Big data has positively impacted marketing by allowing companies to better understand customers. Companies use big data analytics from sources like purchase histories, social media, and online activities to identify customer preferences and develop targeted products and services. However, concerns exist around customer privacy as companies collect and store vast amounts of personal data. Case studies of Amazon, Netflix, and Target demonstrate how each uses big data to personalize the customer experience, though privacy issues remain.
This document proposes advanced data analytics as the key solution for building intimate knowledge about our customers’ behaviour, preferences and aspirations; an essential requirement for maximizing revenue in our current competitive environment.
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...Edureka!
Data Analytics for R Course: https://www.edureka.co/r-for-analytics
This Edureka Tutorial on Data Analytics for Beginners will help you learn the various parameters you need to consider while performing data analysis.
The following are the topics covered in this session:
Introduction To Data Analytics
Statistics
Data Cleaning and Manipulation
Data Visualization
Machine Learning
Roles, Responsibilities and Salary of Data Analyst
Need of R
Hands-On
Statistics for Data Science: https://youtu.be/oT87O0VQRi8
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
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Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
This document proposes advanced data analytics as the key solution for building intimate knowledge about our customers’ behaviour, preferences and aspirations; an essential requirement for maximizing revenue in our current competitive environment.
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...Edureka!
Data Analytics for R Course: https://www.edureka.co/r-for-analytics
This Edureka Tutorial on Data Analytics for Beginners will help you learn the various parameters you need to consider while performing data analysis.
The following are the topics covered in this session:
Introduction To Data Analytics
Statistics
Data Cleaning and Manipulation
Data Visualization
Machine Learning
Roles, Responsibilities and Salary of Data Analyst
Need of R
Hands-On
Statistics for Data Science: https://youtu.be/oT87O0VQRi8
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Big Data is the new buzz word doing rounds these days. What is Big Data? How can be it used for advertising? Which companies use Big Data? How do they use it? What are benefits of Big Data? Know it all!
Which are the essential digital marketing insights and automation tools to grow your business? This deck shows you the best tools across our RACE framework.
Business Value Through Reference and Master Data StrategiesDATAVERSITY
Data tends to pile up and can be rendered unusable or obsolete without careful maintenance processes. Reference and Master Data Management (MDM) has been a popular Data Management approach to effectively gain mastery over not just the data but the supporting architecture for processing it. This webinar presents MDM as a strategic approach to improving and formalizing practices around those data items that provide context for many organizational transactions — the master data. Too often, MDM has been implemented technology-first and achieved the same very poor track record (one-third succeeding on time, within budget, and achieving planned functionality). MDM success depends on a coordinated approach, typically involving Data Governance and Data Quality activities.
Learning Objectives:
• Understand foundational reference and MDM concepts based on the Data Management Body of Knowledge (DMBoK)
• Understand why these are an important component of your Data Architecture
• Gain awareness of reference and MDM frameworks and building blocks
• Know what MDM guiding principles consist of and best practices
• Know how to utilize reference and MDM in support of business strategy
RFM stands for Recency, Frequency, and Monetary value, each corresponding to some key customer trait. These RFM metrics are important indicators of a customer’s behavior because frequency and monetary value affects a customer’s lifetime value, and recency affects retention, a measure of engagement.
RFM analysis helps marketers find answers to the following questions:
Who are your best customers?
Which of your customers could contribute to your churn rate?
Who has the potential to become valuable customers?
Which of your customers can be retained?
Which of your customers are most likely to respond to engagement campaigns?
Let's find out more with the help of Slideshare.
Training Material - Competitive Intelligence - The Life Blood Of Strategy - A...Sadashiv Borgaonkar
This is the training material of Competitive Intelligence. 136 Pages.
Competitive Intelligence is the life blood of strategy
The Ultimate Goal Of Each Intelligence Process Is To Facilitate Decision – Making That Leads To Action.
Eventually, All Intelligence Terms Refer To Using Systematic Methods To Collect, Analyze And Disseminate Information That Supports Decision - Making
Competitive Intelligence (CI) Is Regarded As The Broadest Scope Of Intelligence Activities Covering The Whole External Operating Environment Of The Company And Targeting All Levels Of Decision – Making.
Big Data Tutorial | What Is Big Data | Big Data Hadoop Tutorial For Beginners...Simplilearn
This presentation about Big Data will help you understand how Big Data evolved over the years, what is Big Data, applications of Big Data, a case study on Big Data, 3 important challenges of Big Data and how Hadoop solved those challenges. The case study talks about Google File System (GFS), where you’ll learn how Google solved its problem of storing increasing user data in early 2000. We’ll also look at the history of Hadoop, its ecosystem and a brief introduction to HDFS which is a distributed file system designed to store large volumes of data and MapReduce which allows parallel processing of data. In the end, we’ll run through some basic HDFS commands and see how to perform wordcount using MapReduce. Now, let us get started and understand Big Data in detail.
