Nearing Magic

AI personalization is apparently pure magic just as long as brands can wrangle data that’s actually clean and well-organized, which notwithstanding all the tooling still not much easier than the cat-herding it had forever been. There is a secret sauce for these wizard-level customer experiences. It involves endless hours spent crafting robust taxonomies and obsessively correcting product feeds, except now marketers are told AI will eagerly automagically fix the same problems everyone ignored for years. So, with the right mix of structured and unstructured data, a brand just needs to cross its fingers and hope their holiday sales spikes will drive the promised revenues, sales attributions will work perfectly and clients will love and blindly trust the numbers they see.

Of course, setting up structured data platforms used to be a marathon of manual labor and sadly, even AI can only do so much if fed garbage data, though marketers are encouraged to leave tricky bits to algorithms because taxonomy management is “no one’s favorite task” anyway. Feeds for shopping ads and product carousels get the royal AI treatment, dynamically filling in all those pesky missing details, and optimizing everything until “campaign performance” reaches peak marketing nirvana never mind what measurement data points get lost in translation or mangled along the way.

And as for AI tools, there’s simply no way to escape them, because every platform from Google Ads to Meta Business Manager is now bursting with so-called “embedded AI” features, turnkey solutions promising results as long as brands dutifully ignore limits and only seek “practical” use cases. Should you dare to want more, bespoke “Applied AI” awaits (for those who build yet another centralized data fortress), with case studies boasting revenue jumps that make marketers’ hearts flutter, a whole 72% more from abandoned baskets, because cold emails finally learned how to sound personal. In the end, personalization success is almost guaranteed, provided brands cherish their data foundations and keep believing the dream that AI will fix everything humans have been sidestepping for years. The more things change, the more they remain the same.