コンテンツ配信

クロスプラットフォームでのマーケティングキャンペーン管理システム。

A glass jar filled with popcorn is placed on a dark wooden table. In the background, there's a blurred image of a tablet or screen displaying a grid of colorful thumbnails, suggesting a streaming service interface.

A glass jar filled with popcorn is placed on a dark wooden table. In the background, there's a blurred image of a tablet or screen displaying a grid of colorful thumbnails, suggesting a streaming service interface.

データ分析

リアルタイムのデータを活用した分析機能。

A small group of people are gathered in a modern conference room. One person stands by a whiteboard presenting a diagram labeled 'UGC Types', while the others are seated around a wooden table with laptops and papers. A large screen on the wall displays content related to the presentation.

A small group of people are gathered in a modern conference room. One person stands by a whiteboard presenting a diagram labeled 'UGC Types', while the others are seated around a wooden table with laptops and papers. A large screen on the wall displays content related to the presentation.

エンゲージメント

オーディエンスのエンゲージメントを最大化します。

A person is sitting on a brown couch while using a laptop. The individual is wearing a black hoodie and a cap, and appears to be browsing a website or app. The web page shows some sort of promotional or advertisement content. There is another person partially visible, sitting nearby on a blue chair.

A person is sitting on a brown couch while using a laptop. The individual is wearing a black hoodie and a cap, and appears to be browsing a website or app. The web page shows some sort of promotional or advertisement content. There is another person partially visible, sitting nearby on a blue chair.

Two people stand in front of a whiteboard covered with colorful sticky notes. The notes are arranged into categories: 'User-Generated Content,' 'Engagement,' 'Event,' and 'Social Wall.' The individuals appear to be in discussion, with one holding a marker.

Two people stand in front of a whiteboard covered with colorful sticky notes. The notes are arranged into categories: 'User-Generated Content,' 'Engagement,' 'Event,' and 'Social Wall.' The individuals appear to be in discussion, with one holding a marker.

トレンド分析

トレンドパターンを特定し、戦略を最適化。

推奨システム

最適な公開時期とプラットフォームを提案。

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Two individuals stand in front of a whiteboard covered with multicolored sticky notes and arrows. One person points towards the whiteboard, which has handwritten words like 'User-Generated Content', 'Engagement', 'Event', and 'Social Wall'. The setting appears to be a collaborative or educational environment.

Two individuals stand in front of a whiteboard covered with multicolored sticky notes and arrows. One person points towards the whiteboard, which has handwritten words like 'User-Generated Content', 'Engagement', 'Event', and 'Social Wall'. The setting appears to be a collaborative or educational environment.

ギャラリー

クロスプラットフォームでのコンテンツ配信を最適化します。

A conference room setting with several laptops on a large table, each being used by a person. A large screen displays a blue interface with the text 'Generate ad creatives from any website with AI'. A stainless steel water bottle and a conference phone are also visible on the table.

A conference room setting with several laptops on a large table, each being used by a person. A large screen displays a blue interface with the text 'Generate ad creatives from any website with AI'. A stainless steel water bottle and a conference phone are also visible on the table.

A display window with a variety of movie posters and DVD covers lined up on shelves. The collection includes both classic and contemporary films, and the setup has a vintage aesthetic due to the black and white photography. The titles and images are visible through the reflection of the glass, adding an artistic layer to the scene.

A display window with a variety of movie posters and DVD covers lined up on shelves. The collection includes both classic and contemporary films, and the setup has a vintage aesthetic due to the black and white photography. The titles and images are visible through the reflection of the glass, adding an artistic layer to the scene.

マーケティング支援

クロスプラットフォームでの最適なコンテンツ配信を実現します。

トレンド解析

過去とリアルタイムデータを解析し、トレンドパターンを特定します。

A television screen displaying a user interface with popular streaming service apps including Netflix, Sky, Apple TV, Prime Video, and others. The screen also shows images from movies or shows above the apps. The room is dimly lit with a potted plant visible on the side.

A television screen displaying a user interface with popular streaming service apps including Netflix, Sky, Apple TV, Prime Video, and others. The screen also shows images from movies or shows above the apps. The room is dimly lit with a potted plant visible on the side.

エンゲージメント最適化

データに基づき、オーディエンスのエンゲージメントを最大化する戦略を提供します。

ターゲット推薦

最適なプラットフォームとコンテンツ形式を動的に推奨します。

A television screen displaying the ESPN+ streaming interface with various sports-related shows and categories. The screen includes sections such as 'Browse by Shows' and 'Best of Drew Brees' with thumbnails of sports programs featuring athletes in action and analysts.

A television screen displaying the ESPN+ streaming interface with various sports-related shows and categories. The screen includes sections such as 'Browse by Shows' and 'Best of Drew Brees' with thumbnails of sports programs featuring athletes in action and analysts.

A computer screen displaying a coding interface with Python code related to machine learning. The code imports libraries like sklearn and deals with model metrics such as precision and recall. A classification report is shown along with a section titled 'Different meta model trained' listing various models like DT, RF, LR, and XGB. Below, there is code for tuning an XGB model using GridSearchCV.

A computer screen displaying a coding interface with Python code related to machine learning. The code imports libraries like sklearn and deals with model metrics such as precision and recall. A classification report is shown along with a section titled 'Different meta model trained' listing various models like DT, RF, LR, and XGB. Below, there is code for tuning an XGB model using GridSearchCV.