This document discusses social data intelligence and the challenges of integrating social data across organizations. It defines social data intelligence as insight derived from social data that can be used confidently and at scale alongside other data sources to make strategic decisions. The challenges of integrating social data include dealing with multiple internal interests, requiring new analytical approaches, and social data initially lacking credibility. The document provides an example of how Symantec harvests social data and routes it to the appropriate business functions. It discusses the results Symantec has seen across marketing, customer support, engineering, and other areas. The document also presents a maturity model for social data and trends organizations should consider when using social data.
Big Data: Expectations, Obstacles, and The Road to Greater ValueSAP Technology
What can Big Data do for you? A recent report by The Economist Intelligence
Unit sponsored by SAP Services explores these issues and more. Learn more at www.sap.com/bigdata
SparkScore (The Social Net Promoter Score): A methodology for measuring socia...SocialMedia.org
In her Brands-Only Summit presentation, Satmetrix's VP of Innovation and Strategy, discusses SparkScore -- the Social Net Promoter Score.
She explains how this social media analytic marries the insight from structured, survey-based solutions to the "social universe" through a single, standard metric.
How to Ruin your Business with Data Science & Machine Learning by Ingo MierswaData Con LA
Abstract:- Everyone talks about how machine learning will transform business forever and generate massive outcomes. However, it's surprisingly simple to draw completely wrong conclusions from statistical models, and correlation does not imply causation is just the tip of the iceberg. The trend of the democratization of data science further increases the risk for applying models in a wrong way. This session will discuss. How highly-correlated features can overshadow the patterns your machine learning model is supposed to find this leads to models which will perform worse in production than during model building. How incorrect cross-validation lead to over-optimistic estimations of your model accuracy, especially we will discuss the impact of data preprocessing on the accuracy of machine learning models. How feature engineering can lift simple models like linear regression to the accuracy of deep learning but comes with the advantages of understandability & robustness.
State of the Industry: Creating a 360 View: Leveraging the Right Data for Tod...Digiday
Marketers today are striving to combine all forms of consumer information, from basic demographics to purchase behavior and even social and mobile activity, into a single, unified view of their customers. A comprehensive understanding of your customer across channels is the key to developing analytics that can better tailor approaches toward, and thus predict the behavior of, consumers, both online and offline. The quest to identify a single view is nowhere near complete, and while various tactics are adopted to suit the needs of marketers, there is a growing industry debate regarding the ethicality of these practices, especially when the methods of gathering consumer information are either unorthodox or involuntary.
Neustar conducted a study by surveying hundreds of marketers to hear about current practices marketers are implementing in attempt to gain a single view of their customer and how they are currently leveraging this data to efficiently reach their audiences across device and channel. In this session, Paul McConville, Vice President at Neustar will will discuss the effectiveness of optimizing your marketing efforts, the importance of data quality, identity linkages, data access and how the wider legal and moral narrative is shaping norms and realities.
When sales leaders have real-time data at their fingertips, they’ll always be more efficient and successful. Whether it’s identifying opportunities, understanding who top performers are, validating forecasts, highlighting neglected opportunities, or developing talent, better and faster access to real-time data generates more revenue.
But running a data-driven sales org is not an easy task.
Domo polled more than 400 sales leaders and managers across a range of industries to understand their relationship with data. 73 percent of survey respondents said they would consume data more if they could see it one place, and 66 percent said they would consume data more if they could see it in real time.
The problem is, sales leaders often can’t access the data they need. It’s a company’s responsibility to turn data-hungry sales pros into data-driven selling machines. Every minute a sales rep spends creating or analyzing reports takes time away from prospects and customers. Non sales activities are killers in terms of nailing your number.
Session on the value of social data and how companies are going "beyond the basics" in using social data for research. Presented at #1amconf (www.http://www.altmetricsconference.com) on
4 Steps to Creating an Effective Sales DashboardDomo
Sales executives deal with a daily barrage of data - forecast numbers, pipeline velocity, lead volume, territory effectiveness, win/loss reports. The biggest challenge is figuring out how to consume the data and translate it into better decision-making. How is this accomplished? The answer for an increasing number of successful sales leaders is an effective sales dashboard.
