Recently I've been doing
quite a bit of analysis work using the IBM Watson cognitive business platform. The really exciting thing about this
opportunity is the way data can seem to have a conversation with you.
This got me wondering if social media data could carry on a conversation
as well. Given my almost unhealthy interest in cloud computing, we ran a
one week experiment to "crowdsource the internet" in order to see if it
held any interesting cloud computing insights . To narrow the volume of documents down to a
reasonable number, I limited providers to those on the most recent Gartner IaaS Magic Quadrant:
- Microsoft
- Amazon Web Services
- Google
- VMware
- IBM
- Rackspace
- Verizon
- CSC
- Interoute
- CenturyLink
- Dimension Data
- Fujitsu
- Joyent
- NTT Communications
- Virtustream
Leveraging Watson, I gathered cloud computing related social
media documents. According to Watson, in
one 24-hr period, there were 46,869 documents that mentioned these Cloud
Service Providers (CSP) a total of 57,997 times. Google was totally dominating
the online conversation with 73% of all mentions. Microsoft was a poor second
at 17%.
Figure 1-
Social media cloud computing "Share of Voice"
|
At this this point I
took a look at overall industry sentiment. From this vantage point, Interoute
outshines all rivals for positive sentiment.
Of particular note, however, was that Dimension Data simultaneously held
the crown for largest percentage of negative and lowest percentage of positive
sentiment (which seems to be centered mostly around the dropout of a rider from its Tour de France team and a recent internal restructuring). The Dell/EMC cloud provider Virtustream doesn’t even seem to be
present in social media conversations.
Figure 2- Customer Sentiment Regarding Cloud Service Providers |
Microsoft dominated that segment of the conversation that specifically
addressed the three standard cloud computing service models
(Infrastructure-as-a-Service [IaaS], Platform-as-a-Service [PaaS],
Software-as-a-Service [SaaS]). Over 53% of the working set referenced Microsoft
with second place AWS coming in at 13.5%. Software-as-a-service is the
unsurprising overall service model leader but Microsoft seems to be edging out
AWS for Infrastructure-as-a-Service mentions.
Platform-as-a-Service is a distant laggard with only three providers
(Microsoft, AWS and VMware) represented in social media exchanges.
In order to glean some
business value, the documents were binned across thirteen industry verticals
and analyzed for share of voice and author sentiment. The initial industry bins
were:
- Construction
- Manufacturing
- Wholesale trade
- Information technology
- Retail trade
- Utilities
- Financial services
- Educational services
- Transportation and warehousing
- Entertainment, accommodation, and food services
- Healthcare and social services
- Public administration
Across this set, entertainment,
government, education and healthcare industries seem to be most interested in
the cloud. Surprising to me is that the construction industry interest
surpasses that of financial services. Google seems to be driving industry
related social media conversations with Microsoft and IBM rounding out the top
three.
Although I wouldn’t use this non-scientific experiment to make any big
bets, it does demonstrate how actionable data can be gleaned from the social
media stream. It may also shed a little
light on the power of cognitive computing in the business world.
One especially intriguing capability that I didn’t use in this
experiment is the use of Watson
Explorer technologies with Semantic Analytics. This solution is currently being used by IBM
GTS to deliver “built to purpose” cognitive systems for the information
technology industry vertical.
Figure 5- Cloud Service Provider Industry "Share of Voice |
A key differentiator of
this approach is its ability to extract meaning from the fragmented sentences normally
found in unstructured IT service ticket description fields. Due to the global
nature of GTS Services, this unstructured text is typically in multiple
languages. Additionally, due to the different language skill levels of the
globally sourced pool of agents, the grammar quality varies. This solution is
used by GTS to uncover patterns and trends in the identification of
contributing incident causes in order to prescribe appropriate preventative
actions.
This post was brought to you by IBM Global Technology Services. For more content like this, visit Point B and Beyond.
( Thank you. If you enjoyed this article, get free updates by email or RSS - © Copyright Kevin L. Jackson 2015)
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