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Brilliant analysis and article from McKinsey & Company. Data is the fuel in the Age of AI. Let me add another category that no one has thought of: the data that drives Stars: Celebrities, Athletes and Influencers. Until now, the data that Stars and their teams have access to from social media is crumbs and unpurified junk. Enter DataLucent. This is one of our Creator Empowerment Tech companies that already serves as a true data and insights fiduciary to the world’s top tier Stars. DataLucent continually gathers each of the Stars’ data from all social media platforms, including all fan interactions and DMs, and in their own private data vault, purifies it and empowers each Star to monetize it in multiple ways and revenue streams. DataLucent has secured the critical Star legal and agent partnerships to thrive. High Performance/High Trust Relationships, including investments. A pipeline of top Stars. Imagine the size and quality of that data trove, individually and collectively. Name a larger consumer data trove full of consented data on the planet. That’s an entire new innovation. What Peter Thiel calls a Zero to One innovation.

💡 Ready to Challenge Conventional Thinking? 💭 Delve into this insightful article on data science and marketing strategies that will make you rethink the status quo. Here are some intriguing points to ponder: 🤔 **Reimagining Targeting**: Explore how data science is reshaping the way marketers identify and engage with their audience, leading to more personalized campaigns. 🔍 **Questioning Assumptions**: Reflect on the benefits of using data science in marketing analytics and how it challenges traditional marketing paradigms. 💬 **Provoking Thought**: How can aspiring data scientists carve a niche in the marketing world and redefine the future of customer engagement? 🌟 **Breaking Barriers**: Learn from industry giants like Netflix, Facebook, and Google on how they leverage data science to innovate marketing strategies. Let's spark some engaging conversations and challenge the norms together! 🌐💡 https://lnkd.in/eZuESk3q

💥 "Unlocking the Power of Social Media Data: A Game Changer for Business Strategy" 🙌 ✨ In today's digital era, social media is not just a platform for social interaction; it's a goldmine of consumer insights and trends that can redefine how businesses operate and engage with their audience. As a Data Solutions Analyst, I've had the unique opportunity to delve deep into the intricacies of social media data, uncovering patterns and insights that are invisible to the naked eye but invaluable to any business. 1. The Unseen Value of Every Like, Share, and Comment Every interaction on social media, whether a like, share, or comment, is a piece of the puzzle in understanding consumer behavior. By analyzing these interactions, we can identify emerging trends, gauge brand sentiment, and understand the effectiveness of marketing campaigns. This data, when analyzed correctly, provides a roadmap for crafting more engaging and impactful marketing strategies. 2. Real-Time Insights for Better Decision Making Social media data flows in real time, offering an unparalleled opportunity for businesses to make agile, informed decisions. In a fast-paced market, the ability to adapt and respond to consumer sentiment can set a business apart. Leveraging advanced analytics, we can transform this data into actionable insights, enabling businesses to pivot strategies swiftly and stay ahead of the curve. 3. Personalization at Scale In a crowded digital landscape, personalization is key to capturing consumer attention. Social media data allows us to understand individual preferences and behaviors, enabling businesses to tailor their offerings and communications at scale. This level of personalization not only enhances customer experience but also boosts engagement and loyalty. 4. Navigating the Challenges While the potential of social media data is immense, navigating the complexities of data collection, privacy regulations, and ethical considerations is crucial. Adherence to GDPR, CCPA, and other privacy laws is not just a legal obligation but a commitment to consumer trust and data security. 5. The Future is Data-Driven As we move forward, the integration of AI and machine learning with social media analytics will open new frontiers in data analysis, offering deeper insights and foresight into consumer behavior. The future of business strategy is unequivocally data-driven, with social media data at the forefront of this transformation. Conclusion The power of social media data extends far beyond mere numbers. It's about understanding the story behind each data point and using that knowledge to drive strategic decisions. As Data Solutions Analysts, our role is to unlock these stories, turning data into a strategic asset that can propel businesses into new realms of success. Let's embrace the power of social media data to innovate, personalize, and lead in the digital age. #DataAnalytics #SocialMediaInsights #BusinessStrategy #DataDrivenDecisionMaking

