Welcome to 2024!
I expect this to be a transformative year in martech. The Martech for 2024 The report we published last month ( video presentation ) covered many of the major trends underway, such as aggregation and stackability — especially at the data layer with cloud data warehouses, lakehouses and lakes.
The common theme of these trends is the breaking down of boundaries between different martech applications and platforms. The days of the silo are numbered. (I can take a hallelujah?)
It is a profound change. But there is an even more profound change.
Increasing complexity as a constant for two decades
For the 16 years I’ve been covering martech on this blog, Martech has strictly increased in complexity. And before you blame it on exploding the marketing technology landscape — now over 13,000 products! — recognize that all these martech tools were created in reaction to the increasing complexity of marketing itself.
When customers embraced search, marketers had to embrace SEO to convince both humans and search algorithms. When customers embraced mobile, marketers had to embrace apps, responsive web design, SMS, push notifications, WhatsApp, geofencing, etc. When customers embraced social media — Facebook, Twitter/X, LinkedIn, Instagram, TikTok — marketers had to embrace social content, social advertising, social customer service, social reputation management, influencer marketing, etc. When customers embraced online video, marketers had to embrace video content and video advertising, YouTube channels, Instagram reels, etc.
And that’s just the customer side of martech. New marketing approaches such as account-based marketing (ABM) and product-based growth (PLG), intent-based marketing and digital behavioral marketing, customer journey mapping, unified RevOps at the intersection of sales, marketing and customer success, ecosystem marketing, and so on.
All these inventions and innovations have contributed significantly to the marketing discipline. But they also massively expanded the diversity and scope of marketing. And all these new and different moving parts, all interacting with each other, have exponentially increased the complexity of marketing.
Martech systems – all the different software in the martech stack – have grown in complexity as a function of this inherent complexity in modern marketing. And even if you opted for a bundled suite of apps over a better mix of tools, you couldn’t escape the constant flood of new functions and features to serve your ever-expanding range of demands and responsibilities.
It may seem obvious As martech systems became more complex, so did the user interface with those systems.. Whether you were switching between an infinite series of browser tabs for different martech applications or searching for specific options within a mega marketing cloud, the cognitive load of just figuring out how to do a certain thing — out of all the things that were now possible — became significant. mental toll.
This has been a major factor in plummeting martech adoption rates.
As marketing became more complex, martech systems became more complex, and the UX within those systems became more complex. It was essentially a tautology:
Marketing Complexity = System Complexity = UX Complexity
Admittedly, there were differences at the margin. Martech products increasingly invested in better UX as a competitive advantage. However, even the best were swimming against the tide.
But it could be a new innovation REVERSAL UX complexity?
Productive AI user interfaces are changing the trend
Generative AI is the first major innovation in marketing technology history with the power to radically reduce UX complexity.
One of the first examples of this early last year was the launch of ChatSpot, an AI “chat UX” interface built for HubSpot built by Dharmesh Shah. (Disclosure: I work at HubSpot as VP of Platform Ecosystem.) Through a simple ChatGPT-like text prompt, you can ask ChatSpot to do something for you in HubSpot — create a contact, write a personalized email, run a report, etc. – and, voilahe would just do it for you.
You didn’t have to navigate any menus or buttons, dropdowns, check boxes. Dharmesh eloquently summed up this new way of software interaction as a shift from point-and-click to description-and-done.
Over the past nine months, ChatSpot has rapidly expanded its capabilities to support sales prospecting, SEO consulting, rich content creation, business analytics, deal optimization, and more. However, with all these powerful features enabled, the user interface for ChatSpot remained a simple text message.
Hundreds of other martech companies followed suit, adding natural language “chat UX” interfaces to their products. Many of these new AI-powered interfaces are still in their early stages, just scratching the surface of what will be possible next year. But as they make more features of the existing product more accessible through this user interface — and then add even more new features — they actually restrict their UX complexity.
It’s almost the opposite. The more features you add, the simpler the UX becomes?
The underlying complexity of what their products can do remains. In fact, as we’ll discuss in a minute, the complexity of these martech systems is actually likely to increase further. But martech UX on top of these systems has become much simpler. And it promises to become even simpler.
How does it get simpler than a natural language user interface? Allowing this user interface to serve results more than tasks.
The first generation of chat UX interfaces required you to be quite specific about each task you wanted to do. For example, “give me a sales report by country.” Younger generations – and iterate quickly – will be able to understand higher-level requests such as, “which countries are underperforming and how can we boost closing rates on their most important deals?”
This next generation of martech UX will be legal AI agents, capable of pursuing higher level goals. They’ll be able to plan multiple steps, adjust their plans based on feedback from the actions they take, leverage any data or API functions they have permission to access, and even know when to consult a “human in the loop” for clarifications or confirmations.
AI agents will serve as uber-aggregators in the martech stack, providing a centralized user experience through their chat UX, while also centralizing process functionality and using centralized data warehouses in the background to achieve their goals. Governance will be embedded or layered on top of these agents.
For marketers, the distinction between process, control, and experience will blend behind the interface with these agents.
Removal of a major constraint on system complexity
Ironically, while AI agents reduce the complexity of martech UX, they almost certainly will increase underlying martech system complexity.
In many ways, the limits of how much martech UX complexity humans could deal with had become a major constraint on how much additional martech system complexity could be effectively implemented. There was just so much data, so much functionality, and so many combinations of those elements chained together that even a seasoned marketer could keep track of in his head.
People have many wonderful qualities. Understanding exponential complexity is not one of them. But AI agents can excel at processing hundreds, thousands, even millions of data and combinations and sequences of operations.
As we decouple what martech systems can do from the martech UX we use to manage them, the underlying complexity of the system will be free to grow at a much faster rate. It will look more like the chart above than the one at the top of this post.
Will such exponential growth in martech system complexity be a good thing?
Honestly, it’s hard to predict. As noted, humans are not great at understanding exponential complexity. But I think the answer will be Yes. Why; Because customers and markets are complex. The ability for martech systems to adapt to this complexity with far more fluidity than we could have ever dreamed of before has the potential to dramatically improve marketing effectiveness and efficiency.
Customers are complex.
Therefore, markets are complex.
Therefore, marketing is complex.
Therefore, martech systems are complex.
But martech UX doesn’t have to be so complicated anymore.
I will reiterate: this will be a profound inflection point in martech.