Below topics are explained in this Big Data presentation for beginners:
1. Evolution of Big Data
2. Why Big Data?
3. What is Big Data?
4. Challenges of Big Data
5. Hadoop as a solution
6. MapReduce algorithm
7. Demo on HDFS and MapReduce
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Grow and scale customer acquisition (and retention)Gary Corcoran
This presentation is for startups who understand who their customers are and have their product market fit.
We take a look at how you can scale and grow your acquisition and retention. Looking at some cool tips and techniques for both customer acquisition and retention.
This presentation focuses on the “Data - Big Data - Bigger Data” and the Challenges, Opportunities and Solutions from these trends.
What are the Challenges this massive data brings to the table?
What are the opportunities this data provide ?
Some solutions on how to handle this data.
B2B marketing can be very different from B2C. The buying process is more complex and requires expertise and targeted audiences. LinkedIn is uniquely positioned to help your agency succeed in the B2B marketing space.
Designed to address more mature programs, this tutorial covers the issues and approaches to sustaining Data Governance and value creation over time, amongst a changing business and personnel environment.
Part of the reason many companies launch a Data Governance program again and again is that over time, it is challenging to maintain the enthusiasm and excitement that accompanies a newly initiated program.
Learn about:
• Typical obstacles to sustainable Data Governance
• Re-energizing your program after a key player (or two) leave and other personnel challenges
• Staying relevant to the company as the business evolves over time
• Understanding the role of metrics and why they are critical
• Leveraging Communication and Stakeholder Management practices to maintain commitment
• Embedding Data Governance into the operations of the company
Modeling The Market Mix Modeling Problem (Media Mix Optimization)Amit Satsangi
Channel Attribution Modeling is not the best way to decide on Media Mix Optimization (Channel ROI). Here I present results by formulating the problem as a Marketing Mix using two models:
(a) Linear Regression Analysis
(b) Log-linear Multiplicative Model
The DMP 101 - Data Management Platforms ExplainedEddy Widerker
Learn more about what a DMP is, how it works, and why it is crucial in today's ad-tech space. Examples on how a DMP could benefit a brand or a publisher are included at the end.
What is data mining?
Why data mining is required?
Data mining Applications
Data mining in Retail Industry
Marketing
Risk Management
Fraud Detection
Customer Acquisition and Retention
RFM Segmentation is the easiest and most frequently used form of database segmentation. It is based on three key metrics: Recency, Frequency and Monetary Value of customer activity. RFM is often used with transactional history in e-commerce, but can also work for Social Media interactions, online gaming or discussion boards. Based on calculated segments a marketer can prepare cross-sell, up-sell, retention and reactivation capampaigns. This deck provides a simple introduction to the RFM Segmentation methodology.
Big Data Analytics | What Is Big Data Analytics? | Big Data Analytics For Beg...Simplilearn
The presentation about Big Data Analytics will help you know why Big Data analytics is required, what is Big Data analytics, the lifecycle of Big Data analytics, types of Big Data analytics, tools used in Big Data analytics and few Big Data application domains. Also, we'll see a use case on how Spotify uses Big Data analytics. Big Data analytics is a process to extract meaningful insights from Big Data such as hidden patterns, unknown correlations, market trends, and customer preferences. One of the essential benefits of Big Data analytics is used for product development and innovations. Now, let us get started and understand Big Data Analytics in detail.
Below are explained in this Big Data analytics tutorial:
1. Why Big Data analytics?
2. What is Big Data analytics?
3. Lifecycle of Big Data analytics
4. Types of Big Data analytics
5. Tools used in Big Data analytics
6. Big Data application domains
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Demand Metric's Playbooks provide frameworks with links to actionable research, tools, templates and training to help organizations operationalize best practices for Marketing.
Ce slide comprend des informations sur le big data et son utilisation dans le domaine du marketing digital ainsi que des exemples d'applications réels dans différent secteur
Big Data is the new buzz word doing rounds these days. What is Big Data? How can be it used for advertising? Which companies use Big Data? How do they use it? What are benefits of Big Data? Know it all!
Which are the essential digital marketing insights and automation tools to grow your business? This deck shows you the best tools across our RACE framework.
Business Value Through Reference and Master Data StrategiesDATAVERSITY
Data tends to pile up and can be rendered unusable or obsolete without careful maintenance processes. Reference and Master Data Management (MDM) has been a popular Data Management approach to effectively gain mastery over not just the data but the supporting architecture for processing it. This webinar presents MDM as a strategic approach to improving and formalizing practices around those data items that provide context for many organizational transactions — the master data. Too often, MDM has been implemented technology-first and achieved the same very poor track record (one-third succeeding on time, within budget, and achieving planned functionality). MDM success depends on a coordinated approach, typically involving Data Governance and Data Quality activities.
Learning Objectives:
• Understand foundational reference and MDM concepts based on the Data Management Body of Knowledge (DMBoK)
• Understand why these are an important component of your Data Architecture
• Gain awareness of reference and MDM frameworks and building blocks
• Know what MDM guiding principles consist of and best practices
• Know how to utilize reference and MDM in support of business strategy
RFM stands for Recency, Frequency, and Monetary value, each corresponding to some key customer trait. These RFM metrics are important indicators of a customer’s behavior because frequency and monetary value affects a customer’s lifetime value, and recency affects retention, a measure of engagement.