Streamlining Marketing Campaigns with Data Science Data science is a powerful tool for enhancing marketing campaign effectiveness. By leveraging data-driven insights, businesses can optimize targeting, personalize content, and measure performance with precision. Data science techniques like K-means clustering can be used to group customers based on similarities in behavior, demographics, or preferences. This enables marketers to create tailored campaigns for each segment, improving relevance and engagement. Also, incorporating machine learning algorithms into a website or application will help analyze customer data, such as interactions and purchase history, to recommend products or services aligned with individual preferences. This personalized marketing approach increases conversion rates and customer satisfaction while enhancing the customer experience and driving loyalty. Data visualization tools like logistic regression and decision trees give strategic insights into customer behavior, such as the likelihood of purchase or churn. These insights allow decision-makers to proactively address customer needs and optimize campaign timing and content. By leveraging data science, businesses can create more targeted, personalized, and effective marketing campaigns, that drive better results and maximize return on investment. Looking for a passionate and strategic data scientist? Feel FREE to send me a message here on LinkedIn or via email, olalekanabdulmumeen3@gmail.com, or WhatsApp/call directly at +2347053053024. #marketing #campaign #marketingcampaigns #datascience #lookingfordatascientist #datascientistintern

Revolutionizing Media & Entertainment with Big Data Insights Industry Snapshot: In the dynamic realm of media and entertainment, the race for a customer-centric approach intensifies. Big data analytics adoption becomes imperative for enhanced experiences and reduced attrition, enabling seamless access and analysis of vast data volumes. Big Data Challenges Insights: Industry Dynamics: Rapid industry growth brings challenges of balancing costs and revenue amidst diverse consumer media habits. Challenges: The rise of online platforms introduces hurdles - data privacy concerns, financial constraints, talent acquisition difficulties, and limited broadband penetration. Growth Factors: Staying relevant in the digital landscape and ensuring mobile compatibility are pivotal. Overcoming big data challenges involves addressing privacy concerns, financial constraints, talent acquisition difficulties, and limited broadband penetration. Use Cases in Inventory Control Management: Enhanced Data Privacy: Big data solutions tackle leaks, ensuring user data accumulation for accurate analysis. Financial Alternatives: Cloud storage and SaaS solutions offer alternatives for SMEs facing financial constraints. Talent Acquisition Solutions: Organizations like Quantzig bridge the gap amid the shortage of data science professionals. Insights Despite Limitations: Big data aids in gaining customer behavior insights despite limited broadband penetration. Audience Interest Prediction: Big data provides a profound understanding, enabling content alignment with viewer preferences. Optimized Media Scheduling: Big data facilitates direct interaction through scheduled media streaming, maximizing profits. Impact of Big Data: Transformative Influence: Revolutionizing content personalization, audience insights, targeted marketing, and informed content creation. Tailored Recommendations: Big data enables personalized content recommendations, enhancing user engagement. Deeper Audience Insights: In-depth insights drive targeted marketing, delivering more relevant ads. Guiding Content Creation: Predicting trends offers valuable guidance, refining content strategies for success. Core Activities in the Industry: Foundational Activities: Content creation, distribution, broadcasting, advertising, marketing, and digital transformation. Essential Role: Effective marketing and advertising are crucial for promoting content and products. Embracing Digital: Adapting to changing consumer preferences, the industry focuses on digital media and streaming. Future Anticipation – Inventory Control Management: AI-Driven Analytics: The future unfolds with AI-driven big data analytics, predicting consumer needs and optimizing operations. Quantzig's Role: Quantzig's solutions play a pivotal role in catering to the evolving media and entertainment landscape. https://lnkd.in/gW_WJjtG https://lnkd.in/gpnAw_rK

