X Tweet Sentiment Analysis with AI | $0.0003/Tweet

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Xquik is the world's fastest & cheapest X (Twitter) scraper service with the most complete X data. Xquik's X Tweet Sentiment Analysis adds attitude, intensity & sarcasm to every tweet. Most other Apify Actors charge before filtering or deduplicating. Xquik charges only for delivered, unique, filter-matching results. AI costs are included in the per-tweet price. You need no AI account, tokens or key.

Measure the attitude behind X (Twitter) posts & keep the original tweet data. Xquik's X Tweet Sentiment Analysis with AI collects matching tweets. It adds an AI-powered sentiment category, intensity level & sarcasm probability to every post. Track reactions to a launch, a campaign, an episode or a public figure. Separate loud reactions from passing mentions.

• Sentiment per post. Each tweet gets its own category, so you can audit every answer.
• Intensity. A level from 0 to 2 separates emphatic posts from mild ones.
• Sarcasm probability. It flags posts whose literal wording contradicts the attitude.
• Complete source records. Every row keeps every field the tweet exposes.

Xquik is an independent third-party service. Not affiliated with X Corp. "Twitter" and "X" are trademarks of X Corp.

How to analyze tweet sentiment

New to Apify? Create a free account first. The free plan needs no credit card & gives $5 to spend each month. At $0.0003 per analyzed tweet, $5 pays for up to 16,000 analyzed tweets before platform usage. Then come back here & press Try for free.

1. Add search terms, profile handles, tweet URLs or tweet IDs.
2. Set maxItems & the extraction filters your task needs.
3. Leave analysis.targets empty to judge each post on its own subject. To focus on a brand, product or person, add its names & aliases.
4. Start the run & open the dataset.

{
  "searchTerms": ["\"season finale\" lang:en"],
  "maxItems": 200,
  "analysis": { "context": "Reactions to the show, not spoilers." }
}

What the Actor answers

Question	Answer
Sentiment	Positive, negative, mixed, neutral or unclear
Intensity	0 passing mention, 1 clear attitude, 2 emphatic wording
Sarcasm	Probability that the literal wording contradicts the attitude

With targets, sentiment judges the attitude toward them. It also uses the quote or reply context you supply. Without targets it judges the main subject of the post.

Analyze your own text

Paste your own drafts, replies, reviews or notes in texts. Xquik's X Tweet Sentiment Analysis analyzes them. It fetches nothing from X.

{
  "texts": [
    "The new update is great, but sync still drops on mobile.",
    "Support fixed my issue in 10 minutes. Thank you."
  ]
}

• Each text becomes 1 row with the same analysis answers as a tweet.
• tweet.id is text:1, text:2 & so on, & tweet.type is text.
• Each analyzed text costs the same $0.0003 as an analyzed tweet.
• With texts set, the run analyzes only those texts. Run X targets separately.

Migrate from another sentiment Actor

Use 1 name per setting when adapting an existing input.

Existing input name	Xquik field
query, searchQuery	twitterContent
queries, searchQueries, search	searchTerms
handles, usernames, username, profileTweets	twitterHandles
tweetUrls, postUrls, urls	startUrls
tweetIDs, tweet_ids, postIds, tweetId	tweetIds
maxTweets, maxResults, count, max_posts	maxItems
sort	queryType
tweetLanguage, language	lang
startDate, endDate	since, until

The Actor accepts these common names directly. It also reads the filter names of other tweet Actors. A filter with no field here becomes an X search operator on every search of the run, & the run log lists those operators at the start. Use Latest or Top for sort. Keep language codes & date boundaries. Limits apply across all targets. This input is ready to run.

{ "searchTerms": ["from:NASA"], "sort": "Latest", "maxItems": 5 }

Other inputs need conversion before the run.

Wrap a single tweetUrl in startUrls.

{ "startUrls": ["https://x.com/NASA/status/2105727882588807607"] }

Put text, Texts, dataset strings or file strings in texts.

{ "texts": ["Support fixed my issue. Thank you."] }

Turn hashtag or cashtag into search strings.

{ "searchTerms": ["#Artemis lang:en", "$AAPL lang:en"], "maxItems": 5 }

Replace minLikes, minReplies & minRetweets with these field names.

