Quin AI: Quin Audience Engine Offering Optimisation by Deep Learning

Quin AI：Quin 受众引擎通过深度学习提供优化

• 批准号: 10071276
• 金额: $ 5.98万
• 依托单位: QUIN AI LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10071276
• 关键词: Quin; AI; Audience; Engine; Offering

Predicting the needs and intentions of people based on their online behaviour is an important factor in building successful creative businesses through the personalisation of services, products, actions, and offers. Methods of data collection and behaviour prediction by understanding intentions have been studied in multiple domains. To create accurate and actionable predictions, the collected data must be generated from reliable sources, complete, concise, and relevant to the topic; timely and fresh enough to be actionable; fit for purpose and suited for its intended use; and reliable, meaning it is authentic and trustworthy.To achieve this, Quin AI uses Artificial Intelligence (AI) and deep learning to predict website visitors' in-session behaviour for automated and accelerated decisions without loss of privacy. Our expert team of data scientists, software engineers, business innovation experts, advertising professionals, and project managers will offer an improved product through this project, with the results directly benefitting advertising businesses in the creative industries.We have the experience, technical expertise, and knowledge to successfully deliver an innovative solution for the challenges being faced by the industry, with our current solution already proving an 30% incremental revenue boost with 50% savings in marketing costs.

根据人们的在线行为预测他们的需求和意图是通过个性化服务，产品，行动和优惠来建立成功的创意企业的重要因素。已经在多个领域研究了通过理解意图来收集数据和预测行为的方法。为了创建准确和可操作的预测，收集的数据必须来自可靠的来源，完整，简洁，与主题相关;及时和新鲜，足以操作;适合目的并适合其预期用途;和可靠，意味着它是真实和值得信赖的。为了实现这一点，Quin AI使用人工智能（AI）和深度学习来预测网站访问者的会话行为，以实现自动化和加速决策，而不会丢失隐私。我们的数据科学家、软件工程师、业务创新专家、广告专业人士和项目经理组成的专家团队将通过该项目提供改进的产品，其结果将直接惠及创意行业的广告业务。我们拥有经验、技术专长和知识，能够成功地为行业面临的挑战提供创新解决方案，我们目前的解决方案已经证明了30%的增量收入增长和50%的营销成本节省。