What people ask, share and struggle with about home decor lighting, Rowabi and its competitors · lighting fixtures only · YouTube, Quora / Houzz, Facebook groups, Reddit, TikTok / Instagram (Apify)
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The tool collects public posts, comments, forum threads and reviews about lighting, Rowabi and its competitors, then: 1 cleans them and removes duplicates, 2 keeps the relevant ones and finds the brands named, 3 reads the sentiment, 4 classifies intent (question, complaint, review…), product line, room and pain point. Steps 2–4 use Claude Haiku in batches. The cron collects each source on its own schedule; "Collect now" runs one immediately.
Sources
Official APIs, Google results, public review widgets; public Facebook groups only through Apify (optional); no X
AI digest
A report for the marketing team (in Vietnamese) that rests on evidence: the numbers (items, independent threads, communities, share of a topic this week against the 4 weeks before) are computed by the tool, not by the AI, and every finding cites numbered items, listed with their links under the report. At most 6 items per community are used, so one viral thread cannot decide the result. A topic seen in fewer than 3 threads or in one community is written as a signal, not a trend.
Every collection run: records found and new, status, error and estimated cost (DataForSEO prices; Apify reports its own). More records than the day before does not mean more interest: check that the coverage stayed the same.
Every relevant item, newest first: open it to answer the person (only when you have something useful to add), or hide it if it is noise. The line under each item is the AI summary; the chips are what the analysis found.
Questions people ask
Items whose intent is a question or a request for recommendations, most discussed first. Each is a ready topic for a blog post, a FAQ on a collection page, or a reply in the thread. Group them by pain point and product line to plan content.
Pain points
The problems and doubts people have, counted over the relevant items of the period, with the share of negative ones. Fix the biggest ones where buyers decide: product page details (size, height, wiring, bulb), FAQ, photos, shipping information. Click a row to read the items.
By product line and room
Pain points per week
Trends: is it really growing?
For each pain point, product line and room: the independent threads of the last 7 days (comments under one video or post count once), the communities naming it, and its share of all threads against the average of the 4 weeks before. The status is a fixed rule, not the AI:
confirmed potential, also up the week before and seen in Rowabi's own reviews: worth an action ·
potential 10+ threads in 3+ communities and a higher share: check the evidence ·
spike 60%+ from one community (a viral post, an ad): note it, do not act yet ·
signal seen, not enough evidence. These thresholds are pilot rules, not a statistical test.
The team decides here what to act on. Only trends that passed the evidence gate come in (confirmed, potential, spike). For each one: read the numbers and the quotes (open them), then approve it as an action with an owner, a due date and the metric that will show whether it worked, ask for more evidence (it comes back after 7 days or 3 more threads), or skip it with a reason (it comes back only if it doubles). At most 3 approved actions a week, so the team finishes what it starts. Every decision is in the Google Sheets feed (Trends and Actions).
What the team decides to do from the evidence: a FAQ, a size guide, a product page photo, a piece of content… Each action keeps its evidence links, an owner, a status and the metric that will show whether it worked. Create one from a row of Trends, or here.
Brands: share of voice and sentiment
How often each brand is named in the relevant items, and how people feel about it. Click a brand to read its mentions; negative mentions of competitors show what buyers dislike (an opening for Rowabi).
What to listen to
Brand names and competitors are searched everywhere; topics (the main collections) are searched in the home decor communities, on YouTube and in Google results of the sites below. Saved for everyone.
Only lighting fixtures are kept: a video, post or thread needs one of these words (or pendant, sconce, chandelier, flush mount, lamp…) in its title; a comment needs it in its video / post or in itself. A competitor review from an Apify source needs one too.
3 channels per run, in turn: their newest uploads (a creator's lighting videos only, a brand's all) and the newest comments under them. Find more with the button below.
Optional, through Apify's Facebook Groups Scraper (secret APIFY_TOKEN), on the schedule below (7 days by default): the posts of the last 14 days (30 per group) and their top comments, without author names. Public groups only. Scraping is against Facebook's terms: keep it to a small pilot (3–5 groups, US home decor / kitchen / patio) and check the cost on the Run log.
More sources through Apify
Any actor of the Apify Store, e.g. TikTok or Instagram comments under competitor and creator videos, comments of Facebook posts, Quora answers, Amazon / Wayfair reviews of lighting products. Each source runs on its own schedule with a cap on items and on cost per run (maxItems, maxTotalChargeUsd); its records then go through the same cleaning, de-duplication and AI analysis. Start from a template, test with "Collect now" and a small cap, check the records in Mentions and the cost in the Run log, then turn the schedule on. Needs the secret APIFY_TOKEN.
YouTube channels
8 searches, about 800 of the 10,000 free daily units
Google Sheets and Looker Studio (optional)
Only needed to share the data outside this tool or to build your own charts: the team reviews and plans in the Insights tab. A live link for Google Sheets (IMPORTDATA, refreshed about every hour); Looker Studio reads the sheet.
Setup of the sources (Cloudflare → Worker geo-tag → Settings → Variables and Secrets)
Reddit (internal use): reddit.com/prefs/apps → create another app → type script, redirect https://tools.rowabi.com → copy the client id (under the app name) and the secret → Secrets REDDIT_CLIENT_ID, REDDIT_CLIENT_SECRET.
YouTube: Google Cloud (project geo-tag) → APIs & Services → Library → YouTube Data API v3 → Enable → Credentials → Create credentials → API key (restrict it to YouTube Data API v3) → Secret YOUTUBE_API_KEY. Free quota 10,000 units a day; the tool uses about 900.
Quora / Houzz / forums: the DataForSEO secrets of the Rank Tracker (about $0.003 per Google search).
Google Sheets / Looker Studio / n8n (optional): Secret SOCIAL_FEED_KEY = a long random text (32+ characters, e.g. from a password generator). It opens /feed/social.csv (read-only CSV) and /hook/social (start a source from n8n, or collect when an Apify webhook says a run finished) to whoever has the key, so keep it private.
Facebook groups (optional): apify.com → sign up → Settings → API & Integrations → copy the personal API token → Secret APIFY_TOKEN. Apify's free plan gives $5 of usage a month; the scraper is paid per result, see its price on the Apify Store page of "Facebook Groups Scraper".
Analysis: ANTHROPIC_API_KEY (Claude Haiku; already set) or OPENAI_API_KEY; without a key a word list is used. Alerts for negative mentions of your brand go to the Visitor Log alerts and to Slack when SLACK_WEBHOOK_URL is set.