Strengthening and expanding knowledge about client behavior has become a complex task for banks. Today, technology based on predictive analytics, such as Next-Best-Action models which the consulting firm Bain & Company discusses in its corporate blog, have become an excellent aid that “allows companies to track a dynamic view of their customers and use this information to better understand context and anticipate customer needs”.
With the help of this type of tool, like the product NBA developed by Latinia exclusively for banking, financial institutions have the opportunity to prescribe relevant content and messages to their users, based on information extracted from past usage behavior, in this way anticipating what valuable products and services they will need in the future, offering them through the right channel and at the right time.
“Analyzing and interpreting customer behavior through their transactional events in real time is a key factor for banking growth, as it enables client retention and loyalty by being able to offer them better service, anticipating their needs, improving their experience and generating meaningful interactions,” explains Juliana Ortiz, Head of Customer Success at Latinia. “Our NBA product helps banks boost proactivity and develop strategies that benefit each individual customer, as well as the bank itself.”
Tools based on these Next-Best-Action models have the ability to make recommendations in real time, a feature that adds even more value to every bank-client interaction.
Next-Best-Action models and personalization
The benefits that Next-Best-Action models bring to banking converge on one of the most significant challenges facing today’s Customer Experience: personalization. Financial institutions that can offer personalized services and products to their clients, based on valuable data, will experience greater growth in the future, and in this sense, this technology is key.
The consulting firm McKinsey & Company, in their article Unlocking the value of personalization at scale for operators, make reference to the successful case of a European entity that, thanks to a model based on this technology, developed a specific campaign aimed at reversing its customer churn rate, addressing specific pain points such as bad experiences in customer service channels, price sensitivity, etc.
This analysis of the reasons for dropout allowed the company to create actionable campaigns at the micro-segment level, designing new offers and strategies in the right channels and at the right times to have an impact on its clients. The result was very satisfactory for the company, as it tripled its CVM (Customer Value Management) revenue over a two-year period, from 2% to 6%.
This case reflects the importance of the Next-Best-Action Model tool as a competitive advantage for banking, as it enables the collection, interpretation and activation of customer data that helps the implementation of new experiences and personalized services. “More and more organizations are incorporating these types of models into their businesses to increase the performance of their sales activities and reduce service costs through relevant and immediate actions,” explains Juliana Ortiz. “At Latinia, we have been betting for years on this technology that is bringing benefits to our clients in multiple areas thanks to the reduction of unnecessary message delivery, and an increase in product and service sales,” she concludes.
