Jumping the AI Shark, But Missing the Boat

An overfocus on creative productivity apps by influencers andleadership alike continues to hold marketing back.

The marketing AI conversation is broken. Marketing leadership continues to overfocus on AI creative productivity apps while influencer conversations have failed to evolve.

But can you blame them?

Let’s be honest. Most marketers, marketing influencers, and trade press would prefer to talk about Super Bowl ads instead of AI impacts and real enterprise AI applications that drive dynamic lead-generation activities and customer experiences. And when it comes to AI, they often find themselves talking about ChatGPT or other generative AI apps to produce creative instead of integrating AI within their core marketing processes.

That’s a massive problem and one of the top reasons why most enterprises say they are actively experimenting with AI but have failed to embrace it within their core business processes. In essence, at least in the marketing suite, many have jumped the AI shark (e.g. ChatGPT), but most keep missing the boat.

For example, several companies are making active steps to support sales enablement with AI apps, including No Brainer Podcast guest Andre Yee’s Tiga.ai, Alta HQ’s Katie, Regie.ai, and Salesloft to just name a few. While none of these solutions are silver bullets for sales enablement, they greatly ease and hasten lead identification, prioritization, and initial content drafting, improving the performance of SDRs.

Note that none of these are called, “ChatGPT.”

Where’s the conversation on these apps? Isn’t supporting the sales team with the right content, including well-trained AI tools, part of the marketing team’s job?

Every aspect of the marketing lifecycle has dozens of AI tools that can help strengthen these processes. For example:

• Market Research tools like Crayon, Klue, Kompyte or SEM Rush for AI-powered competitive intelligence

• With Campaign Planning you have tools like Albert AI, Optmyzer and Trellis for autonomous media buying and optimization

• Customer Segmentation providers like Amperity, Qloo, and Segment.io use AI for real-time audience clustering

• Performance Analytics tools include Amplitude, Heap, Mixpanel and Pendo for predictive analytics

And, existing marketing software from CRMs, CDPs, and marketing automation systems are all rapidly incorporating AI to strengthen their processes. Why doesn’t the online conversation discuss these evolutions more frequently?

Influencers Keep Pumping ChatGPT

A quick survey of online marketing influencers, marketing conferences, and even marketing software vendors reveals a strong focus on using AI to assist or create AI content. Influencer conversations still revolve around ChatGPT and other LLM news, and prompting continues to be a dominant topic.

Unfortunately, given the current media environment and relatively small corps of marketing trade media, much of the AI conversation relies on marketing influencers online. It’s not that there aren’t good articles out there; for example, this article on CMSWire does a nice job of summarizing basic elements of strong data-fueled marketing personalization.

Influencers aren’t talking enterprise marketing AI adoption. Instead, because they rely on their content to drive leads and fuel their personal businesses, what we get is their business-specific view on how to adopt AI, which is for individual contributors. In a few instances agents, personalization recommendations, or even lead identification are referenced, but unfortunately, these offerings are half-baked with little substance or tangible outcomes.

It's hard for me to take most marketing AI influencers seriously. They scream that you're missing the boat and you’ll lose your job because you’re not adopting AI, then promote their ChatGPT training on prompting with the right context. Like it's 2023. Or perhaps they haven’t worked inside an enterprise for a significant spell.

Source: CMSWire

Talk to me about what you are doing with CDPs, how you are cleaning and unleashing your significant data stack to take advantage of Agentforce, or whether you are using AI to build lead funnels, sales enablement, and brand journeys. Instead, they just keep talking about content optimization.

Do you want to chat? OK, how are you using chatbots to democratize customer analytics across your enterprise? Copilot, GPT, or your preferred LLM to interface with PowerBI, Tableau, Databricks, or your other preferred BI tool of choice?

As a professional consultant who helps enterprises adopt AI, too, I find myself annoyed by much of the social media conversation on marketing AI because instead of taking the client’s mission first, we get the ChatGPT carpetbag. Maybe ChatGPT isn’t the right tool for the situation…

I get it; it's what influencers know. In the end, they really serve content creators and communicators. But marketing organizations are much more than creators.

The Creator Problem

Marketing executives are charged with generating leads, strengthening customer relationships and experiences, and building brands. Anyone who has worked in an enterprise marketing department knows that communications and content creation, while important for some, often take a backseat to demand generation, product marketing, advertising, and other more measurable forms of outreach.

That being said, in spite of their role, when it comes to AI, actual corporate marketing leaders would rather talk about generative creativity apps or the latest AI trends out of Silicon Valley. That’s instead of discussing the necessary work so that AI can dynamically reshape their entire sales enablement and customer experience.

The underlying reason should be obvious, most marketers are creatives in heart and in practice. Or it is a reflection of the online and media conversation about LLMs and the latest Silicon Valley news.

Thiscreativity app focus prevents marketing leaders from engaging in the hard foundational work to make AI work for their core mission: Compelling more people to buy their products and services. To do that, they need to move beyond ChatGPT productivity to build:

• Hyper-personalization at scale

• Deep pattern recognition in analytics

• Automated routine operations

• Predictive market insights

• Enhanced customer service automation

Building stronger data governance, unifying content libraries for AI consumption, forging better customer data platforms, documenting and measuring process efficiencies, and upskilling staff to manage AI systems seem really boring to most. I get it. As a recovering marketer (see what I did there?), I have learned more about data governance than I ever wanted to over the past few years.

It’s much easier to give ChatGPT and Firefly-enabled Adobe to your teams and say you have adopted AI, and it works partially, but not all the time.

But there are no shortcuts with AI. If marketing leaders want the benefits, they need to do the work. And, it is incumbent on marketing leaders to focus on the larger AI picture, get their data house in order, and use it to dramatically strengthen lead generation processes, brand building, customer experiences, and, most importantly, generate revenue.

/Rant