At the heart of business is marketing, and AI is now the default heartbeat of marketing. or barely noticeable, slow but steady stream of information about AI marketing analytics doesn’t usually make headlines.
This often highly specialized feed tends to be about marketing by marketers to marketers. It’s about new business marketing practices and initiatives at the most basic and esoteric levels. It’s normally 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 raging news about every new hiccup or trick in AI business operations, the information is tailored to a professional audience, relentlessly specific and objective. Even AI noise is minimal and very focused. The focus is on how, why and what roles AI has in different stages of marketing.
Many marketers can say with some justification that their profession is finally getting the attention it needs. This is a truly massive departure from traditional marketing across almost all bandwidths.
The new AI marketing approach is completely systematic and holistic. Introductory methodologies address everything from initial ideation and development to content creation to customer relationships and scope and types of market analytics.
AI marketing is a demanding new ball game
When one of the largest megaliths of American business, McKinsey & Company, describes the operational deployment of marketing AI at the literal nuts and bolts level, you know it’s serious. McKinsey & Company defines these things in clear business terms for their core business clientele, and they do it well.
This guiding level of scrupulous attention to keeping AI marketing ideas clear and understandable is essential. AI marketing needs very efficient structuring from the start. Each phase and element of marketing operations must be clearly defined in order for marketing to do its job.
There is also a necessary element of hard selling in AI marketing. The reason for this obsessive need to thoroughly explain AI marketing is based on the realities of coal. Marketers are rightly wary of simple results. The pitfalls for traders remain and they are diversifying.
The big potential black holes in marketing analytics are all still out there. The irony is that the wide range of AI operations have made the problems more apparent.
Even the most basic tools like search-to-conversion and result attribution are showing significant flaws in reporting and large gaps in market tracking. These gaps (see link) show up in baseline measurements by an average of 25% of respondents last year, and the accuracy of AI results 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” just aren’t an option anymore. This particular number simply shouldn’t exist, but it does.
AI versus legacy system technologies and methodologies
A less obvious and unavoidable problem is integrating different vintages of older and pre-AI business systems and putting them to work in AI environments. The integration of different 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 frame. You tried to expand your reach through targeted marketing. You’ve done basic advertising. You have used a limited set of media to sell.
Now, you have the new generation of hyper-influencers, the TikTok Real Factor, data brokers, algorithmic marketing, international market variables and additional demands on sales, UX and customer relations. All of these new or updated elements include their newly defined marketing roles and needs in the AI environment.
interesting, A revealing “age gap” in the adoption and implementation of SEO and AI research has emerged in a recent survey. Indications are that these two absolute fundamentals are brutally determining progress or lack of progress in market performance. AI search in particular is redefining market positioning, with some businesses feeling “left out” of AI search results. Others say their brand is “misdescribed.”
Keep in mind that these respondents had already established market positions prior to AI marketing. They now apparently perceive themselves to be out of the loop or being pushed out of the loop. Marketing AI was effectively thrown at them and they weren’t ready for it. This is how the collateral damage of new AI markets is measured.
A clear divide between older market positions and the new reality is emerging very quickly. This situation highlights another key issue. More modern businesses are more or less okay with the new market environment and its tools, but they are still adapting to AI marketing. Old marketing models are being verifiably overturned.
This means that marketers will have to customize their operations to specific customer requirements based entirely on this type of positioning. Customers need reliable guidance. Market repositioning is now becoming real-time market navigation.
There are not only dragons here, but market metrics with a mind of their own.
