Italian Marxist philosopher Antonio Gramsci used this phrase about a century ago in his work ‘Prison Notebooks’ to reflect upon societal and political instability and transformation, where existing structures and ideas were losing their validity, but new ones had not yet emerged to replace them.
This could very well define the state of martech today. The old structures (legacy systems) are failing, but new ones have yet to fully emerge.
But, before we look at what’s failing, let’s reminisce about what got us here – the martech evolution we’ve witnessed. The early days of martech brought in a range of emotions for us all – excitement for marketers, confusion for technologists, skepticism by business leaders and frustration for data integration teams.
One would recall back in those days …
- when ‘personalization’ meant adding a {FirstName} placeholder in your email template and hoping it didn’t show up as “Dear {FirstName}” when it landed in the inbox.
- when you had those unexpected surprises—like discovering your website didn’t work on half of all browsers.
- and remember when we felt so cool using an autoresponder that replied to every inquiry with, “Thank you for your email. We will respond within 48 business hours”?
- and not to forget our old analytics tools. Figuring out how to show ROI, coming up with our own concocted calculations.
Yes, it has been one big journey.
From its early days to now, martech has evolved greatly, ushering us into the Third Age of Martech. Below diagram illustrates the shift across the ages.
We’re in the midst of a transformative shift in needs and expectations, sparking the emergence of new tools. As budget season approaches, it’s the perfect time to critically examine our martech stack. We need to ensure every dollar spent is justified and identify any gaps that AI tools can potentially fill. AI is becoming more and more integral in our lives and soon in our martch stack. Here are top things to consider.
Are we faking it, perfectly?
Much like the “sad generation of happy photos,” where people curate perfect lives on social media while grappling with real-life challenges, the narrative around AI in martech can sometimes be misleading. The success stories of AI gloss over the complexities and challenges of implementing AI solutions.
You’d have such stories. You leverage AI-powered recommendations that promises personalized hyper-relevant content to your website visitors but find it more like a magical black box that you don’t understand and can’t control. You either lack the expertise to interpret the AI’s recommendations or find that integrating the ai system with your existing infrastructure is more complex and time-consuming than anticipated.
Let’s take another popular AI use case – Predictive analytics, often heralded as a game-changer for driving business insights and decision-making. But here’s the challenge: we’re dealing with flawed, fragmented, and inconsistent data. How can we expect a predictive engine to run smoothly on such a shaky foundation?
While AI in martech is often portrayed as a silver bullet, let’s not put the cart before the horse. When planning budgets, balance hype with practicality; address the foundational challenges and strategize AI integration with current martech stack.
Are we drowning in a “sea of sameness”?
Imagine walking into a bar and every drink tastes like watered down gin and tonic. That’s exactly how our martech landscape feels today. The number of martech tools has exploded from 150 in 2011 to over 8000 today, creating a landscape filled with overwhelming similarity. It’s like a festival of features with buzzword overload (read: ai, seamless integration, customization, omnichannel). This ‘sea of sameness’ has made it hard to determine which tools actually bring something new to the table.
And here’s a reality check: all these efforts to make tools and features stand out and remain unique often fall short. For example, while customizable platforms promise to enhance user satisfaction, the reality of implementing these customizations is painfully difficult and often disappoints.
Where’s the ROI? And who’s weighing the risks?
While there is enthusiasm and eagerness from management, CIOs and CFOs struggle to find the ROI and how to manage the accompanying risks. The truth is out there: while many companies have adopted/ made plans to adopt AI, very few companies have been able to truly showcase its value. This echoes the earlier struggles of marketers who fought to prove their impact on sales—now, the challenge has escalated to attributing value to AI investments. It’s a complex puzzle that many are still trying to solve.
AI isn’t just a costly line item; it’s a complex investment filled with challenges, especially data privacy. The expenses go way beyond buying new tools—they include data security, compliance, and integration into existing systems. Analysts predict a promising future for AI, but caution that its widespread adoption will remain nascent for the next few years due to the monumental task of standardizing data at the enterprise level.
A few days ago, AI pioneers Geoffrey Hinton, often hailed as the ‘godfather of AI’ and John Hopfield were awarded the Nobel Prize in Physics. Hinton, who foresaw the revolutionary potential of technology, also warned: ‘We have to worry about a number of possible bad consequences, particularly the threat of these things getting out of control.’ While the existential threat of AI is a profound concern, back in the office, the immediate implications are equally pressing. Poor decisions on AI tool implementations in martech can lead to significant disruptions and inefficiencies, underscoring the critical need for careful and informed choices. Choosing an easier or faster solution now may lead to more work and complexity later.
The long-term potential is undeniable, but the road to get there is paved with significant hurdles. We must proceed with cautious optimism.
Closing with a piece of folk wisdom:
A bird doesn’t land on a branch trusting that the branch won’t break, but rather trusting in its ability to fly away.
When planning budgets for the next year and strategizing your MarTech stack, not all decisions will be perfect. Your success hinges on your agility and capacity to adapt and pivot rather than on the perceived promises of new technologies.
Regular attendee and contributor to the Little Grey cells events, Sita Kaluri is Director Marketing Optimisation (Fitch Group Inc).
