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Case Study:
Customer Experience
Objectives
Alpha Matica was engaged to review the customer experience for a European service provider with three underlying objectives:
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Improve operational delivery.
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Create opportunities for revenue generation.
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Design the foundation for a multi-channel AI ecosystem and reflect on the employee development and upskilling programs.
NPS*: Net Promoter Score
Ways of Operating
Alpha Matica partnered with the senior leadership team across critical departments and respective stakeholders from Customer Experience, Technology, Data & AI, Operations and Call Center:
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Customer Journey Mapping and Capabilities Assessment: We initially identified and formalised core customer journeys at a high level. We evaluated existing processes, technologies, and capabilities to capture customer interactions and data. We identified pain points and areas for improvement where AI solutions could significantly impact the business.
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Pain Point Identification: We initially reviewed and analysed customer experience feedback, agent notes, and other surveys, such as NPS and internal CX measures. Using traditional NLP and GenAI technologies, we identified clear friction points with established trends.
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Call Centre Prioritisation: Based on these two reviews conducted in parallel, call centre operations were identified as the top priority. Beyond a simple economic rationale, the senior leadership team optimised call agent handling time to enhance the customer's and agent's experience.
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Implementation: A generative model was implemented and deployed to automatically summarise the transcript generated by third-party software. Based on agent feedback, we established a quality framework to compare the performance of different large language models (LLMs). In addition to operational and technology costs, this framework provides a robust selection process for the release of new LLMs over time.
Outcome and Benefit
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For this transcript summarisation initiative, the generative AI project saved an average of 30 seconds of handling time
on a call.
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Overall, this project saved over 5% of the overall costs.
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The customer experience and NPS improved by 3% as the overall waiting time of calls decreased due to the reallocation of resources.
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The staff retention rate increased by 4% as the agent experience improved with decreased cognitive load.
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From the technological landscape, this project was the first successful milestone of the GenAI application. It provided a successful foundation for generalising GenAI to other channels such as messaging, live chat, email, and social media.
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Beyond channel diversity, the company planned to invest in different areas of generative AI, such as customer experience hyper-personalisation, knowledge management and real-time agent assistance.
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Alpha Matica helped the company overcome organisational and technological challenges, such as the importance of GenAI performance metrics, AI governance, and user experience during the design phase.
