Self-Reported Attribution (or, “How Did You Hear About Us?”): A Practical Guide
Dark social. Dark marketing. Dark traffic.
These are terms you have probably been hearing a lot lately, together with the less ominous, but highly technical-sounding “Self Reported Attribution.”
All this jargon is really about the same thing: how to track and find out where your customers came from, especially the ones with no referral or source data.
Or in the evergreen words of marketers across time: “How did you hear about us?”
In this guide, I’ll break down what self-reported attribution means, the value it provides, how to implement it incrementally in your marketing operations, and how to use self-reported attribution data to drive business outcomes, customer acquisition, and growth.
What is Attribution?
In the era of #efficiency, it’s all about understanding where digital marketers are getting the most bang for their buck. Attribution is an exercise of tracking and measuring customer activity, in order to understand which digital activity ‘moved the needle’, triggered, or contributed to a desired outcome.
During a conversation in 2022, Salesforce claimed that 90% of brands are using last-touch attribution. Last-touch attribution is defined as the last digital activity the customer did before converting. For example, if the customer converted after watching a video, then last-touch attribution says that the video led to the conversion. But in reality, that may or may not actually be the case.
In today’s content-saturated world, who watches a single ad that is compelling enough to trigger an instant action? When was the last time you saw a billboard, Google Ad, or Youtube Ad and instantly made a purchase or meaningful conversion as a result of that touchpoint alone?
There are many other digital attribution models to measure success. These include first-touch, multi-touch, incremental conversions, U-shaped, W-shaped, time decay, marketing mix modeling, fractional attribution… I could go on.
Whilst all these models are relevant and tell an important story, how realistic are they? Can any of these attribution models tell the true story of the customer’s interactions with the brand, and can they deliver the data-driven insights necessary to make meaningful decisions about campaign creatives and budgets?
If your hunch is ‘no’, then let’s see how self-reported attribution fits the picture.
What is Self Reported Attribution?
Self-reported attribution is a method of tracking and attributing the success of a marketing campaign by asking customers how they heard about a business or product. This information is typically collected through “how did you hear about us” surveys, and asking customers directly during the registration, onboarding, or purchase funnel.
Self-reported attribution may well indicate the most impactful marketing activity, as it is the touchpoint that the user chooses as the most memorable or meaningful, no matter where it occurred in the funnel.
Why is Self-Reported Attribution Important?
Dark social or dark marketing is user activity that cannot be tracked digitally. It can include word of mouth, offline campaigns, and conversations in boardrooms, coffee shops, and events.
We already live in a cookieless world, defined by security and privacy concerns, depreciation of third-party data, multi-device usage, and long purchase journeys with multiple decision-makers. In this environment, digital touchpoints can often be impossible to identify and track, and unreliable as a measure of the true impact of marketing activity.
“How did you hear about us” Surveys
The most common way to collect self-reported attribution data is by adding an additional field on the registration form, checkout process, or onboarding funnel. Ask the customer “How did you hear about us?” and provide a list of options, such as “online search”, “recommended by a friend”, “YouTube video”, or even “I’ve worked with your company before.”
Inevitably, the most pressing question marketers ask is: does adding an additional field lower the conversion rate of the form?
Or in other words, is the risk of reducing CVR worth the attribution data that will be collected and the insights and decisions that can be derived