Discussion Topics include:
· The Explosion of Sales and Marketing Data
· Key Metrics Sales Leaders are Tracking
· Lessons Learned from a Sales Veteran
· New Sales Dashboard Technologies
Big Data: Expectations, Obstacles, and The Road to Greater ValueSAP Technology
What can Big Data do for you? A recent report by The Economist Intelligence
Unit sponsored by SAP Services explores these issues and more. Learn more at www.sap.com/bigdata
SparkScore (The Social Net Promoter Score): A methodology for measuring socia...SocialMedia.org
In her Brands-Only Summit presentation, Satmetrix's VP of Innovation and Strategy, discusses SparkScore -- the Social Net Promoter Score.
She explains how this social media analytic marries the insight from structured, survey-based solutions to the "social universe" through a single, standard metric.
How to Ruin your Business with Data Science & Machine Learning by Ingo MierswaData Con LA
Abstract:- Everyone talks about how machine learning will transform business forever and generate massive outcomes. However, it's surprisingly simple to draw completely wrong conclusions from statistical models, and correlation does not imply causation is just the tip of the iceberg. The trend of the democratization of data science further increases the risk for applying models in a wrong way. This session will discuss. How highly-correlated features can overshadow the patterns your machine learning model is supposed to find this leads to models which will perform worse in production than during model building. How incorrect cross-validation lead to over-optimistic estimations of your model accuracy, especially we will discuss the impact of data preprocessing on the accuracy of machine learning models. How feature engineering can lift simple models like linear regression to the accuracy of deep learning but comes with the advantages of understandability & robustness.
State of the Industry: Creating a 360 View: Leveraging the Right Data for Tod...Digiday
Marketers today are striving to combine all forms of consumer information, from basic demographics to purchase behavior and even social and mobile activity, into a single, unified view of their customers. A comprehensive understanding of your customer across channels is the key to developing analytics that can better tailor approaches toward, and thus predict the behavior of, consumers, both online and offline. The quest to identify a single view is nowhere near complete, and while various tactics are adopted to suit the needs of marketers, there is a growing industry debate regarding the ethicality of these practices, especially when the methods of gathering consumer information are either unorthodox or involuntary.
Neustar conducted a study by surveying hundreds of marketers to hear about current practices marketers are implementing in attempt to gain a single view of their customer and how they are currently leveraging this data to efficiently reach their audiences across device and channel. In this session, Paul McConville, Vice President at Neustar will will discuss the effectiveness of optimizing your marketing efforts, the importance of data quality, identity linkages, data access and how the wider legal and moral narrative is shaping norms and realities.
When sales leaders have real-time data at their fingertips, they’ll always be more efficient and successful. Whether it’s identifying opportunities, understanding who top performers are, validating forecasts, highlighting neglected opportunities, or developing talent, better and faster access to real-time data generates more revenue.
But running a data-driven sales org is not an easy task.
Domo polled more than 400 sales leaders and managers across a range of industries to understand their relationship with data. 73 percent of survey respondents said they would consume data more if they could see it one place, and 66 percent said they would consume data more if they could see it in real time.
The problem is, sales leaders often can’t access the data they need. It’s a company’s responsibility to turn data-hungry sales pros into data-driven selling machines. Every minute a sales rep spends creating or analyzing reports takes time away from prospects and customers. Non sales activities are killers in terms of nailing your number.
Session on the value of social data and how companies are going "beyond the basics" in using social data for research. Presented at #1amconf (www.http://www.altmetricsconference.com) on
4 Steps to Creating an Effective Sales DashboardDomo
Sales executives deal with a daily barrage of data - forecast numbers, pipeline velocity, lead volume, territory effectiveness, win/loss reports. The biggest challenge is figuring out how to consume the data and translate it into better decision-making. How is this accomplished? The answer for an increasing number of successful sales leaders is an effective sales dashboard.
