On 11 June 2015 Dick Costolo resigned as the Chief Executive Officer (CEO) of Twitter Inc. Several reasons may explain his departure from one of the world’s key companies in developing social media networks. And in its re-launch, data analytics will very likely have a prominent role.
Frustrated economic expectations
Costolo has been unable to prevent the steady decline in the value of Twitter since being listed on the stock exchange in November 2013. A price drop from 73 dollars per share in December of 2013 to 35.84 today
At Twitter Costolo focused on innovations to ensure maximum user comfort. He drove the acquisition of Vine for the production of limited duration videos. As well as Periscope in an effort to achieve direct audiovisual broadcasting. However, his strategies for attracting and retaining users was poor.
One of his weak points, as business model for investors, was the company’s growth expectations in the number of users for the following years. Para 2015 ésta red crecerá según estudios un 14,1%; situándose para 2019 en apenas un 6%. Chris Sacca (uno de los principales inversores en Twitter) apunta en esta dirección, afirmando que mil millones de personas han probado la red social y la han abandonado poco después la misma.
One of his weak points, as business model for investors, was the company’s growth expectations in the number of users for the following years. However, results have fallen short of expectations. According to market research studies it was estimated that Twitter’s base would only grow 14% in 2015, and by 2019 it would grow a meager 6%. Chris Sacca (one Twitter’s main investors) pointed in this direction, saying that a billion people have used the social network and have abandoned it shortly afterwards.
Advertising revenues have been another point of bitter criticism. Providing direct advertising messages (Twitter Ads) via a link to the advertiser’s website is not proving to be as attractive as expected by the company.
The number of clicks on ads is low and different brands have gradually reduced their investment in this advertising platform. Google’s market share of global advertising is 31,42%, with Facebook controlling just 7,93%, while Twitter represents less than 1% (0,93%).
Considering all the above reasons, profits of between US $ 2,170M and $ 2,270M were expected for 2015, while according to their own studies they were estimated to reach US $ 2,370M.
Data Analytics as advertising key?
Leaving aside issues such as the elimination of their famous 140 character limit for direct messages and new developments, Twitter still has much room for maneuver in the advertising field. The thing is this social network has a huge potential in a fundamental aspect: the vast amount of data it generates daily (over 400 million tweets are sent daily worldwide).
Companies of research and analysis working online have already been able to derive benefit from the generated information since the advent of Twitter, in terms of market research and for consumers. It has also enabled direct communication between companies and users, such as a direct communication service for their complaints and comments, as well as a way to feel the pulse of “social interest” in their publications and advertising actions being carried out continuously.
Therefore, applying Data Analytics can mean not only redefining Twitter’s advertising possibilities; but also creating a more personalized offer and with a greater chance of success for the interested advertisers.
Advertisers and agencies could, through the Twitter data, analyze user profiles, important for different reasons (number of followers, retweets …) and in some way connect them with the products and services being advertised. These advertisers could make payments in exchange for direct advertising messages inserted in these profiles. In this way enhancing possibilities of knowledge over the offer made through the broad follower base which those users have; as well as the “prestige” that represent their publications and profiles in Twitter.
Thus improving the chances of success sought after in different campaigns. It would also allow followers to know how many followers of these profiles are accessing commercial offers or perform sales conversions. And consequently better understand the effectiveness of Twitter as a social channel for advertising investments
In turn, conducting studies at the semantic level on publications and feedback generated between advertisers and users. And then proceeding to classifications over the generated activity, interest trends through publications, behavioral interpretations etc.; this could generate a greater understanding of the target audience of brands and advertising campaigns
In short, the use of Analytics means increasing the possibilities of Twitter as a source of advertising revenue and allowing us to demonstrate its viability as a social channel with advertising and marketing possibilities. And this, not only for the company itself but also for those companies that maintain active profiles and that interact continuously. Since the data obtained, studied and applied correctly, represent an opportunity of Business Intelligence hardly objectionable by any of the parties involved.