Why another piece of marketing technology rarely fixes the underlying problem.
Marketing has never had more technology available to it than it does today. CRMs, marketing automation platforms, analytics tools, ABM platforms, sales enablement systems, content tools, intent data, customer data platforms, AI applications, personalization engines, and an endless collection of specialized software promise to make marketing faster, smarter, more efficient, and more measurable.
A lot of them are genuinely useful. Some have fundamentally changed how marketing teams work, but I’ve also watched companies spend a lot of money buying capabilities they never actually built.
The pattern is usually familiar. The company identifies a problem. Sales and Marketing aren’t aligned, so it buys a better CRM. Lead follow-up is inconsistent, so it invests in automation. Account-based marketing becomes a priority, so the company purchases an ABM platform. Reporting isn’t good enough, so it adds another analytics tool. Content production is too slow, so the team introduces AI.
There’s an understandable logic behind each decision. Technology can solve real problems, and the right tool can make a capable team dramatically better at what it already does. The trouble starts when buying the technology is mistaken for solving the problem.
I’ve seen sophisticated CRM systems filled with incomplete data because nobody established clear rules for how the organization should use them. Marketing automation platforms sit underutilized because the company never developed a meaningful nurture strategy. Expensive analytic tools produce dashboards nobody trusts because the underlying data is inconsistent. ABM platforms get purchased before Sales and Marketing have even agreed on which accounts they want to target.
The technology works. The organization around it doesn’t. That distinction matters because software is usually designed to execute or improve a process. It rarely creates the process for you. A CRM can help manage a sales pipeline, but it can’t decide what your sales process should be. Marketing automation can deliver the right message at the right time, but it can’t tell you what that message should say or whether the audience actually cares. An analytics platform can make data easier to see, but it can’t decide which metrics matter to the business.
The tool can support the capability. It isn’t the capability.
I think this confusion happens partly because technology purchases are tangible. A strategic or operational problem can be messy and difficult to define. Buying a platform feels like action. There’s a demo, a contract, an implementation plan, training, and eventually a new login sitting on everyone’s desktop. Leadership can point to something concrete and say, “We fixed it.”
Building capability is slower and less visible. It requires decisions about strategy, ownership, processes, roles, data, training, measurement, and how the work fits into everything else the organization is already doing. People have to change habits. Teams may need to work together differently. Someone needs to be accountable for the system after the consultants or implementation team leave.
That part is harder to put in a software proposal. I’ve seen this most clearly with CRM and marketing automation systems. Companies sometimes believe implementing the technology will create better alignment between Marketing and Sales. However, if the two teams haven’t agreed on what constitutes a qualified lead, when Sales should become involved, how quickly someone should follow up, what happens to prospects who aren’t ready to buy, and who owns each stage of the process, the platform simply digitizes the disagreement. Now you have a very sophisticated way to be misaligned.
The same thing is happening with AI. I use AI regularly, and I think its impact on marketing will continue to grow. It can accelerate research, analysis, content development, ideation, personalization, data work, and countless other tasks. Yet, AI is also creating another wave of companies confusing access to a tool with possession of a capability.
Giving everyone an AI account doesn’t suddenly make the organization better at marketing. If the positioning is weak, AI can produce weak messaging much faster. If the company doesn’t understand its customers, AI can generate enormous amounts of content built on shallow assumptions. If there’s no clear content strategy, the team can now produce more material nobody particularly needs. If nobody knows which metrics matter, AI can help analyze the wrong ones more efficiently.
Powerful tools amplify whatever system they're placed inside. That can be incredibly valuable when the system is good. A strong marketer with clear strategy, customer insight, good data, and sound judgment can use AI to accomplish far more than was possible a few years ago. A disciplined sales organization can get tremendous value from a well-configured CRM. A mature demand generation team can use automation to manage complexity that would be impossible manually.
Amplification works in both directions. Technology can also help a poorly designed process fail faster and at greater scale.
This is why I think companies should spend more time defining the capability they want before shopping for the technology that supports it.
If you want better account-based marketing, what does that actually mean for your business? Which accounts are you targeting? How will Marketing and Sales coordinate? What kind of content and outreach will those accounts receive? How will you identify engagement? What will success look like? Once those questions are answered, the technology requirements become much clearer.
If you want better analytics, start by deciding what decisions the data needs to help you make. If you want marketing automation, understand the customer journey and the communications you want to automate. If you want AI to improve productivity, identify where people are spending time today and where AI can genuinely improve the work without sacrificing judgment or quality.
Then choose the tool. This approach may also lead to an inconvenient conclusion: sometimes you don’t need another platform at all.
I've walked into companies with surprisingly sophisticated technology stacks that were using only a fraction of what they already owned. One system had been purchased to solve one problem, another added later to solve something adjacent, and a third brought in because a new leader preferred it. Eventually the organization had overlapping tools, duplicate data, multiple vendors, and employees who weren't entirely sure which system was supposed to be the source of truth.
Adding another piece of software would have made the situation worse.
Sometimes the better investment is improving the process, cleaning the data, training the team, integrating existing systems, or simply using more of the functionality you're already paying for. Those solutions aren't as exciting as buying something new, but they can create far more value.
This is also why ownership matters so much. Every important technology needs someone who is responsible for what happens after implementation. Not merely someone who administers the platform, but someone who understands why the organization has it, how it supports the strategy, whether people are using it, and whether it's producing enough value to justify the investment.
Without that ownership, tools tend to become expensive digital furniture. They're there. Everyone knows the company paid for them. Nobody is entirely sure what they're accomplishing.
I’m not skeptical of marketing technology. Quite the opposite. Some of the biggest improvements I’ve seen in marketing performance came from combining good people and processes with technology that allowed them to work at a level they couldn’t reach before.
The sequence matters.
Understand the problem. Design the process. Establish ownership. Build the skills. Then determine what technology can make the system better.
Buying the tool is the easy part. Building the capability is where the real work begins.
