Automate next best offer recommendation and prioritization using proprietary packaged machine learned model based on historic and contextual usage behavior of customers. Optimize offers served on customer touch points based on recent customer interactions and marketing objectives of enterprises with self-learning models.
Configure touch points to be integrated across traditional channels like customer care and digital channels like mobile and email for serving offers. Make use of add-on modules to integrate new age digital channels like social media, Chabot and voice platforms like Google Assistant.
Make use of GUI guided inbound marketing workflow automation from touch point integration to planning, execution and measurement. Switch between heuristic (rule-based) and machine learned decision-making framework for next best offer recommendation within the workflow with ease.
Get an aggregated view of inbound marketing program performance across touch points including offer take up rate and revenue generated with real-time dashboards. Make use of stand-alone dashboards to capture day-wise and aggregated performance of customer care teams or agents in terms of converting customer inquiries to offer uptake.