Twitter built in to the Cloud

Twitter is like no other data source in the world. It is a real-time, public, conversational and global information platform where voices from around the world are speaking about every topic imaginable. 

But for business professionals to do more than social listening – to be able to use Twitter data to inform their organization’s most essential decisions -– they must first isolate the signal from the noise. IBM does this by enriching and analyzing Twitter data in combination with millions of data points from other streams of public and business data – such as weather forecasts, sales information and product inventory stats – to uncover powerful correlations that drive more actionable insights.

“So much of business decision making relies on internal data such as sales, promotion and inventory. Now with Twitter data, customer feedback can easily be incorporated into decision making,” said Chris Moody, Vice President of Data Strategy at Twitter. “IBM’s unique capabilities can help businesses leverage this valuable data, and we expect to see rapid demand in retail, telecommunications, finance and more.”

The new IBM analytics services on the cloud will help businesses and developers:

· Create Social Data-Enabled Apps: Developers and entrepreneurs can search, quickly explore and then mine enriched Twitter content and aggregated insights through IBM’s Insights for Twitter service on Bluemix.

· Merge Sophisticated, Predictive Analytics with Twitter Data: By automating the steps of data curation, predictive analysis and visual storytelling, Watson Analytics can give business professionals the ability to immediately pull Twitter data into any project in order identify and explain hidden patterns and relationships to accelerate the understanding of why things happen and what's likely to happen.

· More Easily Analyze Twitter Data: With select cluster configurations of BigInsights on Cloud pre-configured with access to Twitter content, clients can combine Twitter data with IBM’s full-featured Enterprise Hadoop-as-a-Service offering also available through IBM Bluemix.

More than 4,000 IBM professionals now have access to Twitter data and are trained to enrich the data with analytics capabilities from IBM industry solutions and cloud-based services.

New Social Insights from IBM and Twitter Drive Better Business Decision-Making

IBM and Twitter offer enterprises an unprecedented edge to empower business decisions through the combination of Twitter’s vast and unique overview of what the world is saying together with IBM’s unrivaled analytic power to create actionable insights for business decision-makers. Here are the top three social insights drawn from over 100 early engagements:

1. Geography is Not Destiny: It’s a global economy, but we’re all still very local. Geographic areas can show significant variance in churn even across subscribers in the same marketing segment with the same data history.

Most subscription-based telecommunications and media companies that are subject to high churn rates have developed sophisticated analytic models to understand and predict customer turnover. What's not well understood is the influence of factors like weather or other point-in-time events, within defined geographic areas. By combining Twitter data with other information like rain, wind or snow that triggers service interruptions, IBM identified the correlation between weather events, angry Tweets and customer defections. By helping analyze localized Twitter data combined with weather data, IBM can significantly improve churn models – in some cases by 5 percent – and help a client take actions to minimize turnover.

2. The Inside is the Outside: Employee turnover within retail businesses directly affects your most loyal customers. What happens privately inside your four walls often goes public via social conversations. There are no more closed doors.

IBM analytic models have shown that consumers value, and Tweet about, the relationship they build with sales associates, particularly in food service where individual tastes and preferences are important. Once a relationship is removed consumers also Tweet, but this time expressing a sense of loss for the relationship and their dissatisfaction with having to ‘start over.’ IBM looked at Twitter data along with loyalty information and the financial performance of different stores and restaurants. Not only did dissatisfaction with employee turnover impact sales negatively, the dissatisfaction was most keenly felt by the most loyal (and valuable) customers. In one study the impact was highest with a consumer cluster that represented just 3.3 percent of the total customer population (over six million in the loyalty program) –yet these customers have some of the highest gross margins for the retailer and shop virtually every day.

3. Fashion Forward with Social Insight: Twitter is an effective demand signal for the apparel industry because as focused as it may be on individual commentary, this creates a compelling picture of worldwide trends.

Manufacturers want to know what products to make and when, but constantly changing retail trends and habits make it harder to understand and respond to demand. IBM found that Twitter is a valuable indicator of demand for the apparel industry and other manufacturers. By using psycholinguistic analytics from IBM Research to extract a full spectrum of psychological, cognitive and social traits from Twitter data that influential fashion bloggers generate - combined with operational data such as sales and market share information - manufacturers can better understand why some products sell well while others don't. They can also improve merchandising strategies and provide input to future product development.

“The unprecedented partnership between IBM and Twitter helps businesses tap into billions of real-time conversations to make smarter decisions,” said Glenn Finch, Global Leader of Big Data & Analytics for IBM Global Business Services. “Through unique expertise, curation and insights Twitter data is now able to inform decision-making far inside organizations.”