What is Next Best Action?
One of the key ways that businesses can use their customer data is to implement the concept of "Next Best Action " (NBA). NBA is a strategy that uses artificial intelligence (AI) models to analyze customer data and make personalized recommendations for how a business can engage with each individual customer in the most effective way.
Next Best Action refers to the process of determining the most appropriate action to take in a specific situation, within the context of a complex enterprise system. This process involves considering and balancing various factors, such as service policies, constraints, client circumstances, business procedures, risk indicators, decision rules, and intervention strategies. Domain experts should be involved in generating and fine-tuning the action rules that guide this process, with the goal of addressing the complexities of personalized next-best action-taking. The more complex the system, the more challenges posed in the NBA implementation, but in practice you can consider NBA commonly designed so as the next state depends on the current state and action. For a more technical approach on the challenges can be found in the recent article of Cao and Zhu (2022).
You can consider the NBA process as a feedback loop, between the customer and the business, that involves four key elements: actions, channels, events, and NBA orchestration. The actions element refers to the set of products and services that are available to be offered to the customer. The channels element refers to the various interaction channels that can be used to communicate with customers. The events element involves the analysis of context-sensitive information of customers, it’s the customer’s input to the feedback loop. Finally, NBA orchestration involves determining the best action to take for each customer, at the right moment, while using the appropriate channel. These elements work together to create a feedback loop that helps guide the NBA process and ensure that the most appropriate actions are taken to meet the needs of individual customers. Let’s see some examples. If you are interested in more implementations, find more examples in the latest article by Katsov (2022).
Our first example would be a retail business, which makes use of NBA to analyze customer data and identify which customers are most likely to make a purchase in the near future. The AI model can make recommendations based on available products; on previous purchases from similar customers, and suggest how the business can best engage with these customers. For example, by sending personalized email offers, or notifications about new products, or inform an internal individual that they need to call the customer.
Another example that businesses can use NBA is to identify customers who are at risk of churning or leaving the business for a competitor. By analyzing customer data, the AI model can identify which customers are most likely to churn and make recommendations for personalized customer support, o for actions that can be made to keep them engaged. Hence, by surfarcing these individuals, the NBA increases the efficiency of your special promotions.
But NBA can be used in many other industries as well. For example, a healthcare provider might use NBA to analyze patient data and make recommendations for personalized treatment plans or to identify patients who are at risk of developing certain health conditions. A financial institution might use NBA to analyze customer data and make personalized recommendations for financial products or services that are most relevant to each individual customer.
Why do you need Next Best Action?
NBA allows businesses to make more informed and targeted decisions about how to engage with customers, saves time and resources by automating the process of making personalized recommendations, and improves the customer experience by providing personalized and relevant engagement. This can increase customer satisfaction and loyalty.
How can intouch365 help you facilitate Next Best Action?
Intouch365 is a trusted advisor that helps organizations innovate and grow by bringing data and technology fully to life. An example of NBA implementation is Eneco, who partnered with intouch365, with the request to exceed customer expectations by using Next Best Actions to serve the right message, with the right tone, through the right channel. Intouch365 worked with Eneco to develop their Next Best Actions, through functional use cases, and user stories. To learn more about intouch365 and their cases visit the website www.intouch365.nl
Of course, implementing NBA does require some upfront investment in terms of time and resources. However, the benefits of improved customer engagement, time savings, and enhanced customer experience can make this investment well worth it for many businesses.
In conclusion, the use of AI-powered NBA can provide powerful insights and recommendations for businesses looking to engage with their customers more effectively. By analyzing customer data and making personalized recommendations, businesses can improve the customer experience, save time and resources, and make more informed decisions about how to engage with their customers.
References
Cao, L. and Zhu, C. (2022) “Personalized next-best action recommendation with multi-party Interaction Learning for automated decision-making,” PLOS ONE, 17(1). Available at: https://doi.org/10.1371/journal.pone.0263010.
Katsov, I. (2022) “Building next best action engines for B2C and B2B use cases,” Proceedings of the 31st ACM International Conference on Information & Knowledge Management [Preprint]. Available at: https://doi.org/10.1145/3511808.3557511.