RFM analysis helps marketers find answers to the following questions:
Who are your best customers?
Which of your customers could contribute to your churn rate?
Who has the potential to become valuable customers?
Which of your customers can be retained?
Which of your customers are most likely to respond to engagement campaigns?
Let's find out more with the help of Slideshare.
Training Material - Competitive Intelligence - The Life Blood Of Strategy - A...Sadashiv Borgaonkar
This is the training material of Competitive Intelligence. 136 Pages.
Competitive Intelligence is the life blood of strategy
The Ultimate Goal Of Each Intelligence Process Is To Facilitate Decision – Making That Leads To Action.
Eventually, All Intelligence Terms Refer To Using Systematic Methods To Collect, Analyze And Disseminate Information That Supports Decision - Making
Competitive Intelligence (CI) Is Regarded As The Broadest Scope Of Intelligence Activities Covering The Whole External Operating Environment Of The Company And Targeting All Levels Of Decision – Making.
Big Data Tutorial | What Is Big Data | Big Data Hadoop Tutorial For Beginners...Simplilearn
This presentation about Big Data will help you understand how Big Data evolved over the years, what is Big Data, applications of Big Data, a case study on Big Data, 3 important challenges of Big Data and how Hadoop solved those challenges. The case study talks about Google File System (GFS), where you’ll learn how Google solved its problem of storing increasing user data in early 2000. We’ll also look at the history of Hadoop, its ecosystem and a brief introduction to HDFS which is a distributed file system designed to store large volumes of data and MapReduce which allows parallel processing of data. In the end, we’ll run through some basic HDFS commands and see how to perform wordcount using MapReduce. Now, let us get started and understand Big Data in detail.
Below topics are explained in this Big Data presentation for beginners:
1. Evolution of Big Data
2. Why Big Data?
3. What is Big Data?
4. Challenges of Big Data
5. Hadoop as a solution
6. MapReduce algorithm
7. Demo on HDFS and MapReduce
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Grow and scale customer acquisition (and retention)Gary Corcoran
This presentation is for startups who understand who their customers are and have their product market fit.
We take a look at how you can scale and grow your acquisition and retention. Looking at some cool tips and techniques for both customer acquisition and retention.
This presentation focuses on the “Data - Big Data - Bigger Data” and the Challenges, Opportunities and Solutions from these trends.
What are the Challenges this massive data brings to the table?
What are the opportunities this data provide ?
Some solutions on how to handle this data.
B2B marketing can be very different from B2C. The buying process is more complex and requires expertise and targeted audiences. LinkedIn is uniquely positioned to help your agency succeed in the B2B marketing space.
Designed to address more mature programs, this tutorial covers the issues and approaches to sustaining Data Governance and value creation over time, amongst a changing business and personnel environment.
Part of the reason many companies launch a Data Governance program again and again is that over time, it is challenging to maintain the enthusiasm and excitement that accompanies a newly initiated program.
Learn about:
• Typical obstacles to sustainable Data Governance
• Re-energizing your program after a key player (or two) leave and other personnel challenges
• Staying relevant to the company as the business evolves over time
• Understanding the role of metrics and why they are critical
• Leveraging Communication and Stakeholder Management practices to maintain commitment
• Embedding Data Governance into the operations of the company
Modeling The Market Mix Modeling Problem (Media Mix Optimization)Amit Satsangi
Channel Attribution Modeling is not the best way to decide on Media Mix Optimization (Channel ROI). Here I present results by formulating the problem as a Marketing Mix using two models:
(a) Linear Regression Analysis
(b) Log-linear Multiplicative Model
The DMP 101 - Data Management Platforms ExplainedEddy Widerker
Learn more about what a DMP is, how it works, and why it is crucial in today's ad-tech space. Examples on how a DMP could benefit a brand or a publisher are included at the end.
What is data mining?
Why data mining is required?
Data mining Applications
Data mining in Retail Industry
Marketing
Risk Management
Fraud Detection
Customer Acquisition and Retention
RFM Segmentation is the easiest and most frequently used form of database segmentation. It is based on three key metrics: Recency, Frequency and Monetary Value of customer activity. RFM is often used with transactional history in e-commerce, but can also work for Social Media interactions, online gaming or discussion boards. Based on calculated segments a marketer can prepare cross-sell, up-sell, retention and reactivation capampaigns. This deck provides a simple introduction to the RFM Segmentation methodology.
Big Data Analytics | What Is Big Data Analytics? | Big Data Analytics For Beg...Simplilearn
The presentation about Big Data Analytics will help you know why Big Data analytics is required, what is Big Data analytics, the lifecycle of Big Data analytics, types of Big Data analytics, tools used in Big Data analytics and few Big Data application domains. Also, we'll see a use case on how Spotify uses Big Data analytics. Big Data analytics is a process to extract meaningful insights from Big Data such as hidden patterns, unknown correlations, market trends, and customer preferences. One of the essential benefits of Big Data analytics is used for product development and innovations. Now, let us get started and understand Big Data Analytics in detail.