🌏 Location Analytics leveraging Social Media Data #location #analytics #socialmedia #geoprocessing #gis #geographicalanalytics #dataanalytics #event ✅Around 2 billion active users on social media who keep on recording their location information through their activities like posts, comments to post, blogs, photo tagging, event tagging and other similar activities on social platforms like Facebook, Twitter, LinkedIn and many more. ✅The recorded location data is a rich source of semi structured and unstructured location information that can be processed and exploited using location-based analytics to get customer preferences, usage patterns, pain areas, choices and wish list location wise. ✅Location data analytics using social media data involves extracting, analyzing, and interpreting geographic information embedded within social media content. ✅APIs provided by social media platforms which allow retrieval of location-tagged posts or user profiles with location information are one of the key enablers to extract data. Also large data repository capable of storing and processing huge amounts of unstructured and structured location data play a vital role to store and process data ✅The data extracted can be used for various type of analysis Key Analysis: 📌 Spatial Analysis: This includes mapping the locations of posts, users, or events to visualize spatial patterns and distributions 📌 Sentiment Analysis: Natural Language Processing techniques can be applied to analyze text content to understand opinions, trends, or issues associated with different places. 📌 Time-based analysis: Particularly useful for understanding seasonal variations, event-driven activities, or changes in user behavior in different locations ✅The processed analysis results can be leveraged by the organizations for various business use cases such as: 👉monitoring events or incidents in real-time 👉Public health and safety 👉Urban planning 👉Event planning 👉Public health and Safety 👉customer demographics 👉Targeted Marketing ✅location data analytics using social media data offers a powerful tool for understanding spatial dynamics, consumer behavior, and societal trends across various domains, contributing to informed decision-making and targeted interventions.

In a world full of promises that AI can bring, it’s important to uncover the complexities that lie beneath the surface.   I had the pleasure of interviewing Gareth Powell, a leader in Data & Analytics, to explore the importance of data strategy in transformation projects and the implementation of the latest technological advancements. Gareth is hailed as one of the UK's top influencers shaping the data narrative and he shares invaluable insights from kickstarting transformative data endeavours, to staying ahead in the tech game. 📖 Check out the interview today: https://lnkd.in/eBAqzmpH   #DataStrategy #TechTransformation #AIComplexities #DataLeadership #TechInnovation #DataNarrative #DigitalTransformation #DataInsights #TechLeadership

🚀Harnessing Data Science in DSPs, SSPs, and DMPs 🚀 In the dynamic world of AdTech, Data Science is redefining how Demand-Side Platforms (DSPs), Supply-Side Platforms (SSPs), and Data Management Platforms (DMPs) operate. Here’s a closer look at the transformative impact: 🔄 Demand-Side Platforms (DSPs) 🌟 Precision Targeting: Data Science empowers DSPs to deliver highly targeted ads by analyzing user behavior, demographics, and preferences. This ensures that ads reach the most relevant audiences, enhancing engagement and conversion rates. 📊 Bid Optimization**: Machine learning algorithms enable DSPs to optimize bidding strategies in real-time. By predicting which ad impressions are most likely to perform well, DSPs can allocate budgets more efficiently and maximize ROI. 📈 Predictive Analytics: DSPs leverage predictive analytics to forecast trends and user actions. This allows advertisers to stay ahead of market shifts and adjust their strategies proactively. 🔗 Supply-Side Platforms (SSPs) 💡 Inventory Management: Data Science helps SSPs manage ad inventory more effectively. By analyzing supply and demand patterns, SSPs can price inventory dynamically and maximize fill rates. 🔍 Fraud Detection and Prevention: Advanced algorithms detect fraudulent activities by monitoring traffic and identifying anomalies. This ensures that only genuine impressions are served, protecting both publishers and advertisers. 🚀 Yield Optimization: SSPs use data-driven insights to optimize yield for publishers. By understanding which ad formats and placements perform best, SSPs can enhance revenue generation. 📊 Data Management Platforms (DMPs) 🌐 Comprehensive Data Collection: DMPs gather data from various sources, including websites, mobile apps, and offline channels. This consolidated data provides a 360-degree view of the audience. 📈 Segmentation and Analysis: Data Science enables DMPs to segment audiences based on detailed criteria. This segmentation allows for more precise targeting and personalized ad experiences. 🔄 Data Activation: DMPs activate data across DSPs and SSPs, ensuring that the right message reaches the right audience at the right time. This seamless integration enhances the effectiveness of advertising campaigns. 🌐 The Synergy of DSPs, SSPs, and DMPs 🔄 Seamless Integration: Data Science facilitates better integration between DSPs, SSPs, and DMPs, creating a more transparent and efficient ad ecosystem. Real-time data exchange and analysis lead to smarter decisions and improved campaign performance. 🌍 Holistic Insights: By combining data from DSPs, SSPs, and DMPs, stakeholders gain a comprehensive view of the advertising landscape. This holistic perspective drives more informed strategies and better outcomes. --- #AdTech #DataScience #DSP #SSP #DMP #DigitalMarketing #ProgrammaticAdvertising #MachineLearning #AdvertisingInnovation

