Self-reported attribution is the practice of asking buyers directly how they first heard about you, usually through a single open field on a demo or signup form, and using their answers as an attribution source alongside analytics.
Self-reported attribution captures the buyer's own account of what brought them to you. It is sometimes called the "how did you hear about us" field, or HDYHAU.
It exists because analytics can only record what happens on surfaces you own or can tag. A podcast episode, a private community recommendation, or a colleague forwarding a link produces no trackable event. The buyer, however, remembers it. Asking is the only way to retrieve that information.
The single biggest implementation decision, and most teams get it wrong.
[table]
| Open text field | Dropdown menu
Captures unknown sources | Yes. This is the point | No. Only options you predicted
Answer quality | Specific, often naming a person or episode | Constrained to your categories
Analysis effort | Requires categorisation, manual or automated | Instant, pre-categorised
Common failure | Left blank if optional | "Google" and "Other" absorb everything
Recommended | Yes, required field | Only as a secondary follow-up
[/table]
A dropdown can only return answers you already thought of, which defeats the purpose. The whole value is discovering the sources you did not know about. An open field returns answers like "saw a post from your founder about attribution about two months ago", which no dropdown would ever produce and which is worth more than a hundred rows of "Search".
Placement: on the demo request or signup form, as a required field. Not in a post-sale survey, where recall has degraded and the sales conversation has contaminated the memory. Not as an optional field, which is left blank 60% to 80% of the time.
Wording matters more than it should. "How did you hear about us?" tends to produce the last touch, because that is what is top of mind. "How did you first hear about us?" produces the origin, which is the thing you cannot otherwise see. The word "first" is the difference between duplicating your analytics and complementing it.
Length: one field. Adding a second question measurably reduces form completion, and the marginal information is not worth the conversion loss.
It surfaces the channels that produce influence without producing sessions.
The typical result when a B2B SaaS company adds a required first-touch field: somewhere between 20% and 40% of answers name a source that appears nowhere in analytics. Podcasts, a specific person's LinkedIn posts, a Slack community, a peer recommendation, a conference talk. In last-click reporting every one of those buyers was attributed to branded search or direct.
The second thing it reveals is which people are doing the work. If a founder's LinkedIn posting gets named by name in a meaningful share of responses, that is evidence for expanding the thought leadership programme that no attribution model would ever produce.
Neither finding is available any other way. That is why a field with almost no search volume attached to it is worth building a page about.
Two failure modes.
The field is optional. Optional fields are skipped by most respondents, and the ones who answer are systematically unrepresentative, skewing toward highly engaged buyers. Making it required costs a small amount of form conversion and produces a dataset you can act on. The tradeoff is worth it on a demo form, where intent is already high.
Nobody reads the answers. The field is added, responses accumulate in the CRM, and no one categorises or reviews them. Self-reported attribution needs a monthly ritual: export the answers, group them into rough buckets, and compare against what analytics reported. Thirty minutes a month. Without that, it is a form field that lowers conversion and returns nothing.
Add one required open text field asking how the buyer first heard about you, and review the answers monthly against your attribution report.
The two datasets answer different questions and disagreement between them is the useful signal. Where analytics says branded search and the buyer says a podcast, both are true: the podcast created the demand, branded search captured it. That gap is exactly the information needed to justify demand creation budget in a review where attribution shows nothing.
This is a thirty-minute setup that produces the most reliable read available on the untracked part of the funnel. It is not a substitute for analytics and it is not precise. It is the only direct evidence you will ever have about the part of the journey nothing else can see, and in B2B that part is usually the majority.
One warning. Do not aggregate self-reported answers into a percentage and present them as an attribution model. Human recall is imperfect and the sample is only buyers who converted. Read it as a source of qualitative signal and channel discovery, not as a measurement system.
The practice of asking buyers directly how they first heard about you, usually through an open text field on a demo or signup form. It captures influence from podcasts, private communities, peer recommendations and social feeds that produce no trackable analytics event.
Open text. A dropdown can only return options you already anticipated, which eliminates the discovery value entirely. Open answers frequently name a specific person, episode or community, information no predefined list would have surfaced.
Required, on the demo request form. Optional fields are skipped by most respondents and the answers you do get come from an unrepresentative sample of highly engaged buyers. The small loss in form conversion is worth the usable dataset.
Use "How did you first hear about us?" rather than "How did you hear about us?". Without the word "first", respondents name the most recent touch, which usually duplicates what analytics already told you. With it, you get the origin of the journey.
Not very, as a measurement system. Recall is imperfect and only converted buyers answer. Its value is qualitative and directional: it reveals which untracked channels influence buyers and which people or content get named, neither of which any analytics tool can show you.
Related: Multi-Touch Attribution · Dark Funnel · Demand Capture
If a third of your buyers are naming a source your analytics has never recorded, that is usually the channel worth funding next.
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