Below are explained in this Big Data analytics tutorial:
1. Why Big Data analytics?
2. What is Big Data analytics?
3. Lifecycle of Big Data analytics
4. Types of Big Data analytics
5. Tools used in Big Data analytics
6. Big Data application domains
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Demand Metric's Playbooks provide frameworks with links to actionable research, tools, templates and training to help organizations operationalize best practices for Marketing.
Ce slide comprend des informations sur le big data et son utilisation dans le domaine du marketing digital ainsi que des exemples d'applications réels dans différent secteur
Big Data - How Marketing Has Revolutionised - by Sean SingletonDigital Annexe
Through BIG DATA, Marketeers can now blend human psychology and understanding with behavioural insights to create communication messages and platforms that do not only resonate with the consumer but find them where and when the information is most needed. At Digital Annexe, we believe BIG DATA is going to completely revolutionize the marketing industry forever in 5 key ways.
TechConnectr's Big Data Connection. Digital Marketing KPIs, Targeting, Analy...Bob Samuels
This presentation was given at the Deep Dive Conference in November. 2013.
Big Data Applications... example, digital marketing, and targeting and optimization...
Feedback, and additional perspectives, is appreciated.
Thank you,
Bobby Samuels
TechConnectr.com
Real Time Marketing Big Data Analytics Social Marketing Intelligence DisruptionChase McMichael
Social Analytics-driven Real-time Marketing with Domain-specific Use Cases The Take away from this event:
1. What is Real Time Marketing and how marketers are using it
2. Why social analysis "The Science" is here to stay and how it works
3. Beyond the buzz word of Big Data - real use cases on how SMBs and Big cos are harnessing insight, trends and content to engage with their customers.
Start your Monday off right and be the smartest person in the room. @chasemcmichael
eMarketer Webinar: Data Management Platforms—Using Big Data to Power Marketin...eMarketer
Join eMarketer for a discussion on how Data Management Platforms (DMPs) are enabling marketers to use their big data to make smarter and more efficient marketing decisions.
This presentation, by big data guru Bernard Marr, outlines in simple terms what Big Data is and how it is used today. It covers the 5 V's of Big Data as well as a number of high value use cases.
7 Traits of Highly Effective Digital Commerce OrganizationsSameer Khan
Commerce technology spending is up across the board. Retailers are significantly bolstering their capital investment programs. 85% will increase their spend on commerce technology in 2015. Is your organization prepared for the next generation of digital business?
According to Gartner, each year businesses see 1/5th of their marketing budgets go to waste due to inaccurate data and reporting that leads to ineffective marketing decisions and under-performing campaigns. In this presentation, we will guide you through a proven and efficient process that standardizes the tracking and measurement of marketing campaigns. By eliminating siloes, boosting productivity, and addressing existing and future data accuracy challenges, this approach ensures reliable insights that drive informed decisions and deliver higher marketing return on investment (ROI).
According to Gartner, each year businesses see 1/5th of their marketing budgets go to waste due to inaccurate data and reporting that leads to ineffective marketing decisions and under-performing campaigns. In this presentation, we will guide you through a proven and efficient process that standardizes the tracking and measurement of marketing campaigns. By eliminating siloes, boosting productivity, and addressing existing and future data accuracy challenges, this approach ensures reliable insights that drive informed decisions and deliver higher marketing return on investment (ROI).
The Age Of New Reality Marketing V5.1 FinalTony Mooney
It\'s been a bug-bear of mine for many years that the average marketing skill set has not moved on very much from the 1960\'s model of 4 \'P\'s (Product, Price, Promotion, Place). Or that marketing is still largely synonomous with advertising - and spam advertising at that. This is a presentation I did to a marketing forum out in Singapore, where I\'ve tried to outline the new capabilities of the marketer of the 21st century. I also postulate the (controversial) perspective that a chunk of this new capability - especially around data and decisioning - might be better out sourced, leaving the internal marketing skills to be concentrated on strategy and proposition. See what you think. [Sorry you won\'t have my spoken narrative just yet but the slides are reasonably self explanatory]
Leveraging big data to drive marketing innovationAndrew Leone
Summary of the book: "The Big Data-Driven Company." Contains insights into leveraging data to drive marketing innovation. To buy this book: http://amzn.to/1YTdtqY
Slides from my lecture on digital marketing to first year Bachelor students at the Stockholm School of Economics in May 2011. Many of the slides are based on David Jobber's textbook: http://www.amazon.co.uk/Principles-Practice-Marketing-David-Jobber/dp/0077114159.
The BRITE '12 conference (March 5-6) marked the unveiling of the Center on Global Brand Leadership and the New York American Marketing Association (NYAMA)'s first BRITE-NYAMA Marketing Measurement in Transition Study entitled, Marketing ROI in the Era of Big Data.