Discussion Topics include:
· The Explosion of Sales and Marketing Data
· Key Metrics Sales Leaders are Tracking
· Lessons Learned from a Sales Veteran
· New Sales Dashboard Technologies
Slides by Craig McGill (@craigmcgill) from the recent Edinburgh Chamber of Commerce Inspiring Edinburgh event.
If you've any questions, feel free to reach out to Craig via Twitter.
The average enterprise-class company owns 178 social accounts, while 13 departments — including marketing, human resources, field sales, and legal — are actively engaged in social media. Yet social data are still largely isolated from business-critical enterprise data collected from Customer Relationship Management (CRM), Business Intelligence (BI), market research, and other sources. In this report, industry analyst Susan Etlinger demonstrates how leading organizations are deriving actionable intelligence from a holistic view of social and enterprise data, the challenges and opportunities in doing so, and the criteria required to achieve social intelligence maturity.
Social Data Intelligence: Webinar with Susan EtlingerSusan Etlinger
This webinar covers the findings from the Altimeter Group report, Social Data Intelligence, which lays out the imperative for organizations to integrate social data with other data streams in the enterprise. Includes best practices and frameworks, as well as a maturity map to enable organizations to make the best and most strategic use of social data.
Social data intelligence, presented by Susan EtlingerSocialMedia.org
In her Brands-Only Summit presentation, Altimeter Group's Industry Analyst, Susan Etlinger, talks about how leading organizations are deriving actionable intelligence from a holistic view of social enterprise data.
She discusses the challenges, opportunities, and the criteria required to achieve social intelligence maturity.
To implement data-centric security, while simultaneously empowering your business to compete and win in today’s nano-second world, you need to understand your data flows and your business needs from your data. Begin by answering some important questions:
•
What does your organization need from your data in order to extract the maximum business value and gain a competitive advantage?
•
What opportunities might be leveraged by improving the security posture of the data?
•
What risks exist based upon your current security posture? What would the impact of a data breach be on the organization? Be specific!
•
Have you clearly defined which data (both structured and unstructured) residing across your extended enterprise is most important to your business? Where is it?
•
What people, processes and technology are currently employed to protect your business sensitive information?
•
Who in your organization requires access to data and for what specific purposes?
•
What time constraints exist upon the organization that might affect the technical infrastructure?
•
What must you do to comply with the myriad government and industry regulations relevant to your business?
Finally, ask yourself what a successful data-centric protection program should look like in your organization. What’s most appropriate for your organization?
The answers to these and other related questions would provide you with a clearer picture of your enterprise’s “data attack surface,” which in turn will provide you with a well-documented risk profile. By answering these questions and thinking holistically about where your data is, how it’s being used and by whom, you’ll be well positioned to design and implement a robust, business-enabling data-centric protection plan that is tailored to the unique requirements of your organization.
Intel, Cloudera and guest speaker Forrester Research, Inc. discuss the strategy of pervasive analytics and real life examples of how analytics have already been embedded into applications and workflows.
Unveiling the Power of Data Analytics Transforming Insights into Action.pdfKajal Digital
Data analytics is the process of examining raw data to discover patterns, correlations, trends, and other valuable information. Its significance lies in its ability to transform data into actionable insights, ultimately leading to informed decision-making and improved business outcomes. From optimizing operational processes to enhancing customer experiences, data analytics offers a plethora of benefits across various sectors.
What Big Data Means for PR and Why It Matters to UsMSL
Invited to sit on a panel together with Paul Holmes at the PR Forum held in Bucharest March 26, Pascal shared thoughts about the Big Data tsunami which is deeply transforming marketing, communications and PR. What is "Big Data" exactly, what does it mean to businesses, why does it matter to us, and what potential issues could arise from it?
Data Analytics Ethics Issues and Questions
Presented at the University of Chicago Booth Big Data & Analytics Roundtable, April 2018
Presenter:
Arnie Aronoff, Ph.D.
