Taking a realistic approach to revtech and attribution

Most organizations are focused on adding more tools and capabilities to their revenue technology ecosystems, but the real challenge isn't about having the most sophisticated stack — it's about finding the right balance between capability and complexity for your specific stage of growth.

The past decade of building, breaking, and optimizing revenue tech stacks across multiple companies reveals clear patterns. From early-stage startups to growth-stage unicorns like Ramp, the right approach to RevTech can accelerate growth — while the wrong approach can create a million-dollar mess that actively works against revenue teams.

Here's what experience has revealed about finding the balance that actually drives results.

The three pillars that make or break your revtech stack

Every successful revenue operation stands on three foundational systems, but the relationship between these systems is frequently misunderstood.

The complexity isn't just about having multiple tools — it's about how those tools talk to each other.

When your systems aren't aligned, your data isn't aligned. And when your data isn't aligned, your teams can't align either.

Your tech foundation consists of:

1. Your CRM manages customer relationships, tracking people, companies, and deals
2. Your CDP captures user behavior and events, detailing what people actually do
3. Your data warehouse stores all this raw information for reporting and analysis

But here's where most companies go wrong: they treat these as entirely separate systems rather than connected components in a single coherent strategy.

What's the actual difference between your CRM and CDP? It comes down to schema — the way data is structured. A CDP tracks events and user actions, while a CRM tracks entities and relationships. Understanding this distinction isn't just technical trivia — it's essential to building a stack that makes sense.

At Clarify, our entire product is built around the recognition that these systems should work in harmony, or better yet, that your CRM could act as a CDP, too. The contrast is stark when compared with experiences at companies like Ramp, where a Salesforce stack cost millions of dollars annually and required a team of 10 to maintain. That complexity wasn't just expensive — it actively made the revenue team less efficient.

The dangerous allure of enterprise tools

Pre-revenue startups frequently report proudly implementing Salesforce. It's like watching someone buy a $20,000 triathlon bike for their first ever race. Sure, professional athletes use that equipment, but for someone just starting out? It's absolute overkill that creates more problems than it solves.

The reality is that RevTech needs to evolve dramatically as companies grow:

At the startup stage:

• Basic contact management and deal tracking
• Simple pipeline visualization
• Nothing fancy — just a clear way to keep relationships from falling through the cracks
• Many founders start with a Google Sheet or Notion doc, which is perfectly fine until >15-20 deals, then consider a lightweight CRM

In the growth phase:

• Activity logging becomes critical
• Communication tracking across the team
• Workflow automation starts mattering
• This is where many companies first feel the need for a "real CRM"

At scale:

• Deep integrations with your full tech stack
• Comprehensive audience segmentation
• Advanced reporting and attribution systems
• Enterprise-grade security and compliance

The trick is finding tools that solve current problems without creating new ones through unnecessary complexity. As one founder recently shared:

"We spent six months implementing Salesforce only to realize our team hated using it. We ended up with worse data than when we were using Notion because nobody wanted to log anything in this overcomplicated system."

Working with hundreds of founders reveals a consistent pattern: companies routinely overestimate what they need today and underestimate how quickly those needs will change. The result? Expensive, underutilized systems that create more friction than value.

The attribution wars: When sophistication becomes self-sabotage

Here's the uncomfortable truth about multi-touch attribution that nobody wants to talk about: most attribution models that companies obsess over are fundamentally broken. They completely fall apart when considering how people actually make purchasing decisions.

The reality of customer behavior:

• How often do you click on a YouTube ad?
• How often do you use a podcast's promotional code?
• How many times have you seen a billboard, then searched for the company later?

Most consumers see or hear these messages, and then days or weeks later, go directly to the company's website. No cookie tracks that journey. No pixel captures that influence.

Yet companies spend countless hours building elaborate attribution models based on touch data that misses most of the actual customer journey.

At Ramp, the team learned this lesson the hard way. With a $100M+ marketing budget, they initially tried to build sophisticated attribution models. Eventually, the realization came that sometimes a simple model with acknowledged limitations is more useful than a complex one built on faulty premises.

This meant being transparent about what they couldn't track perfectly — like offline influences, brand awareness effects, and cross-device journeys — rather than pretending their models captured everything. This honest approach to data's inherent blind spots led to more grounded decision-making and prevented the team from over-optimizing toward flawed metrics that didn't actually represent true marketing effectiveness.

For early-stage companies, here's a pragmatic approach:

1. Focus on one clear conversion metric — whether that's demo bookings, trial starts, or qualified pipeline
2. Use basic incrementality testing to understand what's working
3. Run geographic experiments — concentrate marketing in specific regions and measure lift compared to control areas
4. Start with directional insights rather than false precision

This approach doesn't require fancy tools — just disciplined experimentation that reveals actual causality rather than illusory correlations.

Early-stage companies can start by concentrating marketing efforts in specific regions to test effectiveness. For example, a company might focus their paid social budget in a few key states while measuring performance against control regions. This geographic testing often reveals channel impact that traditional attribution models miss entirely.

Sophisticated approaches like Marketing Mix Modeling only make sense when companies spend millions on marketing. Before reaching that scale, teams should focus on simpler experiments that provide clearer directional insights without the false precision that often misleads decision-making.

The lead object debate: A perfect example of revtech overthinking

Want to start a fight among RevOps professionals? Ask them whether to use lead objects in a CRM.