The aim of the study was to gain a better understanding of changing practices among large corporate marketers in the following areas: data collection and usage, marketing measurement and ROI, and the integration of digital and traditional marketing.
In surveying 253 marketing executives from large corporations, the study found both widespread adoption of new digital tools, and support for the use of new data to drive marketing decisions and measure marketing ROI. However, significant gaps exist between desire and execution as companies strive to measure marketing ROI. The overall picture of marketing by large corporations revealed significant need for improvements in the use of data, the measurement of digital marketing, and the assessment of marketing ROI.
http://gsb.columbia.edu/globalbrands
http://www.nyama.org
Web Analytics 2.0 and Multiplicity - PixelMEDIAPixelMEDIA
Slides from a presentation at PixelMEDIA on Web Analytics 2.0 and the concept of Multiplicity. Producing insights, not reporting. By Jonathan B. O'Donnell
Impulsar el negocio de los medios de comunicación gracias al Big Data con IBM...ACTUONDA
Impulsar el negocio de los medios de comunicación gracias al Big Data con IBM.
Presentación de Elisa Martin Garijo, Chief Technology IBM Spain
@ElisaGarijo
Primer encuentro BIG MEDIA
Conectando Media, Audiencia y Publicidad con Datos
24 de junio 2014, Madrid
• Sponsor Platinum : Perfect Memory
• Sponsor Gold : Stratio, Paradigma
• Con el apoyo de : Big Data Spain, Medios On
• Socio tecnológico : Agora News
• Organizadores : Actuonda y Cátedra Big Data UAM-IBM
• Contacto : Nicolas Moulard (Actuonda) moulard@actuonda.com @Radio_20
www.bigmediaconnect.es
Introduction:
In the era of digital transformation, data has become a valuable asset for businesses and organisations across various industries. The collection, analysis, and interpretation of data play a pivotal role in shaping strategic decisions and improving overall efficiency. One key player in this data-driven ecosystem is the data collection company, which specialises in gathering, processing, and providing valuable insights from vast amounts of information.
The Growing Significance of Data Collection Companies:
Data collection companies have become integral to the success of businesses seeking to gain a competitive edge. These firms employ advanced technologies and methodologies to accumulate data from diverse sources, including online platforms, social media, market research, and more. The breadth and depth of data collected allow companies to better understand consumer behaviour, market trends, and industry dynamics.
Types of Data Collection Methods:
Web Scraping:
Data collection company often utilise web scraping techniques to extract information from websites, forums, and online databases. This method enables them to gather real-time data on product prices, customer reviews, and competitor activities.
Surveys and Questionnaires:
Conducting surveys and questionnaires is a traditional yet effective method for gathering specific information directly from target audiences. Data collection companies design surveys to collect insights on consumer preferences, opinions, and demographic details.
IoT Devices:
With the rise of the Internet of Things (IoT), data collection companies leverage connected devices to gather information on user behaviour, preferences, and usage patterns. This data is valuable for improving product design and functionality.
Social Media Monitoring:
Monitoring social media platforms allows data collection companies to analyse public sentiment, track brand mentions, and identify emerging trends. This information aids businesses in adapting their marketing strategies and improving customer relations.
Challenges and Ethical Considerations:
While data collection offers numerous benefits, it is not without challenges and ethical considerations. Privacy concerns, data security, and the responsible use of information are critical aspects that data collection companies must navigate. Striking a balance between collecting valuable insights and respecting user privacy is essential for maintaining public trust.
Conclusion:
Data collection company’s play a vital role in the modern data ecosystem, empowering businesses with the information needed to make informed decisions. As technology continues to advance, these companies will likely evolve in their methodologies and capabilities, further influencing the way organisations harness the power of data for innovation and growth. However, it is crucial for these entities to uphold ethical standards and prioritise data security to ensure a sustainable and responsible data-driven future.
Kathy Bachmann, Executive Vice President and Managing Director for Americas at MarketShare, discussed what it takes for marketers to understand the future of the global marketplace during her presentation at the 2015 Chief Marketing Officer Leadership Forum in Los Angeles on Jan. 27. In her presentation, Bachmann noted that the rising demand for marketing data has led many marketers to leverage sophisticated technologies, but marketers must understand how to optimize these tools to bolster their marketing campaigns.
Introduction:
In today's rapidly evolving digital landscape, the phrase "data is the new oil" has become a mantra, emphasising the invaluable nature of data in shaping business strategies and decision-making processes. At the forefront of this data-driven revolution are data collection company’s, playing a pivotal role in gathering, analysing, and delivering actionable insights. This article explores the functions, significance, and challenges associated with data collection companies in the contemporary business environment.
The Evolution of Data Collection Companies:
Data collection companies have evolved alongside advancements in technology, transitioning from traditional methods to sophisticated techniques that leverage the power of the internet, artificial intelligence, and machine learning. These companies specialise in systematically gathering information from diverse sources, including online platforms, social media, surveys, and more, to provide comprehensive datasets for analysis.
