IBM’s Twitter partnership could charge US$2,000 per 1m analysed tweets

19 Mar 2015

Last October, IBM and Twitter teamed up for an entirely new class of analytical data. Now, they will charge US$2,000 for every million tweets they crunch.

The pair have announced the full roll out of their “industry-first” service, that will let people “extract actionable business insights” from Twitter use.

Following a successful trial of the tool with 100 businesses in the lead up to the release, IBM seems pretty confident that the results it can garner from analysing Twitter will be worth big money to clients.

“The first access to Twitter data is free, then it’s pay as you go,” said IBM’s Alistair Rennie at Cebit. In fact, the first five million Tweets analysed are free, before a charge of US$2,000 per million, per month.

This is the first forward step since the partnership between Twitter and IBM was established last October. Back then they announced three elements were in the works.

There would be a new data-intensive capabilities for the enterprise, they would establish a specialised enterprise consulting and collaboration between the two companies, and they would release an integration of Twitter data with IBM analytics in the cloud.

It is the latter that has come to fruition first, it seems.

“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, VP 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.”

On Tuesday IBM and Twitter announced findings from the trial run with those 100 businesses, with quite surprising results. Firstly, they found out that bad weather is bad news for phone carriers who want to hang on to their customers. It seems rain, wind or snow leads to angry tweets and customer defections.

Secondly, they worked out that staff turnover in store means less loyal customers. “Not only did dissatisfaction with employee turnover impact sales negatively, the dissatisfaction was most keenly felt by the most loyal (and valuable) customers.”

Social media data, via Shutterstock

Gordon Hunt was a journalist with Silicon Republic