The patience for “spray-and-pray” emails is continuing to shrink, and sophisticated B2B buyers are increasingly expecting and demanding relevant and targeted messaging.

In EDRM’s Voice of the Customer research, 73% of the B2B customers surveyed agreed, “For brands or vendors to successfully engage me, they must have a deep understanding of my needs.”  The research also showed 66% said they “expect all of [their] interactions with brands or vendors to be personalized.”

Fortunately for B2B marketers, new advancements in real-time data analytics, AI and machine learning are making advanced segmentation and personalization possible, even across complex industries and buying groups.

60 per cent of enterprise B2B marketers are using a DAM but only 23 per cent are actively using a content marketing platform to support their editorial processes. Net, just over half even have a tool to managed their valuable content assets and a very small number have codified processes that happen in something more formal than an excel spreadsheet and email. 

Atomic content and personalisation is only possible if we, marketers, shift our mindsets, build some new skills and use the tools available to us to attend to the care and feeding of our content library.  A few months ago I wrote a very nerdy post about metadata and attributes. It sparked a lot of conversations about how hard it is to do this today. But trust me, it’s getting easier.  More tools – some CMPs and some re-imagined DAMs – are making it simpler to store and retrieve assets. The infusion of artificial intelligence (AI) into some of these systems will augment work done by marketers and creatives – taking the drudgery out of tagging and unlocking the value in our content – even making recommendations about which assets may work best for a given situation.