Functions of Data Collection Companies:
Aggregating Diverse Data Sources:
Data collection company’s excel in sourcing information from a multitude of channels, ensuring a holistic view of the market, consumer behaviour, and industry trends. This includes both structured data (numerical data) and unstructured data (text, images, videos).
Data Cleaning and Validation:
Raw data often contains inaccuracies and inconsistencies. Data collection companies employ rigorous cleaning and validation processes to ensure the quality and reliability of the information they provide.
Analysing Trends and Patterns:
Leveraging advanced analytics tools, these companies extract meaningful insights, identify patterns, and discern trends from the vast datasets they accumulate. This information is invaluable for businesses looking to make informed decisions.
Customised Solutions:
Data collection companies offer tailored solutions based on the unique needs of their clients. Whether it's market research, consumer behaviour analysis, or competitive intelligence, these companies provide specialised datasets to address specific business challenges.
Significance in the Business Landscape:
Informed Decision-Making:
Businesses rely on accurate and up-to-date information to make strategic decisions. Data collection company’s empower organisations with the insights needed to navigate an increasingly complex and competitive marketplace.
Competitive Edge:
Access to comprehensive and timely data provides a competitive edge. Companies that leverage the services of data collection firms can stay ahead of industry trends, anticipate market changes, and respond proactively to emerging challenges.
Targeted Marketing:
Understanding consumer behaviour through data collection allows businesses to create targeted and personalised marketing campaigns. This enhances customer engagement and increases the effectiveness of marketing efforts.
Challenges and Ethical
Study programmatic and data in Spain DatmeanDatmean
Datmean just released the first study carried out in Spain about programmatic buying and data. The research points out where Spain stands on this subject and the challenges the country is facing in 2017
The What, Why & How of 3D and AR in Digital CommercePushON Ltd
Vladimir Mulhem has over 20 years of experience in commercialising cutting edge creative technology across construction, marketing and retail.
Previously the founder and Tech and Innovation Director of Creative Content Works working with the likes of Next, John Lewis and JD Sport, he now helps retailers, brands and agencies solve challenges of applying the emerging technologies 3D, AR, VR and Gen AI to real-world problems.
In this webinar, Vladimir will be covering the following topics:
Applications of 3D and AR in Digital Commerce,
Benefits of 3D and AR,
Tools to create, manage and publish 3D and AR in Digital Commerce.
Mastering Local SEO for Service Businesses in the AI Era is tailored specifically for local service providers like plumbers, dentists, and others seeking to dominate their local search landscape. This session delves into leveraging AI advancements to enhance your online visibility and search rankings through the Content Factory model, designed for creating high-impact, SEO-driven content. Discover the Dollar-a-Day advertising strategy, a cost-effective approach to boost your local SEO efforts and attract more customers with minimal investment. Gain practical insights on optimizing your online presence to meet the specific needs of local service seekers, ensuring your business not only appears but stands out in local searches. This concise, action-oriented workshop is your roadmap to navigating the complexities of digital marketing in the AI age, driving more leads, conversions, and ultimately, success for your local service business.
Key Takeaways:
Embrace AI for Local SEO: Learn to harness the power of AI technologies to optimize your website and content for local search. Understand the pivotal role AI plays in analyzing search trends and consumer behavior, enabling you to tailor your SEO strategies to meet the specific demands of your target local audience. Leverage the Content Factory Model: Discover the step-by-step process of creating SEO-optimized content at scale. This approach ensures a steady stream of high-quality content that engages local customers and boosts your search rankings. Get an action guide on implementing this model, complete with templates and scheduling strategies to maintain a consistent online presence. Maximize ROI with Dollar-a-Day Advertising: Dive into the cost-effective Dollar-a-Day advertising strategy that amplifies your visibility in local searches without breaking the bank. Learn how to strategically allocate your budget across platforms to target potential local customers effectively. The session includes an action guide on setting up, monitoring, and optimizing your ad campaigns to ensure maximum impact with minimal investment.
First Things First: Building and Effective Marketing Strategy
Too many companies (and marketers) jump straight into activation planning without formalizing a marketing strategy. It may seem tedious, but analyzing the mindset of your targeted audiences and identifying the messaging points most likely to resonate with them is time well spent. That process is also a great opportunity for marketers to collaborate with sales leaders and account managers on a galvanized go-to-market approach. I’ll walk you through the methods and tools we use with our clients to ensure campaign success.
Key Takeaways:
-Recognize the critical role of strategy in marketing
-Learn our approach for building an actionable, effective marketing strategy
-Receive templates and guides for developing a marketing strategy
For too many years marketing and sales have operated in silos...while in some forward thinking companies, the two organizations work together to drive new opportunity development and revenue. This session will explore the lessons learned in that beautiful dance that can occur when marketing and sales work together...to drive new opportunity development, account expansion and customer satisfaction.
No, this is not a conversation about MQLs and SQLs. Instead we will focus on a framework that allows the two organizations to drive company success together.
