Build vs. Buy: The Hidden Cost of Building HDYHAU Surveys
Matt Bahr
CEO & Co-Founder
,
Fairing
For most engineering teams, a "How Did You Hear About Us?" survey seems like a quick win. But what starts as a simple project quickly becomes permanent infrastructure, and infrastructure creates a hidden, perpetual tax on your product roadmap.
We built Fairing to give teams the measurement they need without paying that tax. Here's a breakdown of the real trade-offs between building in-house and buying a dedicated system. But first, let's clarify why attribution surveys matter in the first place.
Why Attribution Surveys Matter
Traditional attribution is breaking down. Pixels and cookies are disappearing, iOS 14.5 gutted tracking, and GA4 can’t follow customers across devices or offline. Meanwhile, major revenue drivers like word-of-mouth, podcasts, TV, and influencers remain nearly invisible in analytics.
Attribution surveys fill that gap by delivering ground-truth data straight from your customers. Unlike last-click attribution, which often over-indexes on lower-funnel "closing" channels and undervalues upper-funnel discovery channels, attribution surveys surface the true mix of channels across the funnel that help you figure out where your best customers come from. This allows you to validate models, calibrate spend, and reveal context you would never see in clickstream data.
To deliver real value, surveys need to be executed well with: high response rates, clean data, seamless integrations, and the flexibility for marketing teams to adjust questions and responses without waiting a sprint. This is where in-house systems typically collapse under their own weight.
Fairing vs. In-House: What the Comparison Actually Reveals
Any company can build a survey. What's harder is building and maintaining a measurement instrument you'd stake multi-million-dollar budgets on. That investment requires ongoing engineering resources that could be building your core product instead.
The difference shows up in five areas that determine whether your measurement system actually works or becomes a drain on your roadmap:
Upfront speed → Hours to launch vs. months of engineering cycles.
Marketing agility → Direct control vs. trapped in the JIRA queue.
Engineering burden → Zero ongoing maintenance vs. perpetual tax on your roadmap.
Data quality → Board-ready rigor vs. guess-driven data that creates false confidence.
Total cost → Predictable subscription vs. hidden costs that multiply over time.
The gap is about whether your team can move fast enough to capitalize on market opportunities, or whether measurement itself becomes the bottleneck.
11 Reasons Why These Differences Matter
Past the initial build, here's what determines whether your measurement system actually works or becomes a drain on your roadmap:
1 - Upfront Effort & Speed
With Fairing, you’re live in hours, not months. Drop in a single script, pick the pre-built HDYHAU template, and you’re already collecting answers. If your team uses Google Tag Manager, engineering doesn’t even need to be involved, marketing can set up and launch surveys on their own.
Building in-house is a different story. You’ll need to design the infrastructure, handle storage and logic, and prioritize it against everything else on your roadmap. What starts as a “quick project” often takes weeks before your first reliable data comes through.
2 - Design
Fairing has six question types designed and tested out of the box, and we’re continually optimizing them for the ideal design patterns that maximize response rates on every device. In-house builds force your team to design and test your own UI from scratch, risking clunky experiences that frustrate users and may actually hurt your data quality.
3 - Engineering Overhead
The hidden cost of a homegrown system is that the requests keep coming. You start with adding a follow-up question, then you need to integrate results with your data warehouse, then there's a bug fix for mobile rendering. Each request makes sense on its own, but together they create a constant drain on your core product priorities. The backlog grows faster than it gets resolved.
With Fairing, there’s no ongoing engineering involvement, and your marketing team gets the features they need without burdening your engineering team.
4 - Scalability & Flexibility
Surveys start simple, but complexity grows quickly. You may want to show follow-ups based on answers, target new versus returning customers, or feed results into multiple tools. These are edge cases for an internal build, but they’re standard in Fairing. The system is built to scale without breaking as needs evolve.
5 - Marketing Control
With Fairing, marketing teams can edit, test, and launch surveys on your own. That agility means you can respond to new campaigns or shifting priorities in real time, without pulling your engineers into the process.
In a DIY system, every change is an engineering task. Even something as small as adjusting response options requires time and attention from your dev team, creating bottlenecks that slow down both marketing and product.
6 - Data Quality
Data is only useful if it’s trusted.
Fairing is designed to protect data integrity. Features like built-in classification, randomization, and statistical extrapolation ensure cleaner results and consistent reporting, so stakeholders can rely on the numbers to make decisions.
7 - Integration Ecosystem
Fairing connects directly to the tools your teams already use: your ESPs, CDPs, analytics platforms, and data warehouses. The integrations are maintained for you, so survey data flows automatically into the right places.
8 - Compliance & Governance
Security and compliance are non-negotiable. Fairing is enterprise-ready out of the box, with the frameworks and audits in place to support privacy and governance needs.
For an internal build, that responsibility falls entirely on your team. The cost and time to build and maintain compliance add up quickly.
9 - Total Cost Over Time
DIY often looks less expensive up front, but the hidden costs add up: engineering hours pulled off the roadmap, integrations that need to be fixed, and marketing requests that sit in the queue.
Fairing offers a predictable subscription cost and a platform that continues to evolve, without draining resources from your core business.
10 - Organizational Trust & Adoption
If a system feels unreliable or hard to use, people stop using it. We’ve seen teams abandon internal builds and revert back to spreadsheets, which means marketing decisions get made on incomplete or outdated data.
Fairing provides a polished, reliable experience that your entire organization can trust, ensuring your insights get used, not ignored.
11 - Focus on Strategic Value
Building surveys isn’t your product. Every sprint debugging survey logic is a sprint not spent on your core business.
Fairing exists so your team can focus on what differentiates you while we handle the attribution complexity.
Turn Surveys Into Signal, Not Overhead
Protecting your team's focus matters more than building a survey. Every hour your engineers spend maintaining an internal form is an hour they're not spending on the core product that drives your business.
Attribution surveys look simple but hide immense statistical, compliance, and organizational complexity. A homegrown system may work in the short term, but it almost always stagnates without constant engineering overhead.
Fairing takes that complexity off your plate. Giving your marketers attribution answers in minutes and your engineers their time back allows your team to stay focused on what actually matters: building the product only you can build.
→ See how Fairing can get you attribution clarity in minutes, not months.
