Lecture

Internship Insights: Machine Learning at Nestlé

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Description

This lecture presents an internship experience at Nestlé by a digital humanities master student from EPFL. The student discusses their six-month internship, focusing on two main projects that utilized machine learning. The first project aimed at predictive maintenance for coffee machines, addressing the challenges of high maintenance costs and customer satisfaction. The student explains how they conducted a literature review to select appropriate machine learning algorithms and developed a data pipeline for predictive analysis. This approach successfully reduced downtime and maintenance costs while enhancing customer satisfaction. The second project involved understanding customer churn through machine learning explainability, aiming to uncover reasons behind customer departures and provide actionable insights for retention strategies. The student highlights the importance of model interpretability to ensure stakeholders can understand the insights generated. Overall, the internship provided valuable experience in applying data science skills and fostering teamwork within a supportive environment.

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Related concepts (27)

Customer satisfaction

Customer satisfaction (often abbreviated as CSAT) is a term frequently used in marketing. It is a measure of how products and services supplied by a company meet or surpass customer expectation. Customer satisfaction is defined as "the number of customers, or percentage of total customers, whose reported experience with a firm, its products, or its services (ratings) exceeds specified satisfaction goals." Customers play an important role and are essential in keeping a product or service relevant; it is, therefore, in the best interest of the business to ensure customer satisfaction and build customer loyalty.

Maintenance

The technical meaning of maintenance involves functional checks, servicing, repairing or replacing of necessary devices, equipment, machinery, building infrastructure, and supporting utilities in industrial, business, and residential installations. Over time, this has come to include multiple wordings that describe various cost-effective practices to keep equipment operational; these activities occur either before or after a failure. Maintenance functions can be defined as maintenance, repair and overhaul (MRO), and MRO is also used for maintenance, repair and operations.

Customer retention

Customer retention refers to the ability of a company or product to retain its customers over some specified period. High customer retention means customers of the product or business tend to return to, continue to buy or in some other way not defect to another product or business, or to non-use entirely. Selling organizations generally attempt to reduce customer defections. Customer retention starts with the first contact an organization has with a customer and continues throughout the entire lifetime of a relationship and successful retention efforts take this entire lifecycle into account.

Customer relationship management

Customer relationship management (CRM) is a process in which a business or other organization administers its interactions with customers, typically using data analysis to study large amounts of information. CRM systems compile data from a range of different communication channels, including a company's website, telephone (which many softwares come with a softphone), email, live chat, marketing materials and more recently, social media.

Predictive maintenance

Predictive maintenance techniques are designed to help determine the condition of in-service equipment in order to estimate when maintenance should be performed. This approach promises cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted. Thus, it is regarded as condition-based maintenance carried out as suggested by estimations of the degradation state of an item. The main promise of predictive maintenance is to allow convenient scheduling of corrective maintenance, and to prevent unexpected equipment failures.

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