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 Etlingersusan@altimetergroup.com

susanetlinger.com

Twitter: setlinger

THANK YOU

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