If you're trying to grow your brand on Twitter, stalking your competitors' followers isn’t just smart—it’s basic research. Want to know who’s following them, what those people care about, and where you might find your next fans? This guide is for you.
We're going to walk through scraping competitor followers on Twitter using Texau, then making sense of the data. No fluff—just a practical, step-by-step playbook. If you’ve got a reason to peek behind the curtain (marketing, sales, recruiting, whatever), you’ll find what works here.
Why bother scraping competitor followers?
Let’s be honest: Twitter’s built-in tools for audience research are a joke. If you want to know who follows your competitors—and how you can reach them—you need the raw data. Here’s what you can actually do with it: - Find potential customers: These people already care about your niche. - Spot patterns: See what your competition is doing right (or wrong). - Build targeted lists: Outreach, ads, partnerships—you name it.
Sure, you won’t get deep psychographic profiles, but you’ll get enough to actually take action. The trick is not getting lost in the weeds.
Step 1: Get your tools ready
Before you dive in, you need: - A Texau account (free trials are available, but scraping lots of data might need a paid plan). - A Twitter account (preferably one that’s not brand new—Twitter gets suspicious of fresh accounts running lots of automation). - A spreadsheet app (Excel, Google Sheets, or anything that can handle CSVs).
Pro tip
Don’t use your main Twitter account for scraping. If Texau (or any automation tool) triggers Twitter’s alarms, you could get temporarily restricted. Use a decent, “aged” burner account.
Step 2: Find your competitor’s Twitter handle(s)
Simple but important. Get the exact @handles for your competitors. If you’ve got a list, great—start with one or two. Don’t try to scrape 20 accounts at once unless you want to hit rate limits and CAPTCHAs.
Step 3: Use Texau to scrape followers
Here’s where Texau comes in. It’s an automation platform that lets you run “recipes” (think: little workflows) for scraping and other repetitive tasks. Here’s how it works for Twitter followers:
1. Log into Texau and find the right automation
- Once you’re in Texau, search for “Twitter Followers Extractor.”
- This “spice” (Texau’s term for a single automation) lets you pull a list of followers for any public Twitter account.
2. Set up your input
- Enter your competitor’s handle (no @ needed).
- Decide how many followers you want to scrape. Texau lets you set limits—if your competitor has 100k followers, start small (a few thousand max), or you’ll run into API restrictions and possibly slow down your account.
3. Connect your Twitter account
- Texau needs a Twitter session cookie to run this automation. They have a browser extension to help you grab it.
- This is basically a way for Texau to pretend to be you while scraping, which keeps things less suspicious to Twitter.
4. Run the automation
- Double-check your settings, then hit “Run.”
- Depending on the number you set, this can take a few minutes or a few hours. Texau will spit out a CSV file with data for each follower.
What you actually get
Expect the basics: Twitter handle, display name, bio, follower/following counts, location (if set), profile URL. Not every field will be filled out (lots of people leave bios blank), but it’s plenty to work with.
Step 4: Clean and prep your data
Congrats, you’ve got a CSV full of strangers. Now, let’s turn that into something useful.
1. Open your CSV in a spreadsheet
- Google Sheets is fine, but for huge exports (tens of thousands of rows), Excel or a desktop program is better.
2. Delete junk columns
- Texau sometimes includes columns you don’t need (like timestamps or irrelevant IDs). Strip it down to: handle, name, bio, location, and URL.
3. Filter out obvious spam/bots
- Sort by follower count or bio. Accounts with no profile photo, no bio, and weird handles? Probably bots. You can skip analyzing those.
4. Optional: De-duplicate or cross-reference
- If you scrape multiple competitors, look for overlaps—these are the super-engaged folks in your space.
Step 5: Analyze for insights (without overcomplicating it)
This is where most people get stuck. You don’t need to run fancy machine learning models. Here’s what actually helps:
1. Look for keywords in bios
- Filter or search for terms relevant to your product, industry, or target audience (e.g., “founder,” “SaaS,” “crypto,” “marketer”).
- Make a tally of how often these words pop up. This gives you a sense of what people care about.
2. Check locations
- Are they clustered in certain cities or countries? Maybe your competitor is big in Germany and you didn’t realize it.
3. Follower counts
- Who are the “power followers”? Sort by follower count to find influential people. These are good targets for networking or outreach.
4. Profile URLs/websites
- Sometimes people link to their business or personal site. Click through a random sample. Are they agencies? Solopreneurs? Journalists?
5. Engagement check
- Not all followers are equal. Spot-check a few handles to see if they actually engage (likes, replies) or if they’re just passive.
What not to obsess over
- Don’t worry about “sentiment analysis” or trying to categorize every single follower. You’re looking for useful patterns, not statistical perfection.
Step 6: Put the data to work
Having a CSV is cool. Doing something with it is cooler.
1. Make a “hot list” for outreach
- If you see people who fit your ideal customer profile, add them to a new list.
- Personalize your outreach—don’t spam them with generic DMs.
2. Plan content based on patterns
- If most followers mention “remote work” in their bios, maybe that’s a topic worth tweeting about yourself.
- Use topics and hashtags you see in their bios or tweets.
3. Build a lookalike audience for ads
- If you’re running ads, you can upload Twitter handles (or find emails via other tools) to build a custom audience. Twitter’s ad platform is hit-or-miss, but this can help you target the right crowd.
4. Track over time
- Redo the scrape every few months. See if the competitor’s audience is changing. Are they attracting new types of followers? Losing old ones?
Pro tips, warnings, and what to ignore
Don’t get greedy: If you try to scrape 100,000 followers in one go, Twitter will notice. Go slow, and rotate which accounts you use for scraping.
It’s not 100% accurate: Bios change, bots slip through, and people fake locations. Use the data as a guide, not gospel.
Ignore “follower quality” scores: Some tools try to rate how “valuable” each follower is. These are mostly guesswork. Stick to what you can see.
Don’t spam people: Seriously. Twitter’s spam filters are ruthless, and nothing turns off a potential customer faster than a cold DM that screams “robot.”
Texau isn’t magic: It’s a tool, not a strategy. The real value comes from what you do with the data—not the data itself.
Wrapping up
Scraping competitor followers on Twitter isn’t rocket science, but it does take some patience and a willingness to dig. Don’t overthink it: grab the data, look for a few actionable patterns, and test your ideas. If you keep it simple and iterate, you’ll get more value than most “growth hackers” who obsess over dashboards but never actually talk to a real person.
Take what works, ignore the rest, and get back to building real connections. That’s where the good stuff is.