Firms should tap customer social chatter

SINGAPORE--Consumers no longer trust their vendors to help them make decisions on their IT purchases, choosing instead to rely on recommendations from fellow consumers via social networking sites. This trend marks an area that businesses will do well to understand and capitalize to improve their customer links, according to Oracle.

Anthony Lye, Oracle's senior vice president for CRM (customer relationship management), highlighted consumer conversations on social networks as one area he hopes the business community will address soon with future CRM offerings from software vendors such as Oracle.

Elaborating on this concept of "customer-to-customer (C2C) relationships", Lye categorized such relationships into "explicit" and "implicit".

"Explicit relationships are people we know and trust on social networking sites such as LinkedIn and Facebook, while implicit relationships are those that involve strangers who will never find out their identities but have similar buying patterns and product likes and dislikes," he said during a press briefing here Tuesday.

Asked if Oracle will introduce more social media features into future CRM products, he said the company has "a number of proof-of-concepts in the pipeline" but declined to elaborate on these.

Lye added that the use of social media in CRM has "big potential [and] characteristics" of being a disruptive technology.

Managing social media chatter
However, it remains challenging to bring such "unstructured data" from social media networks into a structured enterprise environment.

Keith Collins, senior vice president and chief technological officer at SAS Institute, told ZDNet Asia in an interview Tuesday that organizations are looking to business analytics to understand the context of what is being said in the social media space.

Asked how SAS plans to sift out inane chatter from constructive, business-related feeds found in these social networks, Collins pointed out that this is possible "if we can model dialogue and documents" over a period of time to discern significant patterns and filter out topics companies are not interested in.

The problem, though, is that companies are being overloaded with data on a daily basis and it is difficult to trawl through all the information using old business rules, he said. These conventional rules are "old, stale [and] prompt false alerts", he added.

To counter this, the SAS executive said companies need to implement "smart filters" to access the information they need.

Citing lessons learnt from the manufacturing sector in the 1980s, Collins said the key to creating such filters is in understanding how "valid statistical variants" should be attached to information being churned out by the various social networks.

"The question is whether the variants seen in the information are statistically important...such as to determine whether the variants are cyclical due to the four seasons, for example. If we can filter all these out, then we can see what the outlier in the process is and take action," he explained.

Ultimately, he said the process of sifting through social media channels to identify business-critical information requires a change in the thought process of applying technologies that already exist to a new area of managing information.

Shift to business analytics
In terms of how companies analyze useful data to make informed business decisions, Collins noted that there is a "big shift" from business intelligence (BI) to business analytics (BA).

"We're going to see an increased adoption of software-as-a-service (SaaS) in terms of targeted business analytics solutions, while there will be a decline in adoption for BI SaaS, which we think is a dead market," he predicted.

Shanmuga Sunthar, head of technology practice and public sector at SAS Institute Singapore, said that companies are moving away from deploying BI software because it simply collects and reports data and choosing instead to implement BA.

"Companies are increasingly making use of business analytics techniques to find out what is the hidden value and challenges within the data they have collected, which is a capability that BI does not offer," added Suntha, who sat in on the same interview with Collins.

He added that the BA market is predicted to increase significantly, with the Asia-Pacific region expected to see a 30 percent increase in enterprise adoption this year.

He also cited an IDC study which stated that the global business analytics software license and maintenance revenue clocked US$24.1billion in 2008 and is expected to grow to US$34.2 billion in 2013.

Collins urged companies to avoid following the "hype" of BA and jumping into the bandwagon blindly. "Adoption is not just buying a technology but about knowing how to use the tool to target and solve specific business-related problems, and this applies to business analytics as well," he said.