AI Next-Best-Action for Energy Customers
The initiative required more than an analytical model. It needed to connect heterogeneous information, commercial criteria and operational processes so recommendations could be consistently applied by business teams.
The solution combined customer data, AI and advanced analytics with structured decision workflows, connecting information preparation and modelling with operational consumption of prioritized recommendations.
Customer, consumption, digital-profile and behavioural information was consolidated to provide the data foundation used for customer-level decisioning.
Analytical and AI techniques were applied to prioritize products, services and next actions according to each customer context.
Recommendation logic incorporated strategic and profitability criteria, aligning prioritized actions with the retailer’s commercial objectives.
Outputs were designed for business users to prioritize customers, cases or actions and incorporate recommendations into existing commercial and campaign workflows, enabling actions to be launched and monitored more quickly.
The capability delivered a documented 60% reduction in the time required to launch new actions, supporting faster activation of customer actions and campaigns. It also provides more consistent customer-level decisioning across channels and strengthens the use of consumption and behavioural information in commercial interactions.
