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Daily CX updates for the Oracle EMEA CX partner community

Big Data for Social Requires Fast Data…So Oracle Did That

Richard Lefebvre
CX Partners programs Director
We know the goal.  Acquire big data,
then use it to deliver just the right messages to customers and
prospects at just the right time, in just the right place, in just the
right way. Easy, right?

Of
course not. If it were easy, all brands would be on their game,
delivering these perfect and profitable customer experiences every day.
If I had been browsing guitar amps lately and I was near a guitar store
this weekend, I’d get a social message to the effect of, “Hey, we saw
friend x recommended brand y guitar amp to you. Swing by and we’ll give
you 20% off on it. Rock on.”

That
kind of experience rarely happens to me (maybe because I don’t play
guitar). For those to happen, social big data, combined with other
public and enterprise data, needed to “learn” what I was seeking and
which brand I was leaning toward due to peer-to-peer recommendation.

Then,
it had to retain and “know” that info so that when a real-time location
signal came through, that knowledge could be tapped and leveraged to
create and deliver the message before the moment is lost. It not only
requires big data, it requires fast data.

All
social marketing ecosystems are not created equal. Few are capable of
the size and speed of data gathering, processing, filtering and delivery
that makes a social enabled enterprise even possible. A social
marketing platform that can tap into the kind of size and speed Oracle
can serve up would position you exceptionally well against your
competition.

On June 10, Larry Ellison announced the Oracle Database In Memory
Option, an add-on to the Oracle 12c database that super-boosts
real-time analytics and transactional workloads. How much of a
super-boost? Real-time analytics queries that are 100x faster and online
transaction processing that’s twice as fast. It’s possible because your
most important info can be held in dynamic random-access memory (DRAM)
for instant access. And data can be stored in both the columns needed
for analytics and the rows used for transactions.

Big
data that lags behind the customer’s speed of life doesn’t do you much
good. They’re out there right now, researching and buying on mobile.
Half of all local searches are performed on mobile. eMarketer estimates mobile commerce sales should go over $113 billion by 2017. Mobile use continues to explode and digital payments are only getting easier to do.

The future of the enterprise is this: a massive shared customer data pool
continuously pulling from multiple data sources, available to all
business functions for insight and action in perfect alignment so
customer interactions aren’t carried out in department silos, generating
metrics that inform against varied business goals and can be turned
around for real-time, on-location customer engagement and conversion.
Wowsers.

Will you be able to handle that coming big data volume as well as the need for speed?

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