Professor Mohamed Zaki
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Professor Mohamed Zaki

Deputy Director of Cambridge Service Alliance

Professor Mohamed Zaki is the Deputy Director of the Cambridge Service Alliance at the Institute for Manufacturing, University of Cambridge. Mohamed received his PhD in Business Analytics from the Alliance Manchester Business School at the University of Manchester in 2013. Since then, his research interests have centred on digital service transformation, particularly the application of artificial intelligence (AI), to design and manage customer experience and create new data-driven business models. Mohamed has over 100 publications in highly ranked service management journals, conferences and practical outlets such as the Harvard Business Review. He has successfully generated funds from industry and UK research councils (a total contribution of over £10 million). Mohamed consulted and lectured for over 50 organisations, including Mitsubishi Heavy Industry, CEMEX, Caterpillar, IKEA and many others. He is the course leader for the Data-Driven Design for Customer Experience (CX) online course offered by the University of Cambridge Online.

Title: How AI can help firms to gain customer experience insights that matter

Abstract: The most common methods of tracking customer experience has a big blind spot: they cannot pick up on important emotional responses. As a result, qualitative surveys, like Net Promoter Score, end up missing critically important feedback. Even if they provide a positive score, customers often reveal their true thoughts and feelings in the open-ended comment boxes typically provided at the end of surveys, and AI can help companies make use of this valuable data to better predict customer behaviour. Specifically, there are six benefits for adopting AI to analyse this feedback: It can 1) show you what you’re missing in your qualitative comments generated from surveys and call centres, 2) help train your employees based on what’s actually important to customers, 3) determine root causes of problems, 4) capture customers’ responses in real-time, 5) spot and prevent declines in sales, and 6) prioritise actions to improve customer experience.

Key takeaways:

  1. Traditional single-metric approaches, like the NPS, fall short of capturing the full spectrum of customer experience in today's digital landscape.
  2. AI-driven analytics are vital for managing customer experience, enabling the collection of relevant CX data and generating actionable insights (attitudinal, behavioural and market).
  3. Customer experience data varies from structured to unstructured formats, all of which can be integrated and analysed using AI
  4. AI-based predictive models can integrate various data streams — encompassing attitudes, emotions, and behaviours — to forecast customer experience trends, aiding businesses in enhancing their customer experience strategies.