{ "min_faves": 10, "min_replies": 2, "min_retweets": 3 }

Results keep the original record in tweet & answers in analysis.answers. Map positive, negative & neutral labels to the matching sentiment categories. Keep mixed & unclear as separate categories. Other sentiment scores may use different scales & meanings. Xquik's intensity runs from 0 to 2 & may include decimals. Sarcasm is a probability. Confidence describes an answer's certainty.

How much does it cost to analyze tweet sentiment?

Xquik's X Tweet Sentiment Analysis costs from $0.0003 per analyzed tweet. It charges no start fee. The price includes collection & AI costs. You need no AI account, tokens or key. The price covers up to 8 questions & 64,000 bytes of context per tweet. Each question definition may use up to 8,000 bytes.

For more volume, pick an Apify plan with more prepaid usage.

Extraction filters & deduplication run before analysis. You never pay for filtered-out or duplicate rows. Failed analyses, skipped analyses & diagnostic rows have no result charge. Apify bills platform usage for compute, storage & transfer separately at your plan's rates. The Pricing tab shows it.

Input & output examples

The input above is copy-ready. An abbreviated output row looks like this.

{
  "tweet": { "id": "2100493544842494265", "text": "…", "likeCount": 12 },
  "analysis": {
    "status": "succeeded",
    "answers": [
      {
        "questionId": "sentiment",
        "type": "choice",
        "value": "positive",
        "confidence": 0.91
      },
      {
        "questionId": "intensity",
        "type": "score",
        "value": 2,
        "confidence": 0.8
      },
      { "questionId": "sarcasm", "type": "probability", "probability": 0.04 }
    ]
  }
}

Each result contains tweet & analysis. Answers include types, question versions & available probabilities. A row with a failed or skipped analysis keeps the collected tweet & a reason. Its answer list is empty.

Free diagnostics in the key-value store explain invalid inputs, missing results & interrupted collection. The run report separates collected rows, charged analyses & pending charges.

Run summary & flat answers

A run writes an analysis-summary record to its key-value store in 3 cases.

• It hits a problem or is large.
• Its comparison finds a changed, new or not comparable tweet.
• It has alwaysSaveRunRecords on.

Other runs skip the record, including the first run of a series. Their status names the top answer, like Top sentiment is positive in 3 of 5 results. A comparison without a change states No change since the earlier run. A run that hits a problem or is large also writes run-report. So does a run with alwaysSaveRunRecords on. run-report repeats the summary under results.analysisSummary.

The summary counts analyzed, failed & skipped rows. It sums engagement & summarizes every question.

• The sentiment split shows how many tweets fall into each attitude.
• engagementShares weights the same split by likes, retweets, replies & quotes.
• top lists the 3 most engaged tweets per attitude.
• Every row lists sourceDomains, the hostnames it links to.
• Every row lists cashtags found in its text, such as $NVDA.
• With monitor.baselineDatasetId set, the summary's monitor block counts comparison statuses. It lists up to 50 changed rows.

The summary rounds numbers to 4 decimals. An empty run reports counts of 0 & null means.

Every result row also carries answers, a flat map keyed by question ID. Each value is the chosen category, score or probability. The Flat answers dataset view & CSV or Excel exports show 1 column per question. The columns sit beside the tweet, so spreadsheets need no JSON parsing. Failed & skipped rows carry an empty map.

Compare with an earlier run

Pass monitor.baselineDatasetId, the dataset ID of a completed earlier run with the same analysis settings. The comparison reads that run's rows. It works even when that run skipped its summary. Every row then gains a monitor object. Its status takes these values.

• first_run without a baseline.
• new_to_baseline for tweets the earlier run did not have.
• unchanged or changed for tweets it had.

changes lists each sentiment, intensity level or sarcasm decision that moved from previous to current. Decisions compare by category, rounded score level or yes/no at 0.5. A decision counts as changed only when it moves clearly. Near ties between runs stay unchanged.

A baseline above maxBaselineRows, or from different settings, stops the run before collection. The run then writes a diagnostic row. maxBaselineRows defaults to 100,000.

Task examples

Choose from 50 public tasks. Start with the example that matches your question. Most tasks use small caps. The 2 dated searches request 50 posts. Open a task to use its saved input. The copy-ready inputs & observed yields below help you choose settings.

Every successful row returns sentiment, intensity & sarcasm probability. Each keeps its original post or supplied text beside the answers. These examples use English inputs & language filters. A language label can still miss other-language text within a post or quote.

