Twitter is extending its data-gathering and contextualization services to the banking and finance sector in order to boost opportunities from this new revenue stream.
When Twitter made its successful IPO towards the end of 2013, the company announced that it had earned $47.6 million from the sale of data, a slender amount compared with the revenues derived from its advertising activities. Today however the social network provider is continuing to widen its core business in this direction, seeking to monetize its huge data flows by providing input to innovative business indicators. Twitter made an interesting move late last year, setting up in collaboration with Nielsen TV Ratings indicator– the Nielsen Twitter TV Ratings, an audience-tracking tool that maps users’ social conversations about television programs and links them in real time with TV content. In a bid to mine value from the 400 million daily tweets on its network, Twitter is looking to forge more partnerships and has just signed an agreement with business information firm Thomson Reuters, whereby tweet sentiment analysis will be incorporated into the latest version of Thomson Reuters’Eikon market data desktop product, making it more intuitive for financial markets analysts and traders.
Transforming sentiment into actionable indicators
The Eikon software, which is mainly used by traders to provide them with up-to-date information on stock exchange investments, is regularly updated by Thomson Reutersso as to incorporate indicators deemed to have a bearing on financial markets. Under the new partnership, data from Twitter and investors’ and traders’ free social network StockTwits will be integrated, weighted and assessed on a rolling basis, using a tailored protocol, to provide sentiment analysis in relation to each publicly listed company. The feed will incorporate identified key influencers plus a broad cross-section of all tweet activity to provide a unique and powerful picture of global Twitter sentiment at any given time. The decision to launch this new version of the Eikon software, which keeps tabs on over 30,000 publicly quoted companies, reflects the growing trend towards behavioral finance, which seeks to createa more holistic viewof major capital flows than in traditional economic theory. According to Philip Brittan, Chief Technology Officer and Global Head of platform for Financial and Risk at Thomson Reuters: “The addition of this sentiment data […] is really just the tip of the iceberg in terms of what we plan to do to turn qualitative, unstructured text into quantitative and actionable insight for our customers.”
Twitter confirms its vision for Big Data and analytics
Twitter’s policy now seems to be to forge strategic partnerships for the purpose of developing new indicators designed specifically for key industries. Just prior to the announcement of its collaboration with Thomson Reuters, the California-based social network company announced a partnership with 300 Entertainment, a music industry firm founded by the former head of Warner Music Group. In fact music is one of the most discussed topics on Twitter and this pact – announced at the Midem event in Cannes – will see 300 Entertainment develop software which draws insight from a wide range of music-related data on Twitter, including non-public data such as the location from which tweets are sent. Meanwhile, in the field of business and finance research, Twitter also looks set to benefit from a recent decision by the U.S.Securities and Exchange Commission authorizing public companies to post official information on social networks as long as investors have previously been alerted as to which social media will be used to publish such information. Internal development at Twitter also looks likely to benefit from these new partnerships. Developing new tailored programs to respond to specific demand from various sectors will enable it to bolster its know-how in the face of competition from giant rivals such as Facebook and Google. Explains Twitter’s Head of Music, Bob Moczydlowsky: “Helping our clients to take business decisions pushes us to organize our data better than we might otherwise have done.”