While digitization of consumer engagement has increased scalability of operations, it has led to the unintended consequence of dehumanizing customer engagement. This has limited the ability of organizations to develop personal relationships with their consumers, rendering every service a commodity, and brand loyalty an illusion.
The massive reach of social media has exacerbated this problem by amplifying the erosion of consumer trust in response to even slightly negative media coverage. To effectively counter this, organizations need a way to differentiate themselves from others in the way their consumers view them.
Organizations will need to respond to consumers’ needs for individual attention, while retaining the economies of scale in handling transactions. The challenge is to bring empathy into a digital world.
Discourse Analytics (DA) has built an AI-platform that focuses on humanizing digital interactions. The platform treats actions, choices and opinions as behavioral signals that are used to develop and maintain attitudinal profiles of individual consumers – profiles that reflect consumers’ likes and dislikes, fears and desires, as well as their preferences and turn-offs.
The neuro-cognitive map that serves as the “brain” of the DA platform (the DA Data Lake) can interpret a small set of behavioral signals to understand a consumer’s mindset, and to predict their response to specific stimuli. More importantly, it can prescribe the most effective engagement strategy to win the customer over – to gain their trust. Proactively discussing long-term risk profiles of alternatives is likely to get the attention of a risk-averse customer, while a reference to 24×7 access may be the trigger for a convenience oriented customer. In this world of message overload, one cannot stress enough the importance of getting the next best conversation™ right.
The DA platform has been trained using direct customer engagements and data on activities of over 3.7 million consumers across a spectrum of domains including political opinions, media consumptions, retail banking interactions, education and healthcare choices. The Data Lake can successfully interpret thousands of behavioral signals, and engage with hundreds of individual mindset profiles. The platform utilizes a patented algorithm to simulate human cognitive process to interpret observations, and to extrapolate profiles based on think-a-like clusters.
The DA Data Lake is a graph of behavioral signals, attitudes, profiles and interventions linked through stochastic edges representing cognitive triggers. The graph is continuously calibrated using a Bayesian inference engine as it encounters new signals. Thus, every engagement enhances the value of the knowledge contained in the Data Lake.
The outcomes of engagements are constantly tracked to validate the contents of the intervention library (the portfolio of engagement strategies). The DA platform is an organic system that continually learns new behavioral signals and adapts engagement strategies to actual consumer responses.