At Vanguard, we wanted to leverage data that we recorded in Client Relationship Management systems and other tools to more effectively serve our clients. We challenged ourselves to streamline and simplify this process – freeing up valuable time for our client facing teams, to work on addressing client needs and deepen client relationships.
Vanguard began experimenting with Natural Language Processing (NLP) models and leveraged machine-learning to standardize text and to identify key words and topics. With the assistance of a proof-of-concept group, we gathered critical topics and business concepts to help validate the model during the training phase. Based on the results gathered from the model, we created a dashboard allowing the users to perform pattern, trending and hot topic analysis – capabilities made possible by NLP.
The combination of an NLP-powered Tableau dashboard enabled the business to quickly interpret critical data to evaluate business relationships. The team now uses these expanded client insights to tailor their conversations accordingly – offering hyper-personalized communications and insight on plan design and investment options that best suit a particular client’s needs. From a company perspective, the implementation solidified the need for a data analytics and insights team that focuses on data driven business solutions. The data and insights team was formed less than a year ago and grew rapidly to over 40 members, ranging from data analysts, data engineers, data scientists, visualization specialists and product owners, who partner consistently with our institutional business. This team’s main goal is to provide trusted and timely data and insights to enable strategic business decisions. Leaders now have resources to explore hypotheses and create predictive models outside of their individual business units, so their crew can focus on their primary roles of serving clients.