🤔What's needed to implement #personalization at scale for real-time customer interaction?
Personalization for real-time customer interaction at scale is a very difficult task to do #CX. It requires many components to work together at scale. Not only that, you will need a platform to support ALL below capabilities:
1️⃣ Decision Modeling with DMN Engine: The engine that allows you to execute decision models, potentially based on Decision Model and Notation. DMN will be used to model decisions around messages, contents, next best action (NBA), channels (inbound, outbound, paid etc.), offers, products and services and so on. Clarity across all stakeholders in retime customer interaction is a critical need, and failure starts right off the bat. Decision Model and Notation Conformance Level 3 will satisfy this requirement.
2️⃣ Composite #AI: The decision models define the structure of those decisions. Then, each decision unit should use customer analytics, customer data, and customer behavior to create #PredictiveAnalytics or #MachineaLearning model and #businessrules to implement the decision models. Hence, the decision models using Decision Model and Notation Conformance Level 3 are all executable, easy to understand with everyone, and there is no need to code them.
3️⃣ Advanced Orchestration: Many data points, such as product references, operational databases, customer information, etc., are required to execute the decisions. The source of data may also vary, with different types of databases, files, services, etc. Data integration, data flow, data enrichment, and validation, etc., are essentially means of connecting the outside world to decisions. Again, this is done in a visual way that all stakeholders can see and understand.
4️⃣ Distributed execution: Now, execution of the orchestration and decisions should be at scale, meaning a distributed network of computing nodes to execute the decisions and decide what products, services, and next actions are needed for a specific customer context based on what was predicted by predictive analytics and machine learning models as the intent of the customers with a confidence score. Also, the execution should be controlled using Adaptive Control (A/B testing, version scheduling, and other strategies)
5️⃣ Real-time events: Customers navigate through many channels, websites, SEO articles, paid ads, etc., and they provide new data points to the central decision hub. Real-time event processing allows the models, decisions, and outcomes to be adjusted, retrained, and recalculated automatically based on the new behavior or action you see from customers in real-time.
🚀With these five capabilities in your team, you can implement the personalization and real-time interaction solution that creates customer happiness and loyalty. #CMO #CDO #CTO #CCO
To learn more about our Open Decision Intelligence Platform visit https://lnkd.in/grE45k8a #decisionintelligence
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Published October 3rd, 2024 at 07:30 am