Financial curveballs sent many American families reeling in 2023. Household budgets were squeezed by rising interest rates, surging prices on everyday goods, and a stagnating housing market. Consumers were feeling strapped. That sentiment, however, appears to be waning. The question is, to what extent?
To take the pulse of consumers’ feelings about their financial well-being ahead of a highly anticipated election, ThinkNow conducted a nationally representative quantitative survey. The survey highlights consumers’ hopes and anxieties as we move into 2024. Let's unpack the key findings to gain insights about where we stand.
The digital marketing industry is changing faster than ever and those who don’t adapt with the times are losing market share. Where should marketers be focusing their efforts? What strategies are the experts seeing get the best results? Get up-to-speed with the latest industry insights, trends and predictions for the future in this panel discussion with some leading digital marketing experts.
Mastering Local SEO for Service Businesses in the AI Era is tailored specifically for local service providers like plumbers, dentists, and others seeking to dominate their local search landscape. This session delves into leveraging AI advancements to enhance your online visibility and search rankings through the Content Factory model, designed for creating high-impact, SEO-driven content. Discover the Dollar-a-Day advertising strategy, a cost-effective approach to boost your local SEO efforts and attract more customers with minimal investment. Gain practical insights on optimizing your online presence to meet the specific needs of local service seekers, ensuring your business not only appears but stands out in local searches. This concise, action-oriented workshop is your roadmap to navigating the complexities of digital marketing in the AI age, driving more leads, conversions, and ultimately, success for your local service business.
Key Takeaways:
Embrace AI for Local SEO: Learn to harness the power of AI technologies to optimize your website and content for local search. Understand the pivotal role AI plays in analyzing search trends and consumer behavior, enabling you to tailor your SEO strategies to meet the specific demands of your target local audience. Leverage the Content Factory Model: Discover the step-by-step process of creating SEO-optimized content at scale. This approach ensures a steady stream of high-quality content that engages local customers and boosts your search rankings. Get an action guide on implementing this model, complete with templates and scheduling strategies to maintain a consistent online presence. Maximize ROI with Dollar-a-Day Advertising: Dive into the cost-effective Dollar-a-Day advertising strategy that amplifies your visibility in local searches without breaking the bank. Learn how to strategically allocate your budget across platforms to target potential local customers effectively. The session includes an action guide on setting up, monitoring, and optimizing your ad campaigns to ensure maximum impact with minimal investment.
Monthly Social Media News Update May 2024Andy Lambert
TL;DR. These are the three themes that stood out to us over the course of last month.
1️⃣ Social media is becoming increasingly significant for brand discovery. Marketers are now understanding the impact of social and budgets are shifting accordingly.
2️⃣ Instagram’s new algorithm and latest guidance will help us maintain organic growth. Instagram continues to evolve, but Reels remains the most crucial tool for growth.
3️⃣ Collaboration will help us unlock growth. Who we work with will define how fast we grow. Meta continues to evolve their Creator Marketplace and now TikTok are beginning to push ‘collabs’ more too.
AI-Powered Personalization: Principles, Use Cases, and Its Impact on CROVWO
In today’s era of AI, personalization is more than just a trend—it’s a fundamental strategy that unlocks numerous opportunities.
When done effectively, personalization builds trust, loyalty, and satisfaction among your users—key factors for business success. However, relying solely on AI capabilities isn’t enough. You need to anchor your approach in solid principles, understand your users’ context, and master the art of persuasion.
Join us as Sarjak Patel and Naitry Saggu from 3rd Eye Consulting unveil a transformative framework. This approach seamlessly integrates your unique context, consumer insights, and conversion goals, paving the way for unparalleled success in personalization.
How to Use AI to Write a High-Quality Article that Ranksminatamang0021
In the world of content creation, many AI bloggers have drifted away from their original vision, resulting in low-quality articles that search engines overlook. Don't let that happen to you! Join us to discover how to leverage AI tools effectively to craft high-quality content that not only captures your audience's attention but also ranks well on search engines.
Disclaimer: Some of the prompts mentioned here are the examples of Matt Diggity. Please use it as reference and make your own custom prompts.
The digital marketing industry is changing faster than ever and those who don’t adapt with the times are losing market share. Where should marketers be focusing their efforts? What strategies are the experts seeing get the best results? Get up-to-speed with the latest industry insights, trends and predictions for the future in this panel discussion with some leading digital marketing experts.
A.I. (artificial intelligence) platforms are popping up all the time, and many of them can and should be used to help grow your brand, increase your sales and decrease your marketing costs.In this presentation:We will review some of the best AI platforms that are available for you to use.We will interact with some of the platforms in real-time, so attendees can see how they work.We will also look at some current brands that are using AI to help them create marketing messages, saving them time and money in the process. Lastly, we will discuss the pros and cons of using AI in marketing & branding and have a lively conversation that includes comments from the audience.