Instructor, MScA in Data Analytics
Instructor, School of Social Services Administration
The University of Chicago
Group Concept OD
Organizational Development and Training
(312) 259-4544
aaronoff33@gmail.com
Presented by
My keynote speech at the ISACA IIA Belgium software watch day in October 2014 in Brussels on the value of big data and data analytics for auditors and other assurance professionals
The Data Driven Enterprise - Roadmap to Big Data & Analytics SuccessBigInsights
The Data Driven Enterprise - Roadmap to Big Data & Analytics Success
Presentation used at the series of Breakfast seminar around Australia hosted by Lenovo/Intel/SAP/EY
Similar to Social Data Week SF: Integrating Social and Enterprise Data for Competitive Advantage - Susan Etlinger, Altimeter (20)
Welcome to the Program Your Destiny course. In this course, we will be learning the technology of personal transformation, neuroassociative conditioning (NAC) as pioneered by Tony Robbins. NAC is used to deprogram negative neuroassociations that are causing approach avoidance and instead reprogram yourself with positive neuroassociations that lead to being approach automatic. In doing so, you change your destiny, moving towards unlocking the hypersocial self within, the true self free from fear and operating from a place of personal power and love.
https://bit.ly/BabeSideDoll4u Babeside is a company that specializes in creating handcrafted reborn dolls. These dolls are designed to be incredibly lifelike, with realistic skin tones and hair, and they have become increasingly popular among collectors and those who use them for therapeutic purposes. At Babeside, we believe that our reborn dolls can provide comfort and healing to anyone who needs it.
The Healing Power of Babeside's Handcrafted Creations
Our reborn dolls are more than just beautiful pieces of art - they can also help alleviate stress, anxiety, depression, and other mental health conditions. Studies have shown that holding or cuddling a soft object like a stuffed animal or a reborn doll can release oxytocin, which is often referred to as the "love hormone." This hormone helps us feel calm and relaxed, reducing feelings of stress and anxiety.
In addition to their physical benefits, reborn dolls can also offer emotional support. For many people, having something to care for and nurture can bring a sense of purpose and fulfillment. Reborn dolls can also serve as a reminder of happy memories or loved ones who have passed away.
4. So…what is social data intelligence?
Social Data Intelligence
Insight derived from social data
that organizations can use confidently,
at scale and in conjunction with other data sources
to make strategic decisions.
5. Challenges of integrating social data
Multiple internal
constituents and
interests
• Community managers &
customer service
• Marketing and digital
• Risk, compliance, legal, HR
• Market research
Requires new
analytical approaches
It’s big data!
• Variety
• Velocity
• Volume
Social Data (and
sometimes analysts)
lack enterprise
credibility
• Social data is new
• It lacks standards
• Analyst roles are new
6. Symantec harvests social data from across the web
and routes it to the central social business team,
who determines the business function
best equipped to serve the customer.
They classify Actionable Internet Mentions (AIMs) into 7
categories comprising different business functions:
1. Case
2. Query
3. Rant
4. Rave
5. Lead
6. RFE
7. Fraud
• Marketing
• Customer Support
• Engineering
• PR
• Product Management
• Legal
ECase Study: Symantec
7. Results across the enterprise
Customer Experience
Numerous support cases resolved
Converted many ‘ranters’ to ‘ravers’
Product Improvement
Rapidly identifies key areas
to prioritize R&D
Lead Generation & Nurturing
Generated hundreds of business
and consumer leads
Risk Mitigation
Uncovered hundreds of
fraudulent product pilots
9. Implications and trends
1. Flip your POV
Look at data from customer in, not silo out
2. Social data is “big data”
Embracing volumes, variety, and velocity
3. Big data disrupts organizations
The HiPPO phenomenon (data vs. intuition)
4. Faster all the time
Real, right-time enterprise.
10. Susan Etlinger
susan@altimetergroup.com
susanetlinger.com
Twitter: setlinger
THANK YOU
Disclaimer: Although the information and data used in this report have been produced and processed from sources
believed to be reliable, no warranty expressed or implied is made regarding the completeness, accuracy, adequacy or use
of the information. The authors and contributors of the information and data shall have no liability for errors or omissions
contained herein or for interpretations thereof. Reference herein to any specific product or vendor by trade name,
trademark or otherwise does not constitute or imply its endorsement, recommendation or favoring by the authors or
contributors and shall not be used for advertising or product endorsement purposes. The opinions expressed herein are
subject to change without notice.
