Specrom's managed Twitter scraping service delivers structured tweet data, bulk profile exports, and recurring keyword monitors — without you building or maintaining a scraper. We handle proxy rotation, anti-bot evasion, and data normalization. You get clean data delivered via CSV, REST API, or S3. Starting at $49.
// Three things Specrom scrapes for you // 1. Tweets — by keyword, hashtag, or user { "tweet_id": "1879312...", "text": "AI is transforming fintech...", "likes": 847, "retweets": 203, "author_followers": 28400 } // 2. Profiles — bulk handle lookup { "username": "naval", "followers_count": 2100000, "bio": "Co-founder Angellist..." } // 3. Keyword monitoring — recurring delta // New tweets since last Monday: 847 // Delivered to s3://your-bucket/ 06:00 UTC
Most Twitter data needs fall into one of three categories. Specrom covers all three — you can order one or combine them into a single delivery pipeline.
// Order what you need, combine freely tweets/search ?q="climate tech" &from=2024-01-01 &lang=en profiles/bulk ?handles=naval,paulg,sama... &fields=all monitors/create ?keywords=["#fintech","open banking"] &frequency=weekly &destination=s3://bucket/ bio-search ?q="seed investor" &min_followers=5000
Managed means managed. You describe what you need; we deliver the data. No infrastructure, no maintenance, no debugging failed scrapers at midnight.
Keywords, hashtags, account handles, or a bio search query. Specify volume, date range, language, and delivery format. One-time pull or recurring delivery. We'll confirm the spec and send a sample within 24 hours.
Proxy rotation, anti-bot evasion, CAPTCHA handling, pagination, deduplication, and schema normalization — all handled by our infrastructure. You never see any of this. Data is validated before it leaves our systems.
CSV or Parquet delivered by email, S3, or SFTP. JSON via REST API. Webhook for event-driven integration. Same clean schema every time — whether it's your first delivery or your fiftieth.
Here's how four types of teams use Specrom's Twitter scraping service.
Pull large tweet datasets for sentiment analysis, trend research, or academic study. Historical keyword pulls, structured output, and a consistent schema that loads cleanly into Pandas, R, or BigQuery without a cleaning step.
Recurring keyword monitors for brand mentions, competitor tracking, and campaign hashtag performance. Bio search for influencer discovery and prospecting. Profile scraping to enrich contact lists with current follower data.
Continuous tweet stream for fine-tuning datasets, sentiment model training, and social media NLP corpora. Domain-specific keyword monitoring delivers fresh, relevant training data on schedule without manual collection effort.
Bio search to build targeted prospect lists by job title, industry, or tech stack mention. Profile scraping to enrich CRM contacts with current social data. Keyword monitoring to identify high-intent signals (e.g. prospects mentioning competitor pain points).
Every team that builds its own Twitter scraper goes through the same arc. Week one: a Python script pulling data, everything looks fine. Week two: rate limits kick in. Week three: the IP gets flagged. Week four: you're managing a residential proxy pool and your data engineer is spending two days a week on scraper maintenance instead of analysis.
This is the hidden cost of DIY scraping at scale — not the initial build, but the ongoing maintenance burden. Twitter's anti-bot systems are not static. They update. New fingerprinting techniques, new CAPTCHA variants, schema changes in the internal API that the web client uses. Each update can silently break your scraper, and you often find out days later when you notice the pipeline hasn't written a new row.
Managed scraping shifts the maintenance burden from your team to ours. You get a stable data pipeline without the ops overhead.
// DIY scraper week 1: requests.get("twitter.com/search") → 200 OK (but data is empty) → Actually a bot detection response // DIY scraper week 4: → CAPTCHAs on every 10th request → Residential proxy bill: $400/mo → Pipeline still not in production // Specrom managed service: → Request submitted → Sample delivered in 24 hours → Pipeline running in 48 hours
The free tools (Twitter bio scraper and profile scraper at specrom.com) are self-serve with limited result volumes — ideal for testing and small one-off lookups. The managed service handles bulk volume (thousands to millions of records), recurring automated delivery, and custom query configurations that the self-serve tools don't support.
For standard requests, we deliver a sample within 24 hours and the full dataset within 24–72 hours depending on volume. Recurring monitors are configured and running within 48 hours of setup confirmation. For very large historical pulls (millions of tweets), we'll give you an estimated turnaround at quote time.
Yes. Many customers run all three: a one-time historical tweet pull to establish a baseline, profile scraping to enrich account data on key authors, and ongoing keyword monitoring for continuous coverage. We'll price these as a bundle.
Specrom accesses public Twitter data through its own infrastructure, not the official Twitter API. This allows us to offer data types and volumes that the API's current pricing tiers make impractical for most business use cases.
CSV or Parquet by email for smaller orders. S3 bucket, SFTP, or BigQuery for larger or recurring deliveries. REST API for real-time querying. Webhook for event-triggered workflows. We'll match the delivery method to your stack.
No hard minimum. Tweet scraping starts at $49 for a one-time pull. Profile scraping through the free tool handles small lists at no cost. For recurring monitors, pricing starts based on keyword group count and delivery frequency — contact us for a quote.
Yes. Language filtering is available for all tweet scraping and keyword monitoring. We can scope pulls to a specific language, a list of languages, or leave language unrestricted for multilingual datasets.
Tell us what Twitter data you need and we'll respond within 24 hours with a sample dataset and pricing for your specific use case.