Pivigo worked with MADE.com, a furniture retailer making high-end lifestyle design accessible. MADE has a direct-to-business model that cuts out the middle-men, working directly with designers and customers. Customer service is crucial and meeting customer needs and responding to queries is at the forefront of what they do. MADE is also an online-only retail platform which is an ideal environment to accumulate data that can be analysed to improve elements of the business.
A group of aspiring data scientists from Pivigo’s Science to Data Science bootcamp worked intensively over five weeks to automate customer services, as MADE faced huge volumes of queries and found it difficult to keep up with demand.
Customer service is crucial to MADE, as they cut out the middle-men, working directly with designers. However, customer service agents face huge volumes of queries and MADE were looking to automate part of this service to keep up with demand.
MADE were dealing with 2300 queries a day, 800 submitted by email, with an average response time of two days. The S2DS team divided these queries into ones which were easy to respond to, i.e. a one-line reply would resolve the query and then those which were judged to be more complex. Of those more complex queries, a categorisation model built by the S2DS team found a relevant automated response from more than 100 category options.
The team analysed more than 17 million data points, both structured: orders and customer information, and unstructured data: correspondences with customer service.
To understand which response could be sent by the model, it required NLP (Natural Language Processing) to decipher the content of emails; as although they would be easy for a human to understand, without this, an AI would struggle.
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Again, Logistic Regression had the greatest precision when choosing a category for the query; for instance, the sentence, “I write you to know if you also deliver a sofa in Italy,” could be placed into an ‘Overseas Delivery’ category and the correct response sent by AI.