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Crawling Your Social Shares: Social Crawlytics

25th July 2012 by Jennie Stamp | News & Events

This week I have been investigating Social Crawlytics. A new tool from Yousaf Sekand (@ysekand) that scans web pages and produces reports detailing the statistics of sharing across a range of social media.

How does it work?

Its simple, user friendly approach makes it a valuable tool for businesses small or large. Account creation involves two easy steps:

  1. Log in using your Twitter account
  2. Receive credits to create reports
    • No money involved, choice of three plans:



Social Crawlytics is a free service so the way the platform operates is by using a credit system. Upon account creation, you receive 2000 credits to get started. The credits are refreshed weekly, 1500 each week.

How to acquire more credits?

One way to obtain more credits is to allow them to advertise themselves by posting a tweet on your behalf, this will give you 800 credits each time. This can’t be modified, as soon as you click the ‘Post A Tweet For Me!’ button, the tweet is sent:


On the site, they state: ‘While we don’t have any paid plans, if you wish to use our system extensively then please feel free to contact us and we can come to an arrangement.’ This is the Enterprise plan.


To get started, you are asked to submit your desired website address. Multiple addresses can be submitted depending on the number of credits you have.


The details:

  • Pages on your chosen site that are not HTML, or over 2MB can’t be searched by the crawler. However, the number of shares they’ve had will still be reported on.
  • Be selective with which websites you add as credits will be deducted each time. Once the credits are taken, it can still take ten minutes for your report to be produced.


A clear and concise summary details the total numbers of social shares, pages added to the report and pages scanned. The example report in this article scanned SEOmoz, therefore producing extensive analytics.


This simple graph displays a combination of all social shares across various platforms. Each colour represents a page on the scanned site, hovering over each section will display the exact details.

Shares are broken down further in the content type graph to provide more detailed data. The sunburst represntation chart requires the user to click on it to explore the data it holds. Explanation next to the chart, describes how it gives the users a great visual view of how their shares are split up when approaching from a search engine’s point of view. The centre represents the first page, and each segment beyond it are pages linked from that page. Segments beyond that are linked to their parent. Pages with no shares are not included or shown.

Below these visual representations are the raw results along with a handy search function. This is useful for a quick glance at numbers.

Finally, a detailed results table displays the raw data in a page by page view. This is just a small snippet:


Overall, a clean, simple design that produces useful and manageable social analytics to allow organisations, bloggers, brands etc. to view and examine how each invididual web page is being shared via social media.

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