CRM and Big Data Overview

Gathering and analyzing customer data to improve understanding and engagement.

Understanding customers' needs and preferences through data analysis.

Tailoring marketing and communications to individual customers based on their data.

Encouraging customers to provide feedback on products and services.

Using data to understand customer preferences and predict behavior.

Using real-time data to respond quickly to customer needs.

Using data to streamline CRM processes and simplify customer interactions.

Collecting data from various sources, such as website activity, social media, and customer surveys.

The process of managing customer interactions using technology to automate business processes. It encompasses sales, marketing, and customer service activities, with the goal of attracting new customers, nurturing existing ones, and building lasting relationships.

Analyzing large datasets to uncover valuable insights that can improve decision-making and provide a competitive advantage for businesses. It involves collecting, cleaning, and analyzing data using advanced tools and techniques.

Using data analytics to improve the performance of machines and devices. Companies like Toyota are integrating data analytics into their cars to enhance safety and efficiency.

A method of storing and accessing data over the internet, allowing businesses to efficiently manage and utilize data without needing to store it locally. Cloud computing offers scalability, accessibility, and reliability.

The use of data analytics to optimize the performance of machines and devices, ensuring safety and efficiency. This can involve analyzing real-time data from sensors and cameras, providing insights for adjustments and improvements.

The ability of cloud computing to maintain consistent availability and performance even when faced with challenges, providing businesses with confidence and reducing potential disruptions.

The use of technology to enable collaboration, creativity, and information sharing among users. Examples include wikis, blogs, and social media platforms.

Web 2.0 technologies, such as wikis, blogs, and social media, can facilitate collaboration, creativity, and information sharing beyond simple emailing and information retrieval. It allows for dynamic and interactive communication and knowledge creation.

Using large datasets to understand customer preferences and behavior, leading to personalized marketing and targeted campaigns.

Monitoring online conversations and social media to gather real-time customer feedback and insights.

Using big data to analyze buying patterns and personalize offers, advertisements, and discounts.

Analyzing customer interactions across websites, apps, and social media to understand their journey and preferences.

Big data helps companies measure the effectiveness of marketing campaigns and adjust strategies in real-time.

Big data can help predict customer churn and tailor retention strategies to keep customers engaged.

Big data can help companies identify and analyze customer needs, leading to new product development and innovation.

The potential of big data in CRM comes with challenges like data security, privacy, quality, and the need for expertise to analyze and interpret the data.

A type of customer relationship management (CRM) that leverages social media platforms to engage customers and build stronger relationships.

The process of gathering, analyzing, and interpreting large datasets to gain insights and make better decisions.

The systematic and comprehensive review of existing research on a specific topic to synthesize findings and draw conclusions.

The gap in technology adoption based on factors like age, gender, and economic status.

The impact of social media on public policy, particularly in the adoption of new technologies.

The combination of online and offline strategies to create a unified customer experience.

The use of technology to provide healthcare services remotely.

Big Data is characterized by its volume (large amounts of data), velocity (data generated at high speed), variety (data in different formats), and veracity (data accuracy and reliability).

Big Data Analytics can be used to improve marketing by better understanding customer preferences, personalizing campaigns, and optimizing marketing spend.

Customer Relationship Management (CRM) leverages customer data to improve customer relationships, personalize communications, and enhance overall satisfaction.

Big Data Analytics can improve CRM by providing a deeper understanding of customer behavior, preferences, and needs.

E-commerce companies use Big Data Analytics to personalize product recommendations, optimize pricing, and improve customer service.

Businesses can use Big Data Analytics to identify trends, predict future demand, and optimize supply chains.

Big Data Analytics is a powerful tool for various industries, with applications ranging from healthcare to finance, helping organizations to innovate and improve decision-making.

The idea that data is being generated at an increasingly rapid pace, creating a constant flow of information.

Refers to the variety of data sources and formats used in big data analysis. This includes structured data (like databases) and unstructured data (like images, videos, and social media posts).

The sheer volume of data being generated and collected. Big data involves dealing with massive amounts of information.

The process of analyzing data in real-time as it is generated, allowing for immediate insights and responses. Think about how data is used in traffic monitoring systems.

Techniques that involve using algorithms and statistical models to analyze large datasets and identify patterns, trends, and anomalies. This can include machine learning algorithms, clustering techniques, and data visualization tools.

The potential benefits of big data analytics include improved decision-making, enhanced efficiency, cost reduction, and better customer understanding.

Understanding and leveraging big data to improve decision-making and business outcomes helps companies gain a competitive advantage in their markets.

The evolution of web technology from static pages to interactive and user-generated content, allowing for greater connection and collaboration.

The latest iteration of the web, emphasizing decentralization, artificial intelligence, and blockchain technology, allowing for more secure, personalized, and transparent digital experiences.

A way to leverage massive datasets to understand customer behavior, preferences, and needs, leading to more effective marketing and sales strategies.

A CRM approach that focuses on creating and delivering value to customers by not only understanding their needs but also exceeding their expectations.

Large datasets with the characteristics of Volume, Velocity, Variety, Veracity, and Value.

The process of identifying and understanding the value of large datasets for strategic decision-making.

Using data to improve the efficiency and effectiveness of business operations.

Predicting future events based on historical data and patterns.

Creating emotional attachment and maximizing value chain strategies by understanding customer behavior and predicting trends.

Ensuring the security and integrity of data from diverse sources to maintain accuracy and reliability.

A CRM approach that focuses on leveraging social media data and insights to personalize customer interactions and enhance engagement. It's about utilizing social media as a valuable tool for understanding and connecting with customers.

Real-time data insights from social media are used to provide businesses with actionable information. This allows for informed decision-making and personalized marketing strategies.

Emphasizes the creation of value through customer relationships. It goes beyond simply selling products and focuses on building lasting relationships with customers.

Using data to personalize marketing and communications to each customer based on their individual needs and preferences.

Customer relationship management (CRM) refers to managing customer interactions and data to improve customer satisfaction and foster long-term relationships. It involves using technology to automate business processes and collect valuable customer insights.

CRM 1.0: This approach focused on providing personalized experiences for customers using data such as purchase history and preferences. It aims to create tailored marketing messages and targeted offers.

CRM 2.0: This approach leverages the social web to engage customers. It involves using social data insights, real-time feedback, and active customer engagement through social media platforms.

CRM 3.0: Value creation is central to this approach. It aims to build long-term relationships, understand customer needs, and go beyond traditional product-centric marketing.

CRM systems using Web 3.0 technologies can analyze user behavior in real-time. This means they can understand what users are doing and tailor responses based on individual preferences.

Semantic search focuses on understanding the intent behind a search query, not just matching keywords. This makes search results much more relevant. It's like searching for 'restaurants near me' and getting results for nearby restaurants, not just a list of websites with the words 'restaurants' and 'near'

Behavioral advertising uses your web browsing history, preferences, and habits to show you targeted ads. So if you're researching laptops, you might see ads for laptops.

CRM 3.0 is a new model of CRM that leverages user empowerment, better security, and AI/ML for better customer insights, improved relationships, and data-driven decision making.

Customer empowerment means giving customers more control over their data and interactions. They can choose how their information is used, and they have more power in the relationship with a company.

Better security is essential in CRM 3.0 as customer data is increasingly important. This means protecting data from breaches and ensuring user privacy.

CRM 3.0 leverages AI and Machine Learning to automate tasks, analyze data, and improve customer interactions.

The business benefits of CRM 3.0 include deeper customer insights, better personalization, stronger customer relationships, and improved data-driven decision making.