This seemingly technical question perfectly illustrates how historical artifacts can create unnecessary complexity. Let's break it down:

The historical context:

• The lead object exists in Salesforce because, in 1999, data quality management was incredibly difficult
• Leads were essentially a "garbage dumpster" for unvalidated contacts
• Sales reps would manually convert qualified leads into "real" contact records
• This separation helped maintain database cleanliness in an era of limited technology

Fast forward to today, and this data model makes little sense. With modern tools, companies can validate and enrich contact data automatically. The separation creates unnecessary friction and confusion.

As one customer recently shared:

"I'm not a big fan of the lead object because it causes a lot of confusion. I do enablement too, and I can see it has value in the way the structure is, but it causes more problems than it solves."

Another RevOps leader puts it this way:

"It could be useful to tell sales that they are only supposed to reach out to leads, for example, not to reach out to contacts. For certain companies and types of leads, there are more efficient ways to go about them, and not always do you want to have a human interacting with people."

This isn't just a technical detail — it reflects a broader truth about RevTech: sometimes the "standard" approach exists not because it's optimal, but because it's a historical artifact from a different technological era.

Finding your balance: The art of right-sized revtech

After observing hundreds of revenue teams, a pattern emerges among the most successful ones. They aren't looking for the most sophisticated tools or the most comprehensive features — they're looking for the right balance between capability and complexity for their current stage.

The four principles of balanced revtech:

1. Start with real problems, not theoretical ones

Focus on the actual friction points teams face today, not what might arise at 10x the current size. At Clarify, this means constantly asking customers:

• What manual tasks consume most of your time?
• Where are deals falling through the cracks?
• What information can't you access when you need it?

2. Recognize that technology decisions aren't permanent

A company of 10 people is fundamentally different from that same company at 100 people, which is different again at 1,000 people. Tech stacks should evolve accordingly.

Make decisions with a 12-18 month horizon rather than trying to solve for an imagined future state years down the line. As one customer recently shared:

"We wasted a year trying to build the perfect stack that would scale to $100M ARR when we were only at $2M. We should have focused on solving today's problems efficiently and accepted that we'd need to evolve our systems later."

3. Prioritize adoption and usability above all

The most powerful CRM in the world is worthless if the sales team hates using it. Too many companies force their teams to use clunky, complicated systems in the name of "best practices," only to find that the promised benefits never materialize because nobody actually uses the system as intended.

4. Build with integration in mind from day one

A RevTech stack isn't a collection of independent tools — it's an ecosystem. Each component should talk to the others, creating a cohesive environment rather than a fragmented landscape of information silos.

The joy factor: The most underrated aspect of revtech

Here's something that doesn't get discussed enough: joy matters in enterprise software. If revenue teams dread logging into their CRM, they won't use it effectively — no matter how sophisticated its capabilities.

Countless hours observing salespeople and marketers interact with their tech stacks reveals a pattern. The difference between successful adoption and silent rebellion often comes down to one factor: does this tool make the job better or worse?

What creates joy in RevTech?

• Tools that automate tedious tasks nobody wants to do
• Systems that surface information when it's actually needed
• Software that gets out of the way when not required
• Interfaces that feel intuitive rather than frustrating

This isn't just about UI design or user experience — though those certainly matter. It's about whether a RevTech stack is built around helping teams achieve their goals or forcing them to jump through administrative hoops that add no value.

Consider what one Clarify customer shared after switching from their previous CRM:

"I'm in my CRM an hour and a half less every week than I was before. The enrichments happening in the background are so helpful — I don't think I've created a person in Clarify in weeks at this point."

That's time given back to focus on high-value work. For their co-founder, who spent more time logging calls and taking notes, the time savings were even greater at nearly 3 hours per week.

This is why Clarify was built with a relentless focus on reducing manual work. The system automatically captures interaction data, drafts follow-up emails based on conversation transcripts, and eliminates the need for manual data entry. It's not just about efficiency — it's about giving people back the time to focus on what they're actually good at: building relationships.

The balanced path forward

The biggest opportunity in RevTech isn't adding more complexity — it's finding the right balance between sophistication and simplicity for a company's current stage.

First, match tools to the current reality:

• If just starting out: Embrace simplicity. A basic CRM with clean data is infinitely better than an enterprise monstrosity that nobody uses correctly.
• If in growth mode: Choose tools that scale with the business. Look for systems with the right balance of capability and complexity that can grow alongside the organization.
• If at scale: Focus on integration and efficiency. The challenge isn't finding capable tools — it's making sure they work together seamlessly.

As companies grow, they should evolve intentionally. Don't add complexity until clearly outgrowing current capabilities. When upgrading, do it with a clear understanding of the specific problems that need solving.

And regardless of stage, remember that tech stacks exist to serve revenue teams — not the other way around. If a tool is creating more friction than value, it doesn't matter how "enterprise-grade" it is. It's the wrong tool.

The companies that win aren't the ones with the most sophisticated RevTech stacks — they're the ones with the most appropriate stacks for their current needs. They understand that finding the right balance isn't a one-time decision but an ongoing process of adaptation and evolution.

So when evaluating a new tool for the stack, ask this crucial question:

"Is this solving a real problem we have today, or are we overengineering for a future state?"

The answer will guide toward the balanced approach that drives real results.