The marketing attribution data app that changed everything

When I first joined Hex, I had one burning question: What’s worked here before and how do we know?

As Head of Growth Revenue, I was stepping into that classic new-employee fog: you don’t have the full story behind what had worked before or why, just instincts, scattered anecdotes, and a growing list of questions. Meanwhile, decisions are flying, programs are running, and you’re getting asked for answers.

That fog cleared up when I was introduced to a data app that our team had built to track the downstream sales impact of every marketing campaign. It was a living app that connects your marketing to business outcomes, not just vanity metrics. Suddenly, I wasn’t guessing. I could see clear evidence of what worked and why.

If you've been wondering what's truly effective in your marketing efforts, a data app like this might be helpful for you, too!

The question: Do events impact pipeline? And if so, which ones?

Events are notoriously hard to measure. A happy hour might feel electric, a conference booth buzzing, a dinner perfectly curated, but “feel” doesn’t justify a budget.

I needed to know: Should we double down on hackathons or conferences? Were intimate dinners more impactful than splashy sponsorships? Did any of this actually move buyers through the funnel, or just generate fleeting buzz?

To move forward with confidence, our team needed answers to questions that felt deceptively simple:

• Do in-person events outperform virtual ones?

• What role does audience type play in event success?

• Which programs deliver lasting pipeline versus short-term buzz?

The solution: A data app that gives you clarity to plan smarter

The answer for us resides in the Campaign Impact data app, built in Hex, that pulls in Salesforce opportunity data, campaign members, and insights by company size (otherwise known as segment). The app helps us clearly connect the dots between marketing activities and real revenue.

At its core, it makes the invisible visible: it shows how events, content, and other journey touchpoints, such as CTAs and paid ad sources, collectively influence the buying journey. Instead of treating each event in isolation, we can group them together, compare formats, and track their impact over time.

Here are some of the areas it helps us get clarity on:

Campaign groups and parsing – Instead of looking at each activity in isolation, I can group related tactics into a single campaign view. For example, if we sponsored a booth at a conference and layered on a happy hour, an executive dinner, and some pre-event awareness, I can see their collective impact on pipeline. This gives me a clearer picture of overall reach and frequency, and how the mix of tactics works together. At the same time, I can also drill down into a single element, say just the happy hour, to understand its unique contribution within the broader campaign. Do I need to include this component again next time or can we do without and have the same impact?

View near- and long-tail impact over time – With flexible data parameters, I can measure results long after a campaign has ended. Even if the program ran a year ago, I can see how long it continued to influence pipeline and answer: how many months did campaign members convert to MQLs? When did they become opportunities? I can also zoom in to view only recent performance, such as the last two months and then layer in other activities to see what may be driving performance. Getting this deeper information is even easier when I ask our Notebook Agent.

This visibility is powerful from two angles:

1. Pipeline performance:

   Big programs rarely create impact in a straight line. For example, a large campaign we ran in June drove an immediate spike in the weeks that followed. Then, momentum slowed during the quieter summer months, only to resurface in early fall when conversations and connections matured into opportunities. Pipeline impact naturally comes in peaks and valleys, but the long-tail effect of flagship initiatives often proves just as valuable as the initial spike.

2. Content planning:

   Not all leads enter with the same intent. Event leads, for example, often start with lower intent and benefit from a steady diet of educational content. In contrast, someone who downloads a specific piece of content may signal higher intent and be ready for more technical or product-focused material. Understanding these patterns helps tailor nurture strategies that meet prospects where they are in their journey.

Segment drilldowns – I can filter the view by segments, geographies, or other attributes to understand how the impact varied across audiences. This is especially helpful for knowing which tactics and messaging resonates the strongest for each segment.

What this app has made clear

Using the app, I’ve been able to cut through the noise and actually see what’s working. For example:

• Understand campaign impact at scale. Instead of looking at events in isolation, I can see every touchpoint tied to a major conference or regional series.

• Spot critical moments. Some tactics don’t generate instant ROI but move deals forward in meaningful ways — we can now identify and value those.

• Balance short-term wins with long-term plays. The app shows how immediate returns fit into the longer, multi-step enterprise buying cycle.

• Measure quarter comparison. Was Q2 more effective than Q1? We can finally answer questions like that with data.

• Compare formats. Dinners vs. hackathons, workshops vs. panels — it’s easy to see what resonates most.

• Track series as a whole. Instead of measuring single events, we can evaluate how a full program or sequence performed as a package.

The surprising things we learned that shifted strategy

Here are a few surprising things we learned.

1. Hackathons do work - One big surprise was around our hackathon events. They’ve always felt like fun, high-energy brand moments, exciting to host, but not necessarily something we expected to see direct pipeline from. The data told a different story: even online hackathons converted. That reminded us how powerful it is to let people build, try, and feel the product, and got us thinking about how to spark that same engagement in other formats.

2. Happy hours matter more than expected - I once thought happy hours were just name-generators. Turns out, they have influenced pipeline. Without the data, we might have written them off completely.

3. Enterprise deals are long games - Ok, maybe this is no surprise, but it is still exciting to see that dinners, webinars, and conferences play a role in the multi-touch journeys of enterprise sales. A dinner, webinar, or conference interaction might not close a deal tomorrow, but it can be an influential touchpoint that makes a deal possible months later.

How this app has improved our marketing strategy

The app has significantly improved our team’s effectiveness in a few ways:

Clarity on overall impact

When launching new programs, we can now confidently say, “We know this may not generate first-touch pipeline, but let’s measure its influence on the journey.” Since we use a first-touch attribution model, a lot of important programs weren’t being properly recognized before. The data app gives us a way to track the broader impact of these touchpoints.

Metrics for program builders

It helps us see what content and programs are raising the bar. We can define and track meaningful metrics outside of just pipeline, like whether these touchpoints are attracting MQLs in different segments.

Historical visibility

As someone new to Hex, having the ability to look back across multiple views of past campaigns has been invaluable. It helps me make more informed decisions about where to invest and which programs to evolve.

Your next steps: Build attribution that drives decisions

If you’re a growth marketer or data scientist, don’t settle for vanity dashboards. Build something that connects your work directly to business outcomes. It changes everything: how you invest, how you defend your strategy, and how fast you can cut through the fog.

And now, with our Notebook Agent, it’s starting to feel less like a report and more like a strategy partner. It surfaces ideas I hadn’t even considered and is helping us make decisions faster, with more clarity. That’s the thing about good data: it challenges your assumptions. And it forces you to rethink what success looks like.

Thanks to Bryanna Clancy and our incredible data team for making this dashboard not just possible, but indispensable.