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GumGum
GumGum is a leading technology company specialising in contextual intelligence solutions for digital advertising. With its AI-powered platform, GumGum enables advertisers and publishers to unlock new opportunities for engaging audiences through relevant and non-intrusive ad placements. By leveraging advanced computer vision and natural language processing technologies, GumGum transforms digital advertising, delivering personalised and impactful experiences to users across the web.
![GumGum, digital advertising solutions company - NZMinds' AI and ML development company Singapore case study](../assets/img/case/case-ai-ml-3.png)
Our Approaches
GumGum adopts several key approaches to enhance digital advertising effectiveness :
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Contextual Intelligence: Utilising AI algorithms to analyse content and context on web pages, enabling advertisers to place ads alongside relevant and brand-safe content.
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Computer Vision: Harnessing computer vision technology to identify objects, scenes, and visual elements within digital content, facilitating targeted ad placements that align with user interests and preferences.
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Brand Safety: Implementing advanced brand safety measures to ensure ads are displayed in suitable environments, free from harmful or inappropriate content.
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Real-Time Optimization: Leveraging real-time data and machine learning algorithms to optimise ad placements based on user engagement metrics and performance insights.
![Read here Singapore AI ML application development company NZMinds' case study of GumGum, digital advertising solutions company](../assets/img/case/case-ai-ml-3c.jpg)
Key Features
GumGum's visual data platform provides access to a vast repository of visual content and metadata, which can be licensed for various applications such as market research, trend analysis, and content creation.
Computer Vision Solutions
GumGum provides computer vision solutions that enable machines to understand and interpret visual content in images and videos.
In-image Advertising
GumGum's flagship product is its in-image advertising platform. It allows publishers to monetize their visual content by embedding relevant ads directly into images on their websites. These ads are contextually relevant to the image content and appear seamlessly within the user experience.
In-stream Video Advertising
In addition to in-image advertising, GumGum offers in-stream video advertising solutions that allow brands to reach audiences with video ads placed within relevant video content.
Social Media Analytics
GumGum provides social media analytics tools that analyze visual content shared on social media platforms. This helps brands and marketers understand the impact of their visual content and identify opportunities for engagement and brand advocacy.
Contextual Targeting
By analyzing the visual context of images and videos, GumGum enables advertisers to target their ads more effectively, ensuring they are displayed in relevant content environments that align with their brand and campaign objectives.
Usage
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Sign Up: Create an account on the GumGum website and log in to the platform.
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Campaign Setup: Set up a new advertising campaign by defining campaign objectives, targeting criteria, and ad creatives.
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Content Analysis: GumGum's platform analyses web pages and digital content to identify relevant contexts and opportunities for ad placements.
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Ad Placement: Place ads alongside relevant content and ensure brand safety measures are applied to maintain brand integrity.
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Monitor Performance: Monitor campaign performance through real-time analytics dashboards and adjust ad placements and targeting parameters as needed to optimise results.
![AI ML Technology leveraged for GumGum, digital advertising solutions company - NextZen Minds' AI ML application development company Singapore case study](../assets/img/case/case-web-1-details-4.png)
Technologies
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Computer Vision Algorithms: Using deep learning and image recognition techniques to analyse visual content and extract relevant features, such as objects, logos, and text.
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Natural Language Processing (NLP): Employing NLP algorithms to analyse textual content and understand context, sentiment, and semantic relationships within web pages.
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Semantic Analysis: Applying semantic analysis techniques to understand the meaning and context of content, enabling more precise ad targeting and content matching.
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Predictive Modelling: Utilising predictive modelling and machine learning algorithms to anticipate user behaviour and optimise ad placements for maximum impact.