What is Big Data?

Technological Tools Trends:
Prediction Models, Business Intelligence, Big
Data and Multichannel Communications
James Grace,
Contact Center Consultant
What is Big Data?
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What is Big Data?
• Big data is used to describe massive volumes of
both structured and unstructured data that is so
large that it is challenging to process using
traditional database and software techniques.
Can Big Data be an effective prediction tool? YES:
• Big data has the potential to help companies
improve operations and make faster, more
intelligent decisions.
• Big Data can be used to predict results with
reasonable accuracy.
• Big Data can be effectively used in scenarios with
multiple variables and situations lacking certainty.
How is Big Data relevant to
the contact center
environment?
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Using Big Data as a prediction tool:
• When dealing with larger datasets, organizations
face difficulties in being able to create,
manipulate, and manage Big Data. Big Data is
particularly challenging in business analytics
because standard tools and procedures are not
designed to search and analyze massive datasets.
Big Data’s accuracy in the prediction of desired
business outcomes:
• This data, when captured, formatted,
manipulated, stored, and analyzed can help a
company gain useful insight to increase revenues,
acquire or retain customers, and improve
operations.
What Customers Expect in 2014
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A consistent experience – not necessarily to consistently
reach the same person for each interaction (there is a
difference!).
The least path of resistance/effort during an interaction
– ease in doing business.
Organizations will look to address customer
expectations through:
• Unified communication models
• Unified view of the customer
• Unified knowledge and data.
Multichannel Customer
Expectations
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Customers channel entry:
• Customers expect the ability to enter using any channel
provided by an organization, and expect the ability to
change their entry preference at any time.
Movement between channels:
• Customers expect to be able to move between
channels, even within the same interaction.
Information flow between channels:
• Customers expected a seamless flow of information
between channels; no repetition of information already
provided.
Customers expect a universal experience regardless of
channel entry and the number of channels used.
Multichannel Customer
Expectations
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Multichannel Customer
Expectations
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60%
50%
40%
30%
20%
10%
0%
1 or 2 Channels
3 to 4 Channels
5 or More Channels
Source: October 2013, “Optimizing Customer Service in a Multi-Channel World”, Ovum report
Multichannel Access Points
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8.0%
7.0%
Channel Blending
30.5%
Inbound and Outbound Calls
Inbound Calls and Emails
Inbound Outbound Calls and Emails
20.3%
30.5%
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Inbound Calls and Web Chat
Inbound Web Chat and Email
85.2% of Contact Centers handle at least two media
types.
32.8% handle at least three channels.
10.2% up to 4 channels.
3.9% of centers answer 5 channels.
Source: Interactive Intelligence/Contact Center Pipeline,
March 2013.
Channel Growth
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Source: “Companies Dive Deeper Into Multichannel Customer Contact”, March 2013, Strategic Contact
Channel Growth
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Currently Using
Planning to
Implement
In Next 12 Months
Social Media Monitoring
40%
27%
Social Media Engagement
35%
26%
Web Chat
39%
27%
SMS/Text
22%
18%
Source: “The US Contact Center Decision-Makers’ Guide (5th Edition -2012)”, ContactBabel
Deciding Channels for
Deployment
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Research current and emerging trends in the industry.
Know what the competition is doing.
Know the demographics and behaviors of the customer
base.
Determine the corporate strategy.
Ask your customers what they expect.
Metrics for Multichannel
Management
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Challenges to Meaningful
Data Integration
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Fragmentation of efforts between different teams, tools
and data sources across multiple channels, brands and
regions.
Political and fiscal turf protection.
Multiple sales funnels.
Inability to identify the customer.
Inability to quantify the value of customer experiences.
Benefits to Data Integration
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Common Data Marketing Platform for reporting,
analytics, targeting and media integration.
A channel and customer view of success.
Metrics that measure the entire customer journey –
not just the parts.
Decision-making through actionable insights.
A common language for performance across different
teams, brands and markets.
Better use of the team’s time to focus on what matters
most to their business.
How does Big Data Support
Multichannel Deployment
& Management?
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Identify predictable customer
behaviors/patterns:
• Even in situations of change/uncertainty,
predictable patterns can be identified and
applied to current situations.
Aggregates data among multiple entry and exit
points.
Provides the basis for business analytics
Keys to success in
harnessing Big Data within
the Contact Center?
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From a technology perspective:
• Ability to process petabytes and exabytes of data
• Use of integrated platforms to share data across
applications.
From a Key Performance Indicator / Measurement of
Success Perspective:
• Organizations ability to define what constitutes
success.
• What is really important for you to know about
your customers.
More specifically, big customer data makes it
incumbent on organizations to:
• Fully understand the value of the data they are
capturing.
• Adopt a mindset to trust what their most valuable
data tells them.
• Develop fundamentally new strategies for
organizing and leveraging that data.
Big Data for Cross Channel
Success
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By visualizing customer data, patterns of behavior can be formed and conclusions
drawn, and this is where the real value of Big Data starts to become apparent. Now
organizations can introduce a wide variety of data to develop:
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Deep customer insights:
• Not just profiles, but insights into attitudes, behavioral habits, browse and
visit patterns, engagement indices and response scores.
Cross-channel personas:
• Brands can use deep segmentation (the greater the volume and variety of
data, the deeper the potential segmentation) to create rich marketing
personas that can be deployed across channels and are continuously
enriched by near real-time behavioral data.
Multifaceted measurement:
• Going beyond traditional key performance indicators, aggregated and
trend data can be used to develop performance metrics across any number
of categories of dynamic customer behavior, including customer
engagement, channel preferences, cross-channel response attributions,
etc., informing everything from merchandise allocations to complex
marketing budgeting.
Big Data Insights
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There is no going back to the days of favorite
channel marketing. Customers are not
thinking channels – they are thinking
convenience -- and convenience means any
platform, any channel, at anytime.
The very same technologies driving these
customer changes are creating a Big Data
trail that -- when properly collected and
synthesized -- delivers invaluable insights
not simply as to who your customers are,
but the attitudes, motivations, habits, etc.
upon which more robust engagement can be
built.
Most of what constitutes Big Data has an
increasingly short shelf life; its relevance to
the brand is driven either by rapidly
changing customer behavior or the brand’s
incorporation of that data into larger
engagement strategies. Marketing Big Data
is of value only to the extent that it is
organized, useful and accessible to those
who most depend on it.
Gracias.