Editor's Notes
The following case study illustrates how Symantec is addressing the challenges of meaningfully integrating social data with enterprise business processes and data. Note that, while many of the processes the company is using are still manual, the organization has established a clear vision for how it will solve both granular issues (integrating social signals into customer care) and more visionary ones, such as how it will use social data to inform a deeper and more strategic ongoing relationship with customers.Ultimately, the company vision is to integrate social data intelligence deeply into the organization to empower all 20,000 employees around the globe to engage with its 2.5 million customers.ObjectiveFounded in 1982, Symantec provides security, storage and systems management solutions to help customers secure and manage their information and identities independent of device. The company uses social data to optimize business value across the customer journey, as well as to drive revenue, improve efficiencies and mitigate risk. ApproachToday Symantec uses Salesforce Marketing Cloud to harvest social data — including posts, brand mentions, and comments — from across the web and sends it to a central team within the marketing organization that determines the business function best equipped to serve the customer. The central team, known as the Social Business Team, has established processes and workflows to route incoming queries and mentions to approximately 300 trained employees based on which product or issue is mentioned. Symantec has established specific tracks for specific products, but most notably classify what they call Actionable Internet Mentions (AIMs) into seven buckets, falling into different business functions and corresponding to various phases of the customer journey. The seven classifications are:1. Case: Request for help resolving real-time issue2. Query: Question that doesn’t require support resource3. Rant: Insult 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 productsThese seven categories incorporate workflows for Symantec’s top 15 product lines and span business functions that include marketing, customer support, engineering, PR, product management, and legal. Following are some of the ways Symantec harvests social data:Customer Experience. Symantec aims to optimize customer experience at every touchpoint. For example, if a customer mentions the name of a product in a social post, that case is automatically assigned and routed to the appropriate support resource trained in social and on the specific product. Symantec also leverages existing content to streamline the process for both customer and employee, routing to support team members with a deep knowledge of product content who can answer the question or direct the customer to an existing thread in Symantec’s online community. For example, one of Symantec’s goals (and key metrics) is the conversion of “ranters” into “ravers.” The PR team is trained to surface a potential product issue hidden in the “rant,” re-tags the case accordingly, and conducts a “warm transfer”of the customer to the proper support staff to resolve the issue.13 “Raves” are also used to improve experience and are routed when appropriate to product marketing to say thank you, inquire about customer references, or invite the customer to become a blogger or forum advisor. For other customers, submitting ideas for innovation (or “Requests For Enhancements” — RFEs), Symantec routes suggestions to its product management team to help instruct development roadmap and priority• Lead Nurturing. Symantec also uses social data intelligence to generate and nurture leads, both for consumers and businesses. If the customer is comparing with a competitor, questioning renewal, asking for product specifications, or expressing frustration with a competitor’s product, listening tools enable Symantec to route these insights into its lead pipeline and engage in the most appropriate manner based on the customer’s comment. • Risk Mitigation. Symantec has also discovered a way to mitigate risk when analyzing data to build content for marketing. “The fraud protection value of social media monitoring came as a surprise to me: As we ran our product monitoring queries, we were alarmed to find a number of posts promoting and linking to illegal download sites,” explains Tristan Bishop, Symantec’s Director of Social Business. In addition to training its legal department to handle these posts, Symantec now actively monitors for fraud and helps preserve the integrity (and limit the potential for negative posts) around the product. ResultsSince rolling out this workflow, Symantec has resolved numerous support cases, converted many ranters into ravers, generated hundreds of business and consumer leads, rapidly identified key areas to prioritize for product development, and uncovered hundreds, if not thousands, of fraudulent product pilots. In the longer term, Bishop hopes to standardize all customer data within the same CRM system to provide full context for every employee. “When a Symantec employee interacts with a customer, we hope they’ll be able to view Symantec’s entire relationship with that customer: The customer’s sales history, their support history, and their social likes and shares of Symantec products and content. By giving our frontline staff this context, we can empower them to create a superior customer experience.”
