I published a post a few weeks ago describing how to build your own twitter custom audience list, outlining a variety of techniques to build up your list.
This post outlines another method (hat tip to Ade Lewis for the idea) which requires you to scrape Twitter directly.
If you want to skip all the explanations and just want to download the Twitter List Scraper tool, here you go…
Download the Twitter Scraper Tool for Windows or Mac (completely free)
Disclaimer: Scraping Twitter is against their Terms of Service, so if you decide to do this you do it at your own risk.
Some Benchmarks
Building custom audiences on Twitter requires you to identify Twitter usernames that might be interested in your service or product.
In my previous posts, one of the methods I employed was to pull a competitor’s link profile and scrape social accounts from the linking domains.
Once you upload a custom list, Twitter goes through a process of ‘matching’ against profiles in their system, to make sure the user exists and hasn’t opted out of tailored ads.
As our data was scraped from a list of unqualified websites, the data matching wasn’t likely to be perfect.
Experiments
Since I published that post, I have been experimenting a fair bit with list building, and have built up around 10 custom audience lists. I‘ve uploaded a total of 48,857 Twitter usernames using this method, but only 29,260 were matched by Twitter (just less than 60% match rate).
From some other experiments where I have had better control over the input data, this match rate was between 70-80%.
Since we’ll be scraping Twitter directly, I expect our match rate to be much higher – 90%+
Finding Relevant Twitter Lists
So, we’re going to scrape Twitter, and the first step is to find Twitter lists that will contain users potentially interested in what we have to offer.
As an example, we’ll pretend we’re marketing a music website, and we’ve produced a survey we want to collect responses for.
An advanced Google query can give us lists of music bloggers: site:twitter.com inurl:lists inurl:members inurl:music “music blogger”
Source: http://urlprofiler.com/blog/scraping-twitter/
This post outlines another method (hat tip to Ade Lewis for the idea) which requires you to scrape Twitter directly.
If you want to skip all the explanations and just want to download the Twitter List Scraper tool, here you go…
Download the Twitter Scraper Tool for Windows or Mac (completely free)
Disclaimer: Scraping Twitter is against their Terms of Service, so if you decide to do this you do it at your own risk.
Some Benchmarks
Building custom audiences on Twitter requires you to identify Twitter usernames that might be interested in your service or product.
In my previous posts, one of the methods I employed was to pull a competitor’s link profile and scrape social accounts from the linking domains.
Once you upload a custom list, Twitter goes through a process of ‘matching’ against profiles in their system, to make sure the user exists and hasn’t opted out of tailored ads.
As our data was scraped from a list of unqualified websites, the data matching wasn’t likely to be perfect.
Experiments
Since I published that post, I have been experimenting a fair bit with list building, and have built up around 10 custom audience lists. I‘ve uploaded a total of 48,857 Twitter usernames using this method, but only 29,260 were matched by Twitter (just less than 60% match rate).
From some other experiments where I have had better control over the input data, this match rate was between 70-80%.
Since we’ll be scraping Twitter directly, I expect our match rate to be much higher – 90%+
Finding Relevant Twitter Lists
So, we’re going to scrape Twitter, and the first step is to find Twitter lists that will contain users potentially interested in what we have to offer.
As an example, we’ll pretend we’re marketing a music website, and we’ve produced a survey we want to collect responses for.
An advanced Google query can give us lists of music bloggers: site:twitter.com inurl:lists inurl:members inurl:music “music blogger”
Source: http://urlprofiler.com/blog/scraping-twitter/
No comments:
Post a Comment