Databases Reference
In-Depth Information
●
Metrics processing
●
Dashboards
●
Mashups
●
Heat maps
●
Clustering
●
Statistical
Why do we need these entire complex processing steps? The companies could have purchased
third-party data from aggregators like Nielsen Buzzmetrics and integrated sentiments and trends into
their data architecture. But the contexts of the sentiments, the categorization of the trends, and the
ability to reprocess the data for several business situations will be near impossible because the data is
already qualified and presented as metrics. To leverage the complete knowledge provided by the dif-
ferent touchpoints of data, these organizations have processed most of the steps outlined above and
some more in certain situations.
Let us say we have third-party data and it provides the following:
●
Number of posts
●
Channels posted
●
Sentiment tone by topic
●
Word clouds
●
Latitude, longitude, and geographic data
●
Demographic data
●
Social media user identification:
●
Twitter handle
●
Facebook user name
●
Any other user identification
●
Influencer status:
- Peer index
- Klout score
- Likes
- InShare
- ReTweets
- G+ score
●
Opinions:
●
Percentage of tones:
- Positive
- Negative
- Neutral
●
Category of subjects
●
Direct versus indirect sharing
While integrating all this data is a huge step in connecting the customer behaviors, sentiments,
and trends, the unfortunate scenario here is the lack of an integrated approach. The customer senti-
ment expressed in the conversation is not categorized based on the context of the event, and here is
the gap that needs to be addressed.
