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PROPOSAL FRAMEWORK (MAPPED MKT APPLICATIONS (Analysis (Sentiment Analysis,…

- - - - from Attachment :check:
      - Media Plans Aggregation :check:
  - - - Semantic Markup :star:
        
        Article markup
        
        Product markup
        
        Person markup
        
        Event markup
      - Semantic Prediction :star:
- - - - Semantic Analysis (ML)
      - Decision Trees
      - Regressions
      - Artificial Neural Network
    - - Deep Boltzmann Machine (DBM)
      - Deep Neural Networks
      - Convolutional neural networks
- - - - Cross products
        
        Semantic Prediction
        
        Viral Prediction
        
        Concept: semantic algorithm to predict the probability of a content goes viral
    - - KOLAB Dashboard
        
        Analytics
        
        Semantic Analytics
        
        Concept: is the use of ontologies to analyze content in web resources. This field of research combines text analytics and Semantic Web technologies like RDF. In one short sentence is giving meaning to data to drill down into specific categories, better analyze it and get insights.
        
        #1 Semantic Markup - Idea Description: add semantics to KOLAB Dashboard markups to reinforce the meaning of the information and track the effectiveness of marketing actions and bring it to a whole new level
        
        using schema.org vocabulary to specify a semantic markup. e.g. Event markup rock concert: band (itemprop="performer"), venue (itemprop="eventVenue"), event name (itemprop="name"), and time (itemprop="startTime").
        
        Why implement? to create web content that is both human and machine readable. Meaning, it becomes more accessible since computers are better able to analyze its content, index it and deliver it. Developers are better able to tie different sources of information together into new web services.
        
        How to do it: social tags -> Social tagging is a way to share and categorize online content that enables users to express their thoughts, perceptions, and feelings with respect to diverse concepts. In social tagging, content is connected through user generated keywords—“tags”—and is readily searchable through these tags. The rich associative information that social tagging provides marketers new opportunities to infer brand associative networks.
        
        Hyoryung Nam and P.K. Kannan (2014) The Informational Value of Social Tagging Networks. Journal of Marketing: July 2014, Vol. 78, No. 4, pp. 21-40.
        social tag–based brand management metrics capturing
        brand familiarity, favorability of associations, and competitive overlaps of brand associations can explain
        unanticipated stock returns. In addition, they find that in managing brand equity, it is more important for strong
        brands to enhance category dominance, whereas it is more critical for weak brands to enhance connectedness.
        These findings suggest a new way for practitioners to track, measure, and manage intangible brand equity;
        proactively improve brand performance; and influence a firm’s financial performance
        
        add advanced tracking analysis using GTM (Google Tag Manager) to create a Macro that looks for semantic markup in the code of a page. We can then use a Rule to fire a Tag every time someone views a page that has semantic markup on it and include event labels that record what type of entity that person looked at. Ultimately, this will let us drill down into analytics and view reports to see how marked up pages perform against their non-marked up counterparts. We can even pull out granular properties of entities and analyze based on those (for example, pull the "performer" item property out of all "Event" entities and see which "performers" got more traffic and/or led to more conversion events).
        https://www.google.com/analytics/tag-manager/
        
        Question: Why add semantics to an Analytics that you already get information from?
        
        Semantics focuses on the organization of and action upon information by acting as an intermediary between heterogeneous data sources, which may conflict not only by structure but also context or value (semantic integration) is the process of interrelating information from diverse sources
        
        Strengths
        
        Add meaning to data
        
        Personalize customer experience
        
        Connect data from different sources
        
        Preparation to IoT
        
        What kind of Business Intelligence can be pulled from it?
        
        1 more item...
      - Half-Life #
- - - - Advertising
        
        Weather-based Advertising
    - - Prediction
        
        Viral / Post Prediction
        
        went viral
    - - Analysis
        
        Social Network Analysis
        
        Marketing Analysis
    - - Analysis
        
        Marketing Analysis
        
        Social Network Analysis
    - - Analysis
        
        Big Data Analysis
        
        Social Network Analysis
        
        Competitor Analysis
    - - Analysis
        
        Social NetworkAnalysis
        
        Competitor Analysis
      - Reputation
        
        Product Reputation
    - - Automation
        
        Spreadsheet Validation
        
        Spreadsheet Consolidation
    - - Automation
        
        Spreadsheet Validation
    - - Search
        
        Keywords Alert
    - - Automation
        
        Data Entry and Update
        
        from Attachments
    - - Data Storage
        
        Data Lake
    - - Analysis
        
        Social Network Analysis
    - - Automation
        
        Data Entry and Update
        
        Media Plans Aggregation
    - - Analysis
        
        Social Network Analysis