AI has the capacity to augment every phase of the customer journey, even after the customer purchases a product.
Organizations that use automation and machine learning harness data in new ways to deliver personalized value-added customer experiences in both the initial phases of awareness, consideration and evaluation and the later stages of commerce and conversion.
Today’s consumers expect convenience and utility from their connected devices. According to a recent study by Visa and PYMNTS.com, 41% of connected consumers own at least one connected device. More than 60% said they would like to pay for products more efficiently.
Adding commerce capabilities driven by AI as a feature to a consumer IoT device capitalizes on the customers’ desire to pay quickly on whatever channel they’re using.
IoT touchpoints throughout the customer journey must harness the power of machine learning to create experiences that are so seamless that they are taken for granted in their intelligent orchestration.
Integrate AI into commerce and post-commerce customer experience
Examining the latter phases of the customer journey, the following are seven examples of common AI applications that create IoT features.
- Biometric payment. A consumer connects his or her payment preference to the IoT device or virtual assistant to seamlessly make purchases — such as songs, groceries or in-app rewards — with biometric data, such as a simple fingerprint scan, palm scan or voice command recognition.
- Facial recognition. Using computer vision, an IoT device scans the user’s facial features and retinas to determine their unique identity to unlock device privacy features or profiles, usage clearance, or payment verification.
… Continue reading this list on TechTarget’s IoT Agenda, where this post originally appeared.