Augmenting Customer Insight with AI and Big Data

An example of actionable customer insight would be information about a customer’s propensity to respond to ‘call to action’. Ideally we’d like to access this information, in real time and across any given channel.  Actionable customer insight can be automatically derived using algorithms that apply rules and logic. These algorithms based on simple business rules on limited data sets, but accuracy improves with increased complexity and bigger data sets. Machine learning can bee applied using AI methods to enable ongoing automatic optimisation. Next best actions are determined through algorithms that rely on data-models that are built from behaviours, patterns and trends. Data is sourced across multiple channels and retained in data lakes and/or big-data repositories, then processed and re-organised across data-marts that are tailored towards particular applications.