New
Advanced Attribution
Your customers don’t think in channels.
A rebuilt “How did you hear about us?” to match the way they actually remember.
The post-purchase survey, rebuilt for your marketing attribution needs.
THE BREAKING POINT
Your static, single-response survey is falling flat, literally.
One flat survey response leaves marketers with ambiguous data, channel confusion, and leaking signal.
How did you hear about us?
Four different spend decisions. One vague answer.
The flat survey
Your flat survey can’t answer a single one. Thousands of responses, not one name you can act on.
33%
less placement-level attribution when plans force customer responses into one flat list.
Your Report This Month
THE SOLUTION
So we built Advanced Attribution.
Three updates to how our post-purchase attribution surveys work.
01
An adaptive question
Ask once, know exactly which ad, post, or influencer drove it.
02
Response options that stay current
Response lists update automatically as your partner data changes, no manual edits.
03
A record you can spend against
Every response resolves into a structured record you can act on.
The post-purchase survey’s next evolution into marketing attribution software.
An adaptive question
A question that thinks like your customer, not your marketer.
How did you hear about us?
- Google search
- From a friend
- YouTube
- Podcast
- From a friend
- Podcast
- TV
- TikTok
- An influencer
- Podcast
- Radio
One placement
- creator
- @emmachamberlain
- channel
- YouTube
02
Response options that stay current
Survey response lists that are active, not static.
Bi-directional auto-sync
Your media list automatically syncs to your survey response options.


A record you can spend against
Better data, higher fidelity.
How did you hear about us?
YouTubeWhere on YouTube?
A creator’s videoWhich creator?
@emmachamberlain
The record your stack receives
- answer
- YouTube
- channel
- YouTube
- format
- Creator video
- creator
- @emmachamberlain
TRUSTED BY DTC TEAMS
3,000+
brands trust Fairing
5.0 (180 reviews)
A product video beside three timestamped jump points: at one minute 23, dynamic questions go beyond broad channel-level responses, learning which ad, which creator, which podcast; at two minutes 44, media lists sync to your survey response options, keeping them current; at three minutes 34, ambiguous “Other” answers resolve on their own, extracting the usable signal.
Read the transcript
Hello, I'm Amalia, a product manager at Fairing. Today, we're excited to introduce the biggest update to the "how did you hear about us" survey since the dawn of the internet.
The modern marketer's media mix is constantly evolving. Consumers are increasingly discovering brands through the channels that are the hardest to measure — creators, podcasts, connected TV, and more. Channels where there's no click, no effective pixel, or no event to track. That's a real problem the moment you're deciding whether to increase spend you can't prove is working.
We kept hearing the same thing from our users: they wanted to more effectively attribute revenue to those channels so they can make better decisions with their top-of-funnel budget. The problem was the survey tool built to answer that question was falling flat, literally. The single-response static survey at checkout that hadn't evolved in decades was leading to misattributed credit and muddled guidance, so we rebuilt it.
After spending months talking to our customers and analyzing over a billion HDYHAU (how did you hear about us) questions asked, we built the biggest update to post-purchase surveys ever. We reinvented our product around three key principles.
First, the survey should match how your customers think, not how the marketer thinks. In the old survey design, one flat list forced every customer to think in channels. They were asked whether they found you through a podcast, YouTube, or an influencer — and the exact channel and placement combination that worked was lost. In the new design, the survey adapts to how your customers actually experience discovering your brand: how they want to answer, not how the marketer wants to ask.
Let's say three different customers were influenced by the same podcast on YouTube. Customer one starts by selecting podcast and then selecting Huberman Lab. Customer two goes to YouTube first and then also selects Huberman Lab. Customer three selects "other" at the top level, starts typing "Huberman," and is also able to select Huberman Lab on YouTube. Three different customer survey response pathways, the same destination: the exact placement that drove the sale.
Ultimately, by flexibly accounting for different customers' mental models, we see brands get 49% more placement-level attribution — fundamentally changing ROAS and improving future allocation decisions.
Second, your survey response options shouldn't be static. They should be a living, breathing stream that autonomously syncs with your media plan. In the old survey design, keeping that list current meant someone manually adding every new podcast or creator by hand — usually after it had already launched, sometimes never. In the new design, the list keeps itself current. Now you can manage your response options in a centralized place where both your brand and your partners can contribute. We integrated directly with partners such as Agentio, Podscribe, and Vibe, so the moment a new placement goes live in your media plan, it's already an option in the survey.
So you can see Agentio pushed response options here, and when a customer goes to the front end and selects influencer, YouTube, et cetera, they'll see the options pushed by Agentio. Four out of five brands we audited had a real investment missing from their survey entirely — now it's there automatically the moment you start spending.
Third, your survey shouldn't require manual work for higher fidelity. In the old survey design, cleaning up "other" responses was a manual job — someone had to read through every write-in by hand to figure out which ones were actually a podcast or creator you already tracked. In the new design, the survey resolves those write-ins itself. The moment someone's answer matches a placement in your synced list, it's counted as that placement immediately, not stuck under "other" waiting to be read.
Customers are often misspelling the channel they attribute to their discovery — for example, misspelling "James Charles" — and that submission now automatically gets categorized under YouTube in Fairing, where it belongs.
The intention behind the HDYHAU survey hasn't changed: ask your customers, they know best. What's changed is the clarity, depth, and value of your customers' responses. The goal behind all three of these principles is the same — make the marketer more efficient: better attribution, less manual work, and more time spent on the decisions that actually grow the business.
If you want to learn about how to get access to our Advanced Attribution product, book a demo below. We can't wait to show you what we've built.
FAQS
Common questions.
How is Advanced Attribution different from a static post-purchase survey?
A static survey asks one fixed question with a list of channels that never changes, no matter what a customer picks or types. Advanced Attribution replaces that in three ways. An adaptive follow-up question narrows a broad answer like “Instagram” down to the exact creator, podcast, or ad. The response list stays current on its own, syncing with your active media plan through integrations with Agentio, Podscribe, and Vibe. And write-ins that would normally land in a generic “Other” bucket get matched to the right placement automatically.
What happens to write-in (“Other”) survey answers?
Advanced Attribution reads a write-in answer the same way it reads a selected one. When a customer types something that matches your synced media plan, even a partial name or a misspelling, it gets counted as that exact placement right away. Nobody has to comb through a pile of “Other” responses by hand to figure out what a customer meant.
Do I need to rebuild my survey to switch to Advanced Attribution?
You don’t have to rebuild anything. A member of our team is here to help — set up a call at fairing.co/demo.