In today’s fast-paced digital world, companies are constantly looking for ways to improve the customer experience. Artificial intelligence (AI) has emerged as an essential tool for this mission, providing deep insights into customer behavior and driving strategic decision-making. Businesses across all industries have realized the value of customer data in refining their operations, enhancing customer experience and boosting profitability. In this blog, we investigate how using customer data with AI can help transform your business approach.

Understanding customer data

The customer journey encompasses every interaction between the customer and the company, from initial awareness to post-purchase support. Each of these interactions generates valuable data that, when analyzed and applied through AI, can dramatically enhance customer experience.

  • Demographic data: By understanding basic data such as age, gender and location, you can fine-tune your marketing activities to ensure relevance and customer engagement.
  • Transactional data: By understanding customer purchase history, you can refine your inventory, adjust your marketing and boost loyalty programs for a better shopping experience.
  • Behavioral data: You can improve the online experience by tracking how customers interact with your website and apps to identify and resolve any bottlenecks.
  • Social media data: Customer data you obtain from social media can help you understand public sentiment and engagement to refine brand strategies and effectively connect with audiences.
  • Customer feedback: You can use customer reviews and interactions to improve satisfaction through customer support.

Relevant use cases

1. Tackling information overload for a car parking company

Challenge: A well-known car parking company was facing operational challenges due to the size and diversity of its workforce. A large number of back-to-back calls led to an information overload and a lack of operational overview, which affected communication, maintenance and scheduling efficiency.

AI solution: The company implemented an AI-powered insights dashboard, with a speech-to-text solution at its core. This technology converted customer phone calls into text, allowing data to be easily analyzed and integrated into operational workflows.


  • Better communication: AI’s meticulous data logging improved decision-making accuracy.
  • Proactive maintenance: Prioritizing issues through AI-analyzed feedback enhanced customer contentment.
  • Efficient scheduling: AI predictions on busy periods optimized staff allocation, cutting down waiting times.

2. Improving customer support in an online pharmacy

Challenge: The online pharmacy receives ±4,000 emails per month with complex pharmaceutical queries. Ranging from drug safety questions, drug suitability questions, delivery questions, general queries and complaints. This number is expected to grow rapidly. The sheer volume and complexity of the emails made it difficult for the customer service team to respond promptly and accurately.

AI solution: To address this challenge, the online pharmacy uses generative AI and Large Language Models (LLMs), specifically leveraging OpenAI’s capabilities. The implemented solution involved a sophisticated pipeline that anonymized incoming emails to protect customer privacy. These anonymized texts were then processed to classify the intent of the email—whether it pertained to medicine safety, suitability, delivery, general inquiries or complaints. Once classified, the system utilized GPT-4 to generate high-quality, informed responses by drawing on a database of responses to similar historical emails. These generated responses were presented as draft emails to the customer service team. The drafts served as a foundation, which the customer service employees could then review, edit if necessary, and approve before sending to the customer.


  • Efficiency improvement: The time required to handle each email was significantly reduced, enabling customer service employees to manage a larger volume of inquiries with the same resources.
  • Scalability: The solution provided a scalable model that could easily accommodate the anticipated growth in customer inquiries without the need for proportional increases in staffing.

So what can we learn from this?

The essence of AI in business lies in its ability to sift through vast amounts of data and extract not only insights but also actionable predictions from it, enabling a more personalized, efficient and scalable customer experience.

Start seeing AI as your ally, where every piece of customer data is a stepping stone to greater customer satisfaction and business success. The future is all about understanding customer needs before they do!

Need help discovering how to transform your customer data into something that creates value and improves your customer experience? Get in touch with us! Our AI and Data Science experts are ready to help you make a difference in your business!

This blog is written in collaboration with Rick van Bellen – a Data Scientist at Mediaan Conclusion.