Social Data IntelligenceAn Altimeter Group Webinar
Susan Etlinger, Industry AnalystSeptember 5, 2013
Agenda
I. The State of Social Analytics
II. Making Social Data Actionable
III. Building A Data-Driven Organization
IV. Six Dimensions of Analytics Maturity
V. What’s Next
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The State of Social Analytics
Social data is not an island
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It is used across the organization
Organizations want context
Source: Altimeter Group
It has a large and diffuse ecosystem
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Manny’s steakhouse is celebrated for its quality steaks, but when a sudden
change in sentiment related to its meat quality surfaced via social media, the company was able to
pinpoint the precise dates, times, and incidents of faulty product.
Social data turned up the heat for Manny’s Steakhouse, prompting action
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Parasole and Manny’s quickly identified 6 suspect samples, lined
them up, tasted them, and immediately discovered the problem.
Parasole uses social data opportunistically, to protect product (and brand) quality
Using social data to optimize supply Cut ties with the meat supplier Provided employee training to smooth
the transition Updated employee incentive programs
to incorporate social ratings and reviews
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So…what is social data intelligence?
Social data intelligence is insight derived from social data that organizations can use confidently, at scale and in conjunction with other data sources to make strategic decisions.
Challenges of integrating social data
Characteristics to consider
Making Social Data Actionable
1. Identify your business goals
2. Define core social media metrics
Business Goal Social Media Metric
Brand Health Brand sentiment over time
Marketing Optimization
Impact of campaign X on awareness
Revenue Generation Impact of social media on conversion
Operational Efficiency
Impact of social media on call deflection
Customer Experience Impact of social media on NPS
Innovation Impact of social media on speed to market
3. Prioritize Your Metrics
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Prioritization Process
1. List the core set of metrics you would like to evaluate
2. Score them as follows, on a scale of 1-5, where 1 is the lowest, and 5 is the highest
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Symantec has operationalized social data
Symantec harvests social data from across the web. They route data to the central social business team, where they determine the business function best equipped to serve the customer. They classify Actionable Internet Mentions (AIMs) into seven categories comprising different business functions. The seven classifications are:
1. Case: Request for help resolving real-time issue2. Query: Question that doesn’t require support resource3. Rant: Criticism that merits brand management consideration4. Rave: Praise from Symantec brand advocate5. Lead: Pronouncement of near-term purchase decision6. RFE: Request to enhance a product with a new feature7. Fraud: Communication from an unauthorized provider of Symantec products
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• Marketing• Customer Support• Engineering• PR• Product Management• Legal
Results across the enterprise
Customer ExperienceNumerous support cases resolvedConverted many ‘ranters’ to ‘ravers’
Product ImprovementRapidly identifies key areas to prioritize R&D
Lead Generation & NurturingGenerated hundreds of business & consumer leads
Risk MitigationUncovered hundreds of fraudulent product pilots
Building A Data-Driven Organization
Aspire to a (more) holistic strategy
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Scope: The number of internal groups that work with
social data and the scope of data to be measured: which platforms, which data points, and why.
Define what you’ll do and what you won’t do.
InventoryDocumented methodology
Documented success criteria
Mastery means you can easily answer questions such as:
• What social data do we have at our disposal?
• What do we track? What is our methodology for social data?
• What are the critical success factors to scale this across the organization?
1. SCOPEWhat success looks like
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Strategy: The extent to which social data — and
metrics — is in alignment with strategic business objectives across the organization.
Demonstrate the connection to the outcomes the C-Suite cares about.
Brand reputation, revenue generation, operational
savings, customer satisfaction, etc.
Maturity means every social media initiative — however small or short-term — has a clear set of goals and metrics that define success.
2. STRATEGYWhat success looks like
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Context: The extent to which the organization is able
to view social data in various contexts to understand what is typical, what is unusual, and the drivers for each.
Learn what “normal” looks like.
How social data changes over
TIME
Multiple outliers gain significance
Look at existing metrics
Consider the competition– but
not too much
3. CONTEXTWhat success looks like
The top maturity marker is the existence of clear benchmarks against:
• Past history
• Enterprise signals
• The competition
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Governance: The extent to which the
organization has developed, socialized, and formalized processes related to workflow, collaboration, and data sharing.
Identify the areas where you have inadequate processes or policies.
Data sharing
Executive support
4. GOVERNANCEWhat success looks like
Governance maturity means that:
• Social data measurement processes are documented, socialized, and understood company-wide
• Workflows are clear, automated, and scalable
• Approach in context of organization’s cultural norms
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Image by coreburn used with Attribution as directed by Creative Commons http://www.flickr.com/photos/coreburn/487357814
Metrics: The extent to which metrics have been
defined and socialized throughout the business
Define, contextualize, and prioritize core metrics.
Ability to articulate all criteria and process by which metric is
evaluated
Benchmarks & KPIs: decision-making vs. performance
5. METRICSWhat success looks like
The keys to metrics maturity:
• Definition
• Prioritization
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Data: A strategic approach to the data and platforms at
your disposal
Know thy social data, platforms, and roadmap.
Understand social action vs. social text
Know your platforms (capabilities, limitations,
TOS, APIs, etc.)
Warehouse social data
6. DATAWhat success looks like
Maturity in the data dimension requires:
• Understanding of data types, sources, context, influence
• Resources who understand and make best use of platforms, and conform to their terms of service
• Approach to integrating social data into other business critical data streams, big and small
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Caesar’s to integrate social data across 50+ casinos, hotels, and golf courses worldwide
Across a vast empire of brands and locations, Caesar’s realizes the value of its data lies in its ability to inform
the customer journey across channels and touchpoints.
Aggregate, then analyze
Caesar’s is undergoing a mass integration project, aggregating data across offline and online advertising channels, such as display, email, organic, search, and affiliate.
“The goal is to understand both online and offline touchpoints along the customer
journey and how they vary across segments, media types, and brands.”
–Chris Kahle, Manager of Web Analytics, Caesar’s
The goal: understand the customer journey
Building preference modelsUsing previous purchase data + engagement history (online and offline)
Gaining insightsAggregating behavioral preference data informs more efficient, strategic, and timely investments, at customer and organizational level
Driving loyaltyTying pre-purchase + rewards data Online + offline behavior earns customers points towards rooms, shows, discounts, etc.
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Final Thoughts
Implications and Trends
1. View from the customer in, not the organization out• Holistic view of customer drives ‘real-time’ and ‘right-time’
engagement
2. Social data is “big data”• Embracing volumes, variety, and velocity of social data will
help prepare organizations for other data streams to come
3. Big data disrupts organizations• Consider the HiPPO phenomenon and democratization of
decision-making based on data (vs. intuition)
4. The real-time enterprise is getting more real• Demand for data at the point of action
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"Everything should be made as simple as possible, but not
simpler."
− Albert Einstein
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Susan [email protected]
susanetlinger.com
Twitter: setlinger
THANK YOU
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