Without targets, an answer describes the post's main subject. A keyword mention can concern something else. With several targets, the sentiment answer describes them together. It does not return a separate answer for every target.

Profile likes may be hidden. Use profile replies or posts if unavailable.

Search results can include announcements, promotions, jokes & repeated text. Distinct post IDs do not prove independent reactions or customer identities. Opinion phrases & engagement filters select a sample. Review the posts before counting them as feedback. Analysis does not verify their claims.

Tested task inputs

Open a task. Its Input tab has visual fields & JSON. Copy its JSON or change the fields before starting. Apify explains task inputs.

Test dates use UTC. Yields describe the recorded run, not a guaranteed supply. The dated 50-post examples show why unique IDs differ from independent opinions.

Finale review drafts

Season finale review texts

Separate praise from criticism in your finale review drafts. Observed 3 unique supplied texts on 2026-10-01. The cap was 3. These are your own illustrative texts, not audience research.

Phone launch discussion

September 2026 iPhone launch posts

Review launch discussion within a fixed September date window. Observed 5 unique posts on 2026-10-01. The cap was 5. Announcements and personal opinions can both match.

Halftime show reviews

Halftime show review texts

Check mixed judgments and sarcasm in your halftime reviews. Observed 3 unique supplied texts on 2026-10-01. The cap was 3. These are your own illustrative reviews, not live show reactions.

Electric car experiences

Electric car experience posts

Find posts about driving or choosing an electric car. Observed 5 unique posts on 2026-10-01. The cap was 5. Personal phrases can match jokes or secondhand accounts.

Movie discussion

Marvel movie discussion posts

Review movie discussion before selecting audience comments. Observed 5 unique posts on 2026-10-01. The cap was 5. Marvel can match unrelated uses of the word.

Artist media captions

Taylor Swift media caption tone

Review the artist's wording beside recent media. Observed 5 unique posts on 2026-10-01. The cap was 5. Captions cannot describe everything shown in images or videos.

Game release thread

Game release update thread

Read an announcement beside responses about competing games. Observed 5 unique posts on 2026-10-01. The cap was 5. The thread mentions several games and includes its opening post.

Remote work discussion

Remote work discussion

Compare attitudes expressed in remote work discussion. Observed 5 unique posts on 2026-10-01. The cap was 5. Job ads and repeated opinions can appear.

Airline posts

Airline discussion posts

Review airline mentions before choosing service feedback. Observed 5 unique posts on 2026-10-01. The cap was 5. A mention does not prove the author is a passenger.

College football discussion

College football discussion

Separate fan opinions from college football promotion. Observed 5 unique posts on 2026-10-01. The cap was 5. Previews and promotions can match beside fan opinions.

Interest rate discussion

Interest rate discussion

Review market and policy attitudes around interest rates. Observed 5 unique posts on 2026-10-01. The cap was 5. The main subject can be a politician or the market.

Scooter discussion

Electric scooter discussion

Find scooter discussion before choosing rider feedback. Observed 5 unique posts on 2026-10-01. The cap was 5. Ads, research and jokes can match beside personal experiences.

Restaurant experiences

New restaurant experiences

Review first-person wording about new restaurants. Observed 5 unique posts on 2026-10-01. The cap was 5. Personal wording can also appear in invitations or recommendations.

Public list feed tone

Public list feed tone

Review the tone of posts in a public List. Observed 5 unique posts on 2026-10-01. The cap was 5. Members can discuss other subjects and repost another person's wording.

Device profile replies

Google device profile reply tone

Review wording from a device profile, including replies. Observed 5 unique posts on 2026-10-01. The cap was 5. Missing parent context can limit what a profile reply means.

Marathon training

Marathon training discussion

Find attitudes in training updates and marathon plans. Observed 5 unique posts on 2026-10-01. The cap was 5. Plans and promotion can appear beside runner updates.

Trip planning

Personal Tokyo trip posts

Review personal trip plans and travel stories. Observed 5 unique posts on 2026-10-01. The cap was 5. Tokyo-named events can match without describing a Japan trip.

Streaming price discussion

Netflix price discussion posts

Find Netflix price concerns before reviewing cancellation reasons. Observed 5 unique posts on 2026-10-01. The cap was 5. Price phrases select concerns, not a representative viewer sample.

