Customer Science, a customer experience and digital transformation company based in Sydney, has launched Knowledge Quest, an AI-powered knowledge management solution. The solution aims to improve efficiency in contact centres by providing real-time information, which can reduce handling times and increase customer and employee satisfaction.
Knowledge Quest was developed to address a common challenge in customer service: ensuring agents have quick access to accurate, up-to-date information. Outdated or incomplete information can lead to longer call handling times, repeat calls, and disengaged staff.
The solution works by creating new knowledge articles and providing insights into a company’s existing data. This information is displayed on a dashboard, allowing for updates to improve the accuracy of customer interactions.
According to Scott Ward, Director of Product at Customer Science, Knowledge Quest integrates with existing systems to analyse call, email, and chat data in real time. It identifies whether customer issues were resolved, what steps were taken, and the level of customer satisfaction. The tool can also identify knowledge gaps and automatically generate new draft articles that align with an organistion’s branding and format.
Ward notes that many contact centre tools depend on pre-existing, accurate knowledge articles. Knowledge Quest, however, actively creates new knowledge in real time. Its automated workflow helps organisations:
- Identify knowledge gaps by comparing real-time call content with existing information.
- Generate draft articles from successful customer resolutions captured during calls.
- Format content to meet organisational standards for use in platforms like Zendesk or Genesys.
- Monitor knowledge accuracy and resolution in real time.
Unlike generic AI solutions that may only identify common queries, Knowledge Quest integrates analysis and content creation into a single process. It is designed to tailor content to the specific needs and context of each contact centre. While off-the-shelf AI solutions may identify common customer queries, Knowledge Quest goes further by bridging analysis and content creation in a single, integrated process. Its ability to tailor knowledge to the unique ‘intent’ profile of each contact centre means that content is not generic but rather purpose-built for the business context.
At the heart of Knowledge Quest are processes to determine the semantic relationships between data to determine meaning and subsequent relationships enabling enterprises to democratise their information, transform siloed content into searchable, usable knowledge, and learn from every interaction.
