The Tech Vendor Explosion

When I started in operations in the early 2000s, the tech stack conversation was straightforward. You had a CRM, maybe an email platform, and a phone system. That was it. Today, a mid-market company’s tech stack can include 50 to 100 or more tools across departments.

How Did We Get Here? The Numbers Tell the Story

In 2011, Scott Brinker published his first MarTech landscape graphic showing approximately 150 marketing technology tools. By 2025, that number exceeded 15,384. That’s roughly 100x growth in 14 years. And that’s just the marketing technology category. Add in sales engagement tools, revenue intelligence platforms, customer success solutions, billing systems, HR tools, project management software, and BI platforms. The real number is staggering.

Every category that used to have three or four viable players now has 30 or 40. CRM alone isn’t just Salesforce and HubSpot anymore. Generative AI has accelerated this explosion — since 2023, AI-powered tools were responsible for 73 percent of the increase in available MarTech solutions.

What Does the Average Tech Stack Look Like Today?

Productiv’s 2024 State of SaaS report found that the average mid-market company (200 to 500 employees) uses between 200 and 300 SaaS applications. Zylo’s research puts the average annual SaaS spend at roughly $4,800 per employee. For a 200-person company, that is nearly $1 million per year in software costs.

But the real problem is not the number of tools. It is the percentage of those tools that deliver value. Zylo found that 51 percent of SaaS licenses go unused or underused. That means roughly half of that million dollars is shelfware: software the company pays for but does not use to its potential.

These are not small numbers. And they compound over time as contracts auto-renew, new tools get added to solve problems the existing tools could handle, and nobody audits what is already in the stack.

Why Does Tech Stack Sprawl Cost Companies Money?

• Analysis paralysis hits early. Companies spend months evaluating tools and never make a decision. I have seen teams run six-month evaluation processes for a tool that takes two weeks to implement. The cost of not deciding is often higher than the cost of picking the wrong tool.
• Shelfware is expensive and widespread. (Related: Your Budget Deserves Better Than Excel.) The average enterprise uses only 40 to 60 percent of the features in their existing tools. You’re paying for capability you never access.
• Integration nightmares compound with every new tool. Your CRM needs to talk to your marketing platform which needs to connect to your billing system. Each connection is a potential point of failure. I have worked with companies that had 15 integrations where 4 were broken and nobody knew. Data was flowing into the CRM from sources that had been decommissioned months earlier. The reports looked complete, but the underlying data was stale.
• Vendor fatigue is a real tax on your operations team. Managing 15 or 20 vendor relationships means 15 or 20 renewal cycles, support escalations, and contract terms to negotiate.

How AI Is Changing the Vendor Landscape

The vendor explosion is entering a new phase. Every existing tool is adding AI features. Every quarter brings new AI-native alternatives that claim to replace entire categories. This creates a new set of decisions for buyers.

Do you adopt the AI features in your existing tools, or do you switch to an AI-native platform? The answer depends on how deep the AI integration is. A bolted-on AI feature that summarizes call notes is different from an AI-native platform that was built from the ground up around machine learning models. The first is a feature. The second is a different approach to the problem.

For most companies, the practical advice is this: start by using the AI capabilities in the tools you already pay for. Most teams have not scratched the surface of what their current platforms can do with AI. Salesforce Einstein, HubSpot’s AI tools, Gong’s conversation intelligence: these are included in your existing licenses. Use them before buying something new.

The exception is when an AI-native tool solves a problem your current stack cannot address at all. Predictive pipeline scoring, automated data enrichment, and AI-driven forecasting are examples where purpose-built tools may outperform bolted-on features. But evaluate them the same way you would any other tool: does it integrate, will the team adopt it, and does it solve a problem that is costing us real money?

The Necessary Evil of Scaling

Upgrading and scaling your tech stack isn’t optional. What works at 20 employees doesn’t work at 200. The real problem is that most companies scale reactively. Something breaks, so you buy a tool. Fast forward three years: you have 40 tools, half overlap, a quarter nobody uses, and your integration layer is held together by Zapier rules that one person understands.

A Framework for Evaluating Your Tech Stack

Before buying anything new, audit what you have. For every tool in your stack, answer four questions:

Who uses it? Not who has a license. Who logs in regularly and relies on it for their work. If the answer is “two people in marketing,” you may be paying for an enterprise license that serves a team of two.

What does it connect to? A tool that operates in isolation is a data silo. If it does not feed data into or receive data from your other systems, its value is limited to whatever happens inside its own walls.

What would break if you removed it? This separates the critical infrastructure from the nice-to-have. If removing a tool would stop deals from being routed, reports from being generated, or invoices from being sent, it is core infrastructure. If nobody would notice for a month, it is a candidate for evaluation.

Are you using more than 50 percent of its capability? If not, the question is whether to invest in adoption and training, or whether the tool is genuinely a poor fit. Sometimes the tool is right but the implementation was rushed. Sometimes the tool was the wrong choice from the start.

What to Look for When You Do Buy

When a new tool is genuinely needed, evaluate it on five criteria:

Integration capability. Does it connect natively to your core systems? An API is not enough. Native integrations with pre-built connectors reduce implementation time and maintenance burden.

Adoption complexity. How long will it take your team to use it effectively? A tool that requires six weeks of training has a different total cost than one the team can start using in a day.

Total cost of ownership. License fees are the beginning, not the end. Factor in implementation, integration, training, and the ongoing maintenance time from your operations team.

Vendor stability. Is this company going to exist in two years? In the current market, vendor consolidation is accelerating. A tool from a startup that gets acquired may change pricing, features, or direction overnight.

Data portability. Can you get your data out if you need to switch? If the answer is no, you are not buying a tool. You are buying a dependency.

How to Think About It Differently

• Start with the process, not the tool. Define what the workflow should look like before you start shopping.
• Audit what you already have before buying anything new. I recently worked with a client who had Asana and Zapier. (Read the full story on our Case Studies page.) They thought they needed a completely new automation platform. Instead, we built 23 workflow stages and 17 automation rules using what they already owned. No new tools.
• Think in systems, not point solutions. Every tool you add needs to connect to the rest of your stack.
• Plan for change. Your stack will evolve. Document what you have. Document why you chose it. Document how it connects.
• Get outside perspective. Internal teams are too close to their own pain points to see the full picture.

The Vendor Explosion Isn’t Slowing Down

The companies that win aren’t the ones with the most tools. They’re the ones whose tools work together seamlessly, whose processes are documented and repeatable, and whose teams know how to extract value from what they already have.

You don’t need to rip everything out and start over. Most companies benefit from starting with a focused audit of one area. From there, you can scale improvements as budget and priorities allow.