School supply shopping

August 2026 school supply posts

Review 50 school supply posts within an August window. Observed 50 unique posts on 2026-10-01. The cap was 50. The 50 IDs included 42 clearly related rows in our review.

Train delays

Train delay experience posts

Find complaints and experiences involving delayed trains. Observed 5 unique posts on 2026-10-01. The cap was 5. Personal phrases can miss official notices.

Pet food discussion

Pet food experience posts

Review pet food mentions within wider care discussion. Observed 5 unique posts on 2026-10-01. The cap was 5. Care or veterinary discussions can mention food brands incidentally.

Selected fantasy sports posts

Fantasy sports post batch

Analyze a selected batch of fantasy sports posts. Observed 2 unique posts on 2026-10-01. The cap was 2. Labels concern each post's subject, not automatically an app.

Coffee shop experiences

Coffee shop experience posts

Find coffee shop comments before selecting customer feedback. Observed 5 unique posts on 2026-10-01. The cap was 5. Author complaints remain unverified statements.

Housing market

Housing market discussion

Review opinions and news about the housing market. Observed 5 unique posts on 2026-10-01. The cap was 5. News and opinions can concern different market issues.

Tournament discussion

League of Legends tournament posts

Separate tournament discussion from ticket or match promotion. Observed 5 unique posts on 2026-10-01. The cap was 5. Ticket ads and match reports are not viewer opinions.

Podcast publisher posts

Podcast publisher post tone

Review the podcast publisher's own messaging. Observed 5 unique posts on 2026-10-01. The cap was 5. Publisher tone does not measure listener satisfaction.

Gym comparisons

Gym comparison review texts

Check combined attitude toward 2 gyms in your reviews. Observed 3 unique supplied texts on 2026-10-01. The cap was 3. Both targets share 1 sentiment answer per text.

Car rentals

Car rental experience posts

Find car rental comments before reviewing service concerns. Observed 5 unique posts on 2026-10-01. The cap was 5. Inquiries and promotions can match beside renter accounts.

Campus discussion

University cost and campus posts

Review campus discussion before selecting cost-related posts. Observed 5 unique posts on 2026-10-01. The cap was 5. Campus news and criticism do not prove student experiences.

Wedding planning

Personal wedding planning posts

Find first-person wording about wedding plans and costs. Observed 5 unique posts on 2026-10-01. The cap was 5. Stories, jokes and incidental wording can match beside planning experiences.

Charging experiences

EV charging experience posts

Review charging experiences within electric vehicle discussion. Observed 5 unique posts on 2026-10-01. The cap was 5. Charging can be secondary to another vehicle concern.

Tax filing discussion

Spring 2026 TurboTax filing posts

Review filing discussion within a fixed spring date window. Observed 5 unique posts on 2026-10-01. The cap was 5. Posts do not verify current fees or tax rules.

Theme park visits

Theme park visit discussion

Find theme park mentions before choosing visit reactions. Observed 5 unique posts on 2026-10-01. The cap was 5. Incidental references can match longer posts about another subject.

Grocery spending

Grocery budget experience posts

Find first-person comments about grocery spending. Observed 5 unique posts on 2026-10-01. The cap was 5. Wider political, nutrition or creator discussions can mention grocery spending.

Camera discussion

Phone camera discussion

Review camera mentions beside photos, reviews and announcements. Observed 5 unique posts on 2026-10-01. The cap was 5. Camera mentions can be incidental in other announcements.

Selected sneaker post

A selected sneaker post

Analyze a known post without a broad keyword search. Observed 1 unique post on 2026-10-01. The cap was 1. This selected caption does not describe every detail of its image.

Support chatbots

Support chatbot discussion posts

Find support chatbot discussion before selecting service complaints. Observed 5 unique posts on 2026-10-01. The cap was 5. Emotional support bots and business responses can also match.

Festival discussion

April 2026 Coachella discussion

Review 50 festival posts within an April window. Observed 50 unique posts on 2026-10-01. The cap was 50. The 50 IDs included 47 related rows and repeated news copy.

Electricity bills

Electricity bill discussion

Review personal electricity costs beside policy discussion. Observed 5 unique posts on 2026-10-01. The cap was 5. Policy claims and price predictions remain unverified.

Basketball roster changes

NBA trade and signing discussion

Find trade and signing discussion before choosing fan reactions. Observed 5 unique posts on 2026-10-01. The cap was 5. Other stories can mention players or teams incidentally.

