way, you still get answers and a measure of the drop-off point.
The results of all these efforts is a much better user experience, a greatly increased response rate and a much greater total volume of data collected.
Asklayer's answer:
i like reddit very much
It's flexible and does most things well. Support is amazing, they even added a feature for me!
Got a really high response rate. I used this in tandem with Promolayer on my EC site for CRO. I did a 'whats missing from this product description' type survey + post purchase + product follow-up email and frankly, it's been amazing. I spent about 2 years trying to figure out my direction via analytics and heatmapping when I should have just been talking to my users the whole time.
Based on our record, Reddit seems to be more popular. It has been mentiond 3301 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
From urllib.parse import urlparse Def normalize_gh(r): return { "title": r["name"], "url": r["url"], "source": "github", "score": r["stars_this_period"], "desc": r.get("description", ""), "date": r["trending_date"], "lang": r.get("language"), } Def normalize_hn(p): return { "title": p["title"].replace("Show HN: ", ""), "url":... - Source: dev.to / 3 months ago
@tool Def search_reddit(keywords: str, max_results: int = 20) -> list[dict]: """Fallback: search Reddit directly via PRAW.""" reddit = praw.Reddit( client_id=os.environ["REDDIT_CLIENT_ID"], client_secret=os.environ["REDDIT_CLIENT_SECRET"], user_agent="doug-agent/1.0", ) candidates = [] for submission in reddit.subreddit("all").search(keywords, sort="new",... - Source: dev.to / 2 months ago
Import requests Import time Def fetch_subreddit_posts(subreddit, sort="hot", limit=25): url = f"https://www.reddit.com/r/{subreddit}/{sort}.json" params = { "limit": limit, "raw_json": 1, # Prevents HTML encoding in responses } headers = { "User-Agent": "PythonScraper/1.0 (research project)" } response = requests.get(url, params=params, headers=headers) if... - Source: dev.to / 3 months ago
From sessionkeeper import SessionKeeper Async with SessionKeeper("reddit") as sk: page = await sk.get_authenticated_page("https://reddit.com") # You're logged in. Do your automation. await page.goto("https://reddit.com/r/blender/submit"). - Source: dev.to / 4 months ago
It's completely free, and takes just moments to set up - you just need to create an account, and set up keywords for the service to track. When your keywords are mentioned on Reddit, Hackernews, or Lobste.rs, you'll get a tidy little email in your inbox. - Source: dev.to / over 1 year ago
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