At the very heart of business is marketing, and AI is now the default heartbeat of marketing. A barely noticeable, glacially slow but steady drip of information about AI marketing analytics usually doesn’t make the headlines.
This often highly specialized feed tends to be about marketing by marketers for marketers. It’s all about new business marketing practices and initiatives at the most fundamental and esoteric levels. It’s normally well under the C-level radar of business news, but it’s crucial for marketers.
The quality of this news and information is also managed differently. Unlike the usual frenzied news about every new hiccup or gimmick in AI business operations, information is geared to a professional audience, relentlessly specific and objective. Even the AI hype is minimal and highly focused. The focus is on how, why, and what roles AI has in different stages of marketing.
Many marketers could say with some justification that their profession is finally getting the attention it needs. This is a truly massive departure from traditional marketing on just about all bandwidths.
The new AI marketing approach is fully systemic and holistic. The incoming methodologies address everything from initial ideation and development to content creation to customer relations and rollout and types of market analytics.
AI marketing is a demanding new ballgame
When one of the great megaliths of US business, McKinsey & Company, spells out operational AI marketing deployment at the literal nuts and bolts level, you know it’s serious. McKinsey & Company defines these things in clear business hardhead terms for their own high-end core business clientele and they do it well.
This instructive level of scrupulous attention to keeping AI marketing ideas clear and comprehensible is essential. AI marketing needs highly efficient structuring from inception. Each phase and element of marketing operations must be clearly mapped out for marketing to do its own job.
There’s also a necessary element of hard sell in AI marketing. The reason for this obsessive need to thoroughly explain AI marketing is based on coalface realities. Marketers are quite rightly wary of simplistic outcomes. The pitfalls for marketers remain, and they’re diversifying.
The potential big black holes in marketing analytics are all still there, too. The irony is that AI’s vast range of operations have made the problems more visible.
Even the most basic tools like “from search to conversion” and attribution of results are showing significant glitches in reporting and big gaps in market tracking. These gaps (see link) are shown in basic measurements averaging 25% in surveyed respondents last year, and the accuracy of AI outputs was another big issue.
Translate that nominal 25% into what it really is, a total lack of essential marketing information, and you can see why marketers are so wary. “Cute numbers” are just not an option anymore. That particular number just shouldn’t exist, but it does.
AI vs old system technologies and methodologies
A less obvious and unavoidable problem is integrating diverse vintages of older and pre-AI business systems and getting them to work in AI environments. Integrating the various levels of antiquity of management systems and methods is also part of this mix. In old-style marketing, you marketed to a specific target audience in a limited market framework. You tried to expand your reach by targeted marketing. You did basic advertising. You used a limited set of media to sell.
Now, you have the new generation of hyper-influencers, the immovable TikTok Factor, data brokers, algorithmic marketing, international market variables, and additional requirements in sales, UX, and customer relations. All of these new or updated elements include their own newly defined marketing roles and needs in the AI environment.
Interestingly, a revealing “age gap” in SEO and AI search adoption and implementation has emerged in a recent survey. Indications are that these two absolute fundamentals are rather brutally defining progress or lack of progress in market performance. AI search in particular is redefining market positioning, with some businesses feeling “excluded” from AI search results. Others say their brand is “incorrectly described”.
Bear in mind that these respondents already had established market positions pre-AI marketing. They now apparently perceive themselves to be out of the loop or being pushed out of the loop. AI marketing effectively leaped out at them, and they weren’t ready for it. This is how the collateral damage of the new AI markets is measured.
A clear split between older market positions and the new reality is emerging very rapidly. This situation highlights another key issue. The more modernized businesses are pretty much OK with the new market environment and its tools, but they’re still adapting to AI marketing. Older marketing models are verifiably getting sidelined.
That means marketers will have to customize their operations to specific client requirements based entirely on this type of positioning. The clients need trustworthy guidance. Market repositioning is now becoming real-time market navigation.
Here there be not just dragons but market metrics with a mind of their own.