Stay discussion

Airbnb stay discussion

Focus attitudes toward Airbnb within stay discussion. Observed 5 unique posts on 2026-10-01. The cap was 5. Host promotion and app posts can appear beside guest stories.

Book reactions

Book reading reaction posts

Review reading reactions without assuming book club membership. Observed 5 unique posts on 2026-10-01. The cap was 5. Film comparisons and personal reading opinions can both match.

Meal kit experiences

HelloFresh experience posts

Find meal kit comments before reviewing product experiences. Observed 5 unique posts on 2026-10-01. The cap was 5. Plans, ads and wider personal stories can mention the brand.

Race discussion

Formula 1 race discussion posts

Review race discussion beside team and driver statements. Observed 5 unique posts on 2026-10-01. The cap was 5. Quoted driver statements can repeat across different IDs.

Dating app experiences

Dating app experience posts

Find dating app experiences, match remarks and jokes. Observed 5 unique posts on 2026-10-01. The cap was 5. Match remarks and jokes do not verify customer identities.

Airport wait posts

Airport wait and lounge posts

Review airport wait comments beside travel notices. Observed 5 unique posts on 2026-10-01. The cap was 5. Official notices can appear beside personal wait experiences.

School lunch discussion

School lunch discussion

Review personal posts and policy debate about school lunches. Observed 5 unique posts on 2026-10-01. The cap was 5. Authors can include institutions, not only parents.

Beer tasting

Craft beer tasting posts

Find beer tasting opinions before choosing review examples. Observed 5 unique posts on 2026-10-01. The cap was 5. Thin linked captions can lack enough context for a clear attitude.

Docking announcement quotes

SpaceX docking announcement quotes

Review quotes of one docking announcement after a fixed time. Observed 5 unique posts on 2026-10-01. The cap was 5. Quotes can be invitations or neutral descriptions, not only reactions.

Birthday replies

NASA birthday replies

Review direct replies to one birthday post. Observed 5 unique posts on 2026-10-01. The cap was 5. Missing root context can limit what a reply's answer means.

Keep maxItems small while you inspect results. A cap limits output, not supply. If fewer posts qualify, check the run report before changing your filters. Widen 1 setting at a time, such as dates or an engagement floor. Keep a record of the setting you changed.

For failed analyses, inspect analysis.reason & retry only the affected IDs. If a post's replies look incomplete, read the free diagnostic row. It says when X showed fewer replies than it counts. Media captions cannot describe everything shown in an image or video. Missing quote or reply context can make an answer uncertain.

Related Xquik Actors

Every Xquik Actor shares the same extraction engine, filter-first billing & diagnostics. Pick the one that matches the data you need.

