LONDON February 1, 2011 http://www.stockopedia.co.uk/ http://www.stockopedia.co.uk/page/readership-analytics-for-publishers/
Publishers on Stockopedia contributors now have access to a personalised dashboard allowing them to view real-time readership statistics across all their published content. Features include the ability to track and chart readership details across different timeframes and versus their average performance. Publishers and subscribing companies can track the level of investor engagement with their content and any social media reactions aggregated from across the web.
Croft added: "Our objective is to give our authors the same level of insight and feedback as if they published the content on their own blog or website. We partner with top names in the financial world – including research houses, video producers, fund managers and bloggers – and it’s important to ensure they maximise their return on investment in creating and syndicating content. We believe that this is the most granular analytics system available for financial publishers on the web."
The Publisher Analytics platform leverages MongoDB, a document-oriented database adept at handling high volumes of information, well suited for large scale data processing and most famously used at CERN for handling data generated by the Large Hadron Collider.
Stockopedia is now experimenting with using its data processing systems to build recommendation, categorisation and discovery features that mine all the latest financial news and commentary across the UK stock market.
Croft concluded: "As part of our mission to level the information playing field, we partner with financial publishers and investment bloggers to help them reach the broadest possible audience through Stockopedia and the wider Web. We see our Publisher Analytics platform as a key part of this partnership and are excited to be able to provide them with this new functionality".
Stockopedia uses sophisticated information discovery and categorisation techniques to aggregate and index data to build real time streams based on individual user’s personal investment interests, driving considerable incremental viewership from engaged users to its contributing publishers. The company’s engineers work with cutting edge tools for large-scale data collection, processing, text parsing, search indexing and information retrieval.
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