IBM’s Customer Experience Lab has just announced the release of three new pieces of technology in the areas of in social, mobile and big data. Collectively, they offer deep insights into customer behaviors, particularly around purchases.
Customer Experience Labs
You may recall in March that the Customer Experience Lab (CEL) was originally opened to try and optimize customer experience for brands and services and, in doing so, develop ways to individualize customer experiences and find patterns in they way products are consumed.
IBM proposed to discover all this information using technologies that it has already developed, or bought, particularly big data analytics, but also mobile, social and cloud technologies.
While the move towards developing personalized experiences for customers is an established one, IBM is taking a scientific approach to it and some of the progress it has made already appears impressive.
New Innovation Lab Products
The three products that IBM unveiled today were developed in the CEL in India (the principal lab is in New York, but it has 12 support labs all over the world). They are built around the work the India team did on the Watson Engagement Advisor.
The new products include:
1. IBM Edge Analytics
This is a non-intrusive technology built on IBM’s iLOG and SPSS software. It takes users’ locations and cross-references them with daily financial activity, like buying airline ticks, or supermarket shopping. Client companies can then send contextual promotions, or other information, by email.
With the IndusInd Bank in India, which IBM cites as an early adopter, it has been able to analyze all the customers' financial records with other banks, and then make competing offers that could result in customer wins.
This is only a newly developed technology that helps Chief Marketing Officers target customers working in specific industries. It does this by analyzing their interactions on social networks associated with a particular business, and then cross-referencing that interaction with their purchasing patterns with that business.
IBM cites the example of Facebook sites. It says that Vibes can research the purchasing history of users of a Facebook site to determine their interests and what they will respond to.
3. Social Media Event Tracker Tool (SMETT)
This uses text mining and advanced analytics to drill down through social network messages to find insights into customer behaviors and their opinions about a subject or product. It can do this in any language and contextually relate a number of different topics to find out why a product is popular, or how to improve it online.
While the concept of trying to identify customer behaviors and respond to them is not exactly new, the range of technologies that is being used is very advanced.
It is not clear, when, or even if at this stage, any of these products will become commercially available, but as a sign of what’s to come from CEL, it looks promising.
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