• X Tweet Scraper scrapes tweets from searches, profile timelines, Lists & tweet IDs with 50+ filters & flat exports. Use it when you need tweet data without analysis. From $0.00015 per row.
• X Profile Scraper scrapes profiles plus their posts, replies, media & followers from handles, IDs or URLs. Use it when you start from accounts rather than searches. From $0.00015 per row.
• X Reply Scraper scrapes replies, comments & whole conversations under posts with 25+ filters. Use it when you need the discussion beneath tweets. From $0.00015 per row.
• X Engagement Scraper scrapes replies, quotes, retweeters & threads for post URLs or IDs in bulk. Use it when you measure who engaged with posts. From $0.00015 per row.
• X Quote Tweets Scraper scrapes the quote tweets of posts with text, media, counts, authors & 11 filters. Use it when you study who quoted posts & what they said. From $0.00015 per tweet.
• X Follower Scraper scrapes followers, following, List members, subscribers & Community members as profile rows. Use it when you need audience or member lists. From $0.00015 per profile.
• X User Search Scraper searches users by handle, bio & location with follower, verification, age & location filters. Use it when you build account lists from search. From $0.00015 per profile.
• X Account Location Scraper checks where accounts are based with X's "Account based in" label, "connected via" & username changes. Use it when you vet where accounts are based. From $0.00015 per account.
• X Email Scraper gets the emails, phones & links accounts publish on their profiles, from handles, followers or user searches. Use it when you need the emails profiles publish. From $0.00015 per profile.
• X List Scraper scrapes List posts, members & followers from List URLs or IDs. Use it when a curated List defines your sources. From $0.00015 per row.
• X Community Scraper scrapes Community info, posts, searches, members & moderators. Use it when your sources are X Communities. From $0.00015 per row.
• X Space Scraper finds Spaces by keyword & reads their titles, states, times, listener counts, hosts & speakers. It also reads broadcasts by URL or ID. Use it when you track live audio & video on X. From $0.00015 per Space or broadcast.
• X Trends Scraper scrapes real-time trends by location with rank, volume, query & WOEID. Use it when you track what is trending where. From $0.00015 per trend.
• X Jobs Scraper scrapes X job listings by keyword, place, workplace, seniority & company, with salaries & apply links. Use it when you collect job openings posted on X. From $0.00015 per job.
• X Article Scraper scrapes long-form X Articles as Markdown & text with covers, authors, dates & metrics. Use it when you need article bodies, not tweets. From $0.00015 per article.
• X Media Downloader extracts or stores photos, videos & GIFs from posts or profiles with MP4 & metadata options. Use it when you need the media files themselves. From $0.00015 per media row.
• X (Twitter) Brand Monitoring with AI Analysis tracks brand mentions with AI relevance, sentiment & customer-experience answers & compares runs. Use it when you watch a brand over time. From $0.0003 per analyzed tweet.
• X (Twitter) Stock & Crypto AI Trading Signals labels bullish, bearish, neutral or mixed stance, content type, conviction & asset relevance with AI. Use it when you follow stocks, crypto or trading talk. From $0.0003 per analyzed tweet.
• X (Twitter) News Monitor with AI Analysis labels news posts by format, source attribution & topic relevance with AI. Use it when you separate reporting from commentary. From $0.0003 per analyzed tweet.
• X Tweet Classifier with AI Analysis answers your own category, score & yes/no questions for every tweet with AI. Use it when the preset analyses do not fit your labels. From $0.0003 per analyzed tweet.
• X Tweet Viral Score Analyzer with AI estimates a Viral Score from 0 to 100 & a verdict for every tweet from 8 AI trait answers. Use it when you study why tweets spread or flop. From $0.0003 per analyzed tweet.

FAQ & support

Answers to common questions, then where to get help.

Do I need an AI account, X API key or login?

No. Xquik's X Tweet Sentiment Analysis includes AI costs in its price. You need no AI account, tokens or key. You also need no X API key, login or credentials.

Can I use my own questions?

Yes. Custom analysis.questions replace the defaults. Send 1 to 8 choice, score or probability questions. Choice questions accept 2 to 255 categories. Score questions need at least 2 ordered levels. Keep the same questions across runs you want to compare.

Why did a row come back with a failed or skipped analysis?

analysis.status is failed or skipped. The Actor collected & delivered the tweet, but the AI analysis did not complete. analysis.reason names the cause. context_limit means your context & targets leave no room for the tweet. service_unavailable means the analysis service was briefly unavailable. These rows carry no result charge. Shorten analysis.context or rerun the affected IDs.

The Actor still analyzes a tweet longer than maxContextBytes. It cuts quoted & replied-to posts first, then the tweet. analysis.contextAvailability.postText is then truncated. Raise maxContextBytes up to 64,000 to keep more text.

Does the analysis verify facts?

No. Answers describe what the post expresses & how the post frames it. Probabilities express AI confidence, not truth. Review important classifications against the original tweet, which every row keeps.

Which languages work?

Extraction supports every language X serves. We validate analysis on English customer scenarios first. Other supported languages return answers with the same structure. unclear categories & probabilities show uncertainty in every language.

How do I limit cost?

Filters, deduplication & maxItems run before analysis. You pay only for unique, filter-matching tweets. Use precise search operators, date bounds & engagement floors. Start with a small maxItems to check answer quality before a large run.

Is it legal to analyze X data?

The Actor requests public X fields. Results can contain personal data. Confirm a lawful purpose & follow applicable privacy rules. Ask qualified counsel when uncertain.

Can I use the API, schedules & integrations?

Yes. See the API tab for Python, JavaScript & cURL examples. Use Apify schedules for recurring runs. Pass the previous dataset ID as monitor.baselineDatasetId to see what changed. Apify integrations also connect runs to webhooks, Make, Zapier, n8n & Google Sheets.

Where do I get help?

Open an issue in the Issues tab with the run ID. Free diagnostics in the key-value store explain runs that need attention. A run that gets no row back says why in its status.