Customer 360 has sat front and centre of digital personalisation initiatives for many years. But since customers and businesses have become increasingly digital and interconnected, just having a digital 360 profile of a customer (web logs, Adobe/GA analytics data, ID graphs, etc.) will not suffice for the hyper-personalisation that is required in todayʼs competitive landscape.
With digital-only 360, there are two other aspects of a customer that get ignored: 1) a businessʼ back-office information about the customers; and 2) social media and other public domain information about the customer. These two sets of data are each “Customer 360” in their own rights. Bringing all three information sets together produces a true customer 1080 profile that is required to power recommendations, next best actions, and other effective personalisation mechanisms.
Throughout most part of this digital era, a Customer 1080 profile of a customer has been the holy grail. Yet the predominant tech and operational challenges associated with maintaining a demanding data pipeline from multiple different sources, at varying schedules, and ensuring IDs can be mapped across disparate datasets, have kept customer 1080 from becoming reality.
At Syntasa, we have seen tremendous potential for a platform that is able to connect the entire value chain of Customer 1080, from creating data ingestion pipelines and applying machine learning algorithms, to disseminating the insights back to action and activating on some of the most popular marketing clouds such as Adobe. Our platform simplifies technology challenges by creating an entire “app”-like framework for creating and managing hairy data pipelines, applying super complex AI models to the data, and sending the actionable insights back to web and business applications, all with an inbuilt micro framework of DevOps and cost reporting. Loved by Data Scientists & Data Engineers (who can use their existing tools with Syntasaʼs platforms), by IT and Infra teams (who can simply plug in Syntasaʼs containerised solution within their existing cloud or on-prem data lakes environments), and by business users (who can configure and see their complex business strategies laid out in easy-to-navigate graphs).
If any of this resonates with you, email me (Apoorv Kashyap) and share your thoughts or experience with your own personalisation projects.