“Think Liquid” Could Be the Key to Success in Geoff Livingston’s Book, Now Is Gone
A marketing communications director last year had done everything right with AI, that is if you follow the daily swirling memes on Linkedin. Her team had adopted AI tools across the board: content generation, social scheduling, performance analytics, and even creative concepting. Productivity was up, headcount held steady, and her CMO was pleased.
Six months later, the pipeline numbers were flat, engagement was declining, and she couldn’t explain why. The tools were working, but what she had built was a faster version of the same machine.
The Renovation Trap:
There’s a pattern I keep seeing across marketing organizations right now, and it’s the same one I watched play out during the social media era. Teams treat a structural change caused by a technology shift as a tool upgrade. They add capabilities without questioning the assumptions underneath them, renovate workflows, and call it a transformation.
During the social media boom of the late 2000s, most organizations responded by hiring a community manager, opening a Facebook page, and measuring followers and likes. The platforms were new, but the thinking wasn’t. The teams that actually thrived in that era asked whether their fundamental assumptions about audiences, channels, and brand relationships were still accurate. They used social media to foster niche customer and advocacy communities that were brand loyal, in turn creating word-of-mouth engines.
AI is presenting marketing leaders with the same choice, and most are making the same mistake.exists. It will analyze more data more cheaply. It will automate more of the repetitive work that consumes junior staff. It will produce more content faster, but at a lower level of machine-generated quality, which creates the slop problem.
What it will not do, on its own, is tell you whether the underlying strategy is sound. Oh, it will offer an opinion, but in fact, that will be laden with tropes based on commonly accepted best practices from yesteryear, not new ones that meet the moment. To really understand the strategy, you need to understand your customer journey in totality.
What “Think Liquid” Means in Practice:
The Think Liquid framework outlined in my new book, Now Is Gone, encourages marketers and communicators to use AI to expose the full customer journey as it actually exists, not as it was designed or assumed to be. This helps marketers move toward their actual destination by finding the path of least resistance to customer engagement and loyalty, not by forcing their original strategy.
AI gives us better tools than we’ve ever had to understand that journey in granular detail, to identify where customers find us, what causes them to react, how acquisition breaks down, where retention erodes, and where the assumptions baked into the current strategy are simply wrong. But most teams aren’t using AI for that.
They’re using it to produce more content for channels that may or may not be working, to scale campaigns built on strategies that haven’t been interrogated in years, and to move faster in directions that haven’t been reexamined. The current AI approach assumes its underlying strategy is right.
Every marketing team has sacred campaign tactics it believes in: The email cadence, the social format that won an award three years ago, the partnership that has history behind it. These are the last things to get cut when budgets tighten, and they’re often the first things that should be examined.
Think Liquid doesn’t mean being reactive or abandoning discipline. In concrete terms, liquid thinking looks like being willing to cut a tactic that has history and comfort behind it because the honest assessment says it’s not converting. Ask whether your current channel mix reflects where your audience actually is, or if it was forged when the strategy was last updated.
Using AI’s analytical capabilities to first surface the real customer journey, and continue to monitor ongoing evolutions, is the strategic approach. To get there, we need to elevate our thinking beyond the campaigns.
What This Requires of Marketing Leaders:
The mindset shift isn’t complicated to describe, but it’s hard to execute. It requires accepting that the strategies and instincts that made you effective as a marketer were built in conditions that no longer fully exist.
The hardest part of this work is political. Looking at the journey and examining fault lines takes a certain amount of willingness to be vulnerable. For many work cultures and leaders in particular, this presents a challenge that can only be overcome with courage.
AI provides an opportunity and a cover. Teams can use it to scale existing sacred tactics faster, which delays the reckoning (or hastens it with slop and quicker failures). Or they can use its analytical depth to surface an honest picture of what’s actually working, which accelerates it. In the AI era, what once worked may no longer succeed… And that’s OK.
The teams I’ve seen navigate this well share two characteristics: 1) Their leadership is willing to treat the current customer data as more authoritative than institutional memory. 2) They are not punitive, but rather innovative and curious. Those are cultural decisions.
The teams that thrived in social media won because they were willing to let the old model of audience relationship die and build something more accurate in its place. We need that same courage right now. To succeed in the AI era, marketing, communications, and PR must become willing to bring an honest customer-journey-centric inventory to analyze current strategies. When we do that, we can better decide what to scale and what to let go.
That leadership growth is the real work of the AI era.
Reprinted with permission of Capitol Communicator, a sister-company of CommPRO.