The following case study illustrates how Symantec is addressing the challenges of meaningfully integrating social data with enterprise business processes and data. Note that, while many of the processes the company is using are still manual, the organization has established a clear vision for how it will solve both granular issues (integrating social signals into customer care) and more visionary ones, such as how it will use social data to inform a deeper and more strategic ongoing relationship with customers.Ultimately, the company vision is to integrate social data intelligence deeply into the organization to empower all 20,000 employees around the globe to engage with its 2.5 million customers.ObjectiveFounded in 1982, Symantec provides security, storage and systems management solutions to help customers secure and manage their information and identities independent of device. The company uses social data to optimize business value across the customer journey, as well as to drive revenue, improve efficiencies and mitigate risk. ApproachToday Symantec uses Salesforce Marketing Cloud to harvest social data — including posts, brand mentions, and comments — from across the web and sends it to a central team within the marketing organization that determines the business function best equipped to serve the customer. The central team, known as the Social Business Team, has established processes and workflows to route incoming queries and mentions to approximately 300 trained employees based on which product or issue is mentioned. Symantec has established specific tracks for specific products, but most notably classify what they call Actionable Internet Mentions (AIMs) into seven buckets, falling into different business functions and corresponding to various phases of the customer journey. The seven classifications are:1. Case: Request for help resolving real-time issue2. Query: Question that doesn’t require support resource3. Rant: Insult 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 productsThese seven categories incorporate workflows for Symantec’s top 15 product lines and span business functions that include marketing, customer support, engineering, PR, product management, and legal. Following are some of the ways Symantec harvests social data:Customer Experience. Symantec aims to optimize customer experience at every touchpoint. For example, if a customer mentions the name of a product in a social post, that case is automatically assigned and routed to the appropriate support resource trained in social and on the specific product. Symantec also leverages existing content to streamline the process for both customer and employee, routing to support team members with a deep knowledge of product content who can answer the question or direct the customer to an existing thread in Symantec’s online community. For example, one of Symantec’s goals (and key metrics) is the conversion of “ranters” into “ravers.” The PR team is trained to surface a potential product issue hidden in the “rant,” re-tags the case accordingly, and conducts a “warm transfer”of the customer to the proper support staff to resolve the issue.13 “Raves” are also used to improve experience and are routed when appropriate to product marketing to say thank you, inquire about customer references, or invite the customer to become a blogger or forum advisor. For other customers, submitting ideas for innovation (or “Requests For Enhancements” — RFEs), Symantec routes suggestions to its product management team to help instruct development roadmap and priority• Lead Nurturing. Symantec also uses social data intelligence to generate and nurture leads, both for consumers and businesses. If the customer is comparing with a competitor, questioning renewal, asking for product specifications, or expressing frustration with a competitor’s product, listening tools enable Symantec to route these insights into its lead pipeline and engage in the most appropriate manner based on the customer’s comment. • Risk Mitigation. Symantec has also discovered a way to mitigate risk when analyzing data to build content for marketing. “The fraud protection value of social media monitoring came as a surprise to me: As we ran our product monitoring queries, we were alarmed to find a number of posts promoting and linking to illegal download sites,” explains Tristan Bishop, Symantec’s Director of Social Business. In addition to training its legal department to handle these posts, Symantec now actively monitors for fraud and helps preserve the integrity (and limit the potential for negative posts) around the product. ResultsSince rolling out this workflow, Symantec has resolved numerous support cases, converted many ranters into ravers, generated hundreds of business and consumer leads, rapidly identified key areas to prioritize for product development, and uncovered hundreds, if not thousands, of fraudulent product pilots. In the longer term, Bishop hopes to standardize all customer data within the same CRM system to provide full context for every employee. “When a Symantec employee interacts with a customer, we hope they’ll be able to view Symantec’s entire relationship with that customer: The customer’s sales history, their support history, and their social likes and shares of Symantec products and content. By giving our frontline staff this context, we can empower them to create a superior customer experience.”