Twitter And IBM Unveil 1st App To Analyze You and Your Tweets

The first fruits of IBM’s partnership with Twitter were unveiled this week, with new services announced to help businesses pull insights directly from tweets.

The service will allow developers to access Twitter APIs, mine the data and then use IBM’s analytics tools, including AI technology Watson, to scour them for solutions to business challenges.

Twitter’s vice president for data strategy, Chris Moody, said “Twitter is the world’s best focus group, we’re a data gold mine – we know a lot about the world and a lot about customers.”

Over 100 firms have already taken part in trials of the Insights for Twitter service, which uses IBMs custom BigInsights Hadoop framework running on its Bluemix cloud platform.

IBM is said to have trained 4,000 data science staff to work alongside businesses to help them use Twitter’s data to solve their problems.
6,000 tweets are published every second – the service is based on the principle that an awful lot can be learned about the people making those tweets, if they can be structured in a useful way.

The companies involved in the early testing of the product have not been named, but IBM gave several examples of the kinds of insights which have been unearthed.

These included a communications company which was able to reduce customer churn by 5% by predicting where customers were most likely to be affected by loss of service due to bad weather.

Also mentioned was a food and drink retailer which discovered that high staff turnover was one of the factors which negatively affected the value of their most loyal customers – leading to the discovery that “the human touch matters most to you most loyal customers”, in their own words.

Twitter is reported to have generated $47 million in revenue during the last quarter by selling its data.

IBM is not the first company to offer analysis of social media sentiment, but it is one of the few to have full access to the “firehose” of 6,000 tweets per second in real time. And it is the only one which allows them to be analyzed through the lens of Watson – its sophisticated natural language-based analysis engine which was initially designed to answer questions on the game show Jeopardy!

In theory this means you should be able to ask a question in standard English such as “How many people who mentioned us on Twitter today are going to be eating out tonight?” and expect a reasonably sensible answer.

IBM’s global leader of big data and analytics, Glenn Finch described the initiative as “an unprecedented partnership between IBM and Twitter [that] helps businesses tap into billions of real-time conversations to make smarter decisions.”

Plans include integrating Twitter data with IBM’s customer engagement system ExperienceOne, as well as developing solutions tailored to various industries such as banking, retail and travel.

My prediction is that this won’t be the last big partnership we hear about between social media and big business. As social becomes more and more integrated into the lives of everyday people, the volume (and value) of the data we share will continue to grow.

Twitter – where almost all conversations are effectively held in public – is easier to mine than most, and its ongoing status as the second most popular social media network cements its value.

No mention is made, however, of whether analysis of Twitter’s non-textual information is possible. Although most people use Twitter to post text, it has allowed video and photos to be posted for a while, and image-led social services such as Instagram are catching up with Twitter and the daddy Facebook in terms of user numbers and posts per day. The next natural step (which is already being taken) is to develop technologies for analyzing images and videos to draw out clues on what we like and what we spend our money on.

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About : Bernard Marr is a globally recognized expert in big data, analytics and enterprise performance. He helps companies improve decision-making and performance using data. His new book is Big Data: Using Smart Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance'.

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