We have found that AI is a common tool used by businesses in the digital TV or over-the-top streaming media space. With high acquisition costs and escalating content costs, operators are looking for a rich content platform that drives user engagement and value with data. By providing richer, data-backed insights into audience preferences and behaviours, AI has provided the opportunity for marketers in this space to cut through the noise of local regional content and create customised offerings for different customer segments through storytelling.
We have been able to apply these learnings to other clients, who are now using large-scale AI and data analytics to predict and understand customer behaviour and create more meaningful engagement along their customer journey.
For example, a client of ours in the quick service restaurant (QSR) segment was seeking a solution to trigger repeat customer orders via their app. The challenge was not to understand the purchasing behaviour of their loyal customers but to identify the trigger for their infrequent, dormant buyers.
We assisted the client by creating a specific micro-targeting model that translated data into more granular insights that informed targeted customer messaging. The model matched the behaviour and needs of customers at the right time and on the right channel.
In situations like these, we are using AI to process data from corporate levels at speed to use it for micro-finance at retail stores. The data is coming from different parts of the business, and the insights are executed at the customer touch point.