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MarTech and AdTech
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Mobile App Intelligence
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Paid Search Advertising
Ad deliveryAd extensionsAd MediationAd strengthAd ViewabilityAutomated bid strategyAverage Order Value (AOV)Combined audiencesConversion AttributionConversion TrackingCost per acquisition (CPA)Floodlight TagHeadline TestingImpressionsKeyword ResearchLocation-based Advertising (LBA)Path Length ReportQuality scoreReturn on investment (ROI)SitelinksSmart BiddingSmart ListsUser IDView-through conversion windowYield Management
Social Media Sensing
Ad ViewabilityCommunity ManagerCountry ReachImpressionsInstant MessagingLocation-based Advertising (LBA)MicrobloggingNet Media CostPinterestPlayable AdsReachReputation ManagementRewarded Video AdsRich PinsSnapchatSocial Media ConversionsSocial Media ListeningUser-Generated Content (UGC)Video Companion Impressions
Technology and Innovation
Artificial IntelligenceBig DataBlockchainData WarehouseDeep LearningDisruptive InnovationInternet of ThingsMarketing Technology StackPredictive Data AnalyticsPredictive SegmentationPrescriptive AnalyticsR AnalyticsVoice Assistants
TV Ad Measurement and Insights
Ad ViewabilityAd-supported streaming video on demand (ASVOD)Addressable TVAdvanced TVAutomatic content recognition (ACR)Broadcast Addressable TVHousehold DataLocation-based Advertising (LBA)Multichannel Video Programming Distributor (MVPD)Nielsen RatingsOver-the-top (OTT)Skinny BundleSubscription video on demand (SVOD)Targeting Rating Point (TRP)Television advertisementTelevision Viewer Rating (TVR)TV NetworkUpfrontsVideo on demand (VOD)
Data mining is an automated analytical method that lets companies extract usable information from massive sets of raw data. Data mining combines several branches of computer science and analytics, relying on intelligent methods to uncover patterns and insights in large sets of information.
One of the defining characteristics of this method of analysis is its automation, which involves machine learning and database tools to expedite the analytical process and find information that is more relevant to users.
What is data in data mining?
Data mining is the process of analyzing hidden patterns of data according to different perspectives for categorization into useful information, which is collected and assembled in common areas, such as data warehouses, for efficient analysis, data mining algorithms, facilitating business decision making.
What is data mining process?
Data mining process is the discovery through large data sets of patterns, relationships and insights that guide enterprises measuring and managing where they are and predicting where they will be in the future.
Where is data mining used?
Data Mining is primarily used today by companies with a strong consumer focus — retail, financial, communication, and marketing organizations, to “drill down” into their transactional data and determine pricing, customer preferences, and product positioning, impact on sales, customer satisfaction, and corporate profits.
What is the procedure of data mining?
Despite its name, data mining isn’t always about extracting pure data from a mountain of information, but rather identifying important patterns and trends that emerge from the set. In this respect, data mining is similar to certain aspects of data exploration. See the full article for more details.
Why is data mining needed?
Data mining helps analysts to recognize significant facts, relationships, trends, patterns and anomalies which might go unnoticed otherwise. In business, data mining is useful for discovering patterns and relationships in data to help make better decisions.
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