Not just a buzzword, data activation refers to a brand’s ability to not only collect, store, categorize, and analyze customer data, but also to be able to act upon this data in real-time, in order to take the smartest possible marketing decisions and influence users with custom tailored messages, based on all available data.
After a long history of optimizations based on fragmented, non-substantive visitor data plagued the web, organizations grew tired of missed monetization opportunities. Thus, an era of traditional hunch-based marketing transformed into an obsession with data-driven approaches, transforming consumer and business facing industries alike.
But with any new trend marketers aim to adopt, what’s great into theory doesn’t always translate into desired outcomes. Instead, brands limited by data trapped in siloed legacy systems practiced ineffective “data activation” and were met watered down results. Because when there is no single source of truth, not all data that can be activated should be.
Without a cohesive dataset based on all available customer information, how can a brand achieve actual precision? In order for real meaning to be derived from data, data must first be accurate and fresh. This can only occur if the right technology is able to ingest data from multiple sources, allowing for it to flow freely as customers interact with a brand, and rendered up-to-date upon “actioning” on behalf of the marketer. For there’s no point in targeting Jason with a display ad if already converted from a triggered email.
To break it down: Siloed data = wasted media spend + frustrated customers.
And this is just one example of data activation gone wrong.
For truly orchestrated and contextual experiences, a unified platform for engagement is the only answer to true data activation.
Once centralized, data can be supercharged and activated in the following ways to more personalized experiences:
Behavioral Messaging – Powered by behavioral data, deliver highly targeted and engaging onsite and in-app messages with precision.
Recommendations – Make trustworthy content and product recommendations onsite, in-app or via email backed by data in order to realize your highest ROI.
Segmentation – Identify and target high-value customers across channels based on specific events, interactions, demographic data and more.
Testing & Optimization – Feed your A/B tests with data from all customer channels and run highly targeted experiments based on your most valuable KPIs.