Extracting Data from Facebook Email us at: info@datascrapingservices.com Leverage the potential of social media data with Datascrapingservices.com! 🚀📊 Our expertise in extracting data from Facebook allows businesses to analyze market trends, target audiences, and optimize their digital strategies. Gain valuable insights and stay competitive in the dynamic social media landscape. Contact us for tailored data extraction solutions! Email us at: info@datascrapingservices.com to ask how we can help you scrape your data. #extractingdatafromfacebook #scrapingfacebookdata #facebookpagescraping #facebookcommentscraping #facebookeventdatascraping #facebookprofilescraping #facebookpagescraping #facebookreviewscraping #facebookbusinesspagescraping #facebookdatascrapingservices #datascrapingservices #datamining #dataanalytics #webscraping #datascraping #webscrapingexpert #webcrawler #webscraper #datamining #dataentry #emaillistscraping #emaildatabase

Integration of Artificial Intelligence, Ground Based Intelligence, Psychographic Modeling, and Simple Demographic Data: Marketing Into the 22nd Century. 10 years ago, I began a new adventure in marketing and business services. Integration of or the combining of multiple disciplines in business intelligence has been an ongoing personal research project, now adding the intense and thought challenging rise of Artificial Intelligence. That being said, the goal remains the same, that is, to provide practical applications for the wine, beer, spirits, and cider industries to leverage these powerful tools. For 14 years, the objectives have been and continue with: 1. Leveraging broad-based psychographic segmentation modeling (originally grounded on modeling work developed while building the Oak Ridge Winery brand portfolio [OZV, Moss Roxx, Old Soul, Gnarled Vine, Preccessi, Into Zin, and others]). 2. Integration all disciplines of business intelligence, now including Artificial Intelligence, into a usable single approach to consumer and business marketing; 3. Creation of a single platform of this integration; 4. Utilization this platform to Evolve go-to-market strategies for on and off premise sales, control brand development, and private label services, addressing the unique sales challenges in each of these areas of business intelligence, and; 5. Teach these principles also for the benefit of Direct to Consumer trade and to help refine best practices for online sales and tasting room development. Summarizing the first step of the process of integrating disciplines: 1. Cross-referencing & integration of ground-based analytics (the data direct from our phones, computers, & other ‘trackable’ digital trails), with; 2. ‘Simple’ demography data (I.e.: Baby Boomers, Millennials, etc), & then; 3. Viewing both disciplines from the perspective of ‘Fortune’ psychographic modeling (such as Experian’s Mosaic, ESRI’s Tapestry, &/or Neilsen’s Prism Segmentation data). 4. And finally viewing all data through the eyes of Artificial Intelligence. The realization is that no one has actually worked to combine these areas of business intelligence all the while multiple business intelligence service organizations are thriving (continuing to build massive ‘empires’) on limited data. One of the first projects I undertook was to integrate data simply by taking the demographic outline of age segments and cross-referencing them with the Experian Mosaic model. This exercise highlighted how many different psychographic segments crossed over into multiple demographic segments proving the lack of precision when basing brand and marketing development on demography alone (which is surprisingly still extremely prevalent in brand design and marketing campaign development). Let’s go offline & make it your plan of attack. See also, “Fish Where the Fish Are!” Nick ~ https://lnkd.in/gUvq32rK Bill Tolar William Arruda Annette Solomon, MBA, CS, DipWSET (candidate)