What Is Marketing Attribution?

You spent $50,000 on marketing last quarter. Revenue went up. But which campaigns actually drove that growth? Was it the LinkedIn ads, the email nurture sequence, or the conference sponsorship? Marketing attribution answers these questions.

The Basic Problem

Most companies know their total marketing spend and their total revenue. What they don't know is the connection between them.

A customer might see your LinkedIn ad, read a blog post, attend a webinar, get an email, and finally book a demo. Which of those touchpoints gets credit for the sale? All of them? The first one? The last one?

Attribution Models Explained

There are several ways to assign credit across touchpoints:

First Touch - All credit goes to the first interaction. The LinkedIn ad that introduced them to your brand gets 100% credit. Simple, but ignores everything that happened after.

Last Touch - All credit goes to the final interaction before purchase. The demo request page gets 100% credit. Also simple, but ignores how they found you.

Linear - Every touchpoint gets equal credit. If there were 5 touchpoints, each gets 20%. Fair, but probably not accurate - not every interaction is equally valuable.

Time Decay - Touchpoints closer to the purchase get more credit. The demo gets more credit than the LinkedIn ad from 3 months ago. Makes intuitive sense for longer sales cycles.

Position-Based (U-Shaped) - First and last touchpoints get 40% each, the middle touchpoints split the remaining 20%. Acknowledges that introduction and conversion are particularly important.

Data-Driven - Uses machine learning to analyze your actual data and determine which touchpoints correlate with conversions. The most accurate, but requires significant data volume.

Why This Matters

Without attribution, you're flying blind. You might be:

• Spending heavily on channels that don't convert
• Underfunding the channels that actually drive revenue
• Unable to justify marketing spend to leadership
• Making decisions based on gut feel instead of data

Good attribution tells you where to put your next dollar.

The Technical Challenge

Here's where it gets complicated. To do attribution properly, you need to:

Track users across touchpoints. This means connecting anonymous website visits to known contacts to closed deals. It requires proper tracking infrastructure - cookies, UTM parameters, CRM integration.

Connect marketing data to sales data. Your ad platform knows about impressions and clicks. Your CRM knows about deals. Connecting these requires a unified data layer.

Handle long sales cycles. In B2B, months might pass between first touch and purchase. Your data needs to maintain that connection over time.

Account for offline touchpoints. Conferences, phone calls, and in-person meetings don't automatically get tracked. Manual logging is often required.

Getting Started

You don't need a complex multi-touch model to get value from attribution. Start simple:

1. Track UTM parameters consistently. Every campaign, every channel, every ad. Make it a habit.

2. Integrate your ad platforms with your CRM. Most platforms (HubSpot, Salesforce, etc.) have native integrations with Google, LinkedIn, and Facebook ads.

3. Start with first-touch and last-touch. These are easy to implement and still valuable. You can see which channels bring people in (first touch) and which channels close deals (last touch).

4. Graduate to multi-touch when you have volume. Multi-touch models need data to be useful. If you're closing 10 deals a month, simple models work fine. At 100+ deals, multi-touch starts to shine.

Common Mistakes

Over-engineering too early. A startup with 5 customers doesn't need a data-driven attribution model. Start simple.

Ignoring data quality. Attribution is only as good as your tracking. Missing UTM parameters, disconnected systems, and inconsistent naming conventions will give you garbage results.

Treating attribution as absolute truth. All models are simplifications. Use attribution as a guide, not a law. Combine it with qualitative feedback from sales.

Not acting on insights. Attribution is pointless if you don't change behavior. If data shows LinkedIn outperforms Facebook 3:1, shift budget accordingly.

The Bottom Line

Marketing attribution connects your marketing spend to your revenue. It's not perfect - no model captures the full complexity of how people make buying decisions. But even imperfect attribution is better than no attribution.

Start with simple tracking and basic models. As your data grows, your attribution can grow with it.

This is part of our analytics fundamentals series. Next, learn about what a data warehouse is and why it matters.