Key Takeaways:
Attendees will learn about LLM platforms, like ChatGPT, and how they work, with preset examples and real time interactions with the platform. Attendees will learn about other AI platforms that are creating graphic design elements at the push of a button...pre-set examples and real-time interactions.Attendees will discuss the pros & cons of AI in marketing + branding and share their perspectives with one another. Attendees will learn about the cost savings and the time savings associated with using AI, should they choose to.
When most people in the industry talk about online or digital reputation management, what they're really saying is Google search and PPC. And it's usually reactive, left dealing with the aftermath of negative information published somewhere online. That's outdated. It leaves executives, organizations and other high-profile individuals at a high risk of a digital reputation attack that spans channels and tactics. But the tools needed to safeguard against an attack are more cybersecurity-oriented than most marketing and communications professionals can manage. Business leaders Leaders grasp the importance; 83% of executives place reputation in their top five areas of risk, yet only 23% are confident in their ability to address it. To succeed in 2024 and beyond, you need to turn online reputation on its axis and think like an attacker.
Key Takeaways:
- New framework for examining and safeguarding an online reputation
- Tools and techniques to keep you a step ahead
- Practical examples that demonstrate when to act, how to act and how to recover
Short video marketing has sweeped the nation and is the fastest way to build an online brand on social media in 2024. In this session you will learn:- What is short video marketing- Which platforms work best for your business- Content strategies that are on brand for your business- How to sell organically without paying for ads.
How to Run Landing Page Tests On and Off Paid Social PlatformsVWO
Join us for an exclusive webinar featuring Mariate, Alexandra and Nima where we will unveil a comprehensive blueprint for crafting a successful paid media strategy focused on landing page testing.With escalating costs in paid advertising, understanding how to maximize each visitor’s experience is crucial for retention and conversion.
This session will dive into the methodologies for executing and analyzing landing page tests within paid social channels, offering a blend of theoretical knowledge and practical insights.
The Pearmill team will guide you through the nuances of setting up and managing landing page experiments on paid social platforms. You will learn about the critical rules to follow, the structure of effective tests, optimal conversion duration and budget allocation.
The session will also cover data analysis techniques and criteria for graduating landing pages.
In the second part of the webinar, Pearmill will explore the use of A/B testing platforms. Discover common pitfalls to avoid in A/B testing and gain insights into analyzing A/B tests results effectively.
3. Definitio
ns :
Big Data : The growth in the volume
of data and how fast it is created
and saved. Big data is usually
stored in computer servers.
Marketing : the activity of a
company that deals with buying and
selling a product or a service.
Marketing departments of a company
use slogans, packaging designs and
special advertisements to attract and
keep consumers.
3
5. 5
SPOTIFY CAMPAIGN Thanks, 2016.
It’s been weird
A Spotify advertisement in UK. Source :
Businessinsider.com
A Spotify advertisement in Los Angeles.
Source : dailyedge.ie
6. 6
Dear person who played « Sorry » 42 times on
Valentine’s Day. What did you do ?
Spotify
Spotify campaign in New York City. Source :
businessinsider
8. I- How big data is used in
marketing
A- Explanation of big data
B- The use of big data in
Marketing
C- Impacts
II- Case studies
A- Amazon,a leader in big data
use
B- Netflix, movies and data
C- Target, a calculated shopping
experience
Conclusion
8
9. I- How big
data is
used in
Marketing ?
A-Explanation of big data
4 V’s :
Volume : Scale of data
Variety : Different forms
of data
Velocity : analysis of
streaming data
Veracity : Uncertainty of
data
9
10. 4 V’s
10
6 Billion people
have cell phones
World population :
7 Billion
Poor data quality costs : $
3.1 Trillion a year (US)
By 2016, 100 million
wearable, wireless health
monitors
1 TB Of Trade Information in
NY Stock Exchange during each
session
11. B- The use
of big data
in
marketing
Customer’s analytics, operational
analytics, new product and service
innovation and data warehouse
optimization
Customer Relationship Management
(CRM)
Key Performance Indicator (KPI)
Geomarketing
44 % of B2C Marketers use big
data to attract more customers and
keep them
$ 1 trillion of marketing
expenditures
11
12. 12
Identify valuable
opportunities.
Develop pictures of their customers
and create the perfect products for
them.
Systems track key words. Prices
change because of consumer’s
preferences,comparisons, inventory
and predictive analysis.
13. C-Impacts
13
4 million jobs created (SEO,
SEM… )
An increase of consumption and
profits
Gain of time for companies
Consumer privacy threats
Predictive analysis
Tracking free search
engines
Ethical issues
Exclusion
More corporate inequality
More adblockers
Lots of errors
22. Conclusio
n
Big data has positively affected
marketing. Companies know better
their customers and can perfectly
match consumers’ needs with their
products.
Nevertheless, consumers’ privacy may
be in danger because of big data. Are
all of our data well used by
companies ?
22
23. I’M WITH BIG DATA
MAKE MARKETING GREAT AGAIN
Source : Openclipart.org
Thank you
for your
attention !
23
24. Debate :
Are you afraid of big data ?
Are you aware that all of your data are
stored ?
Will you change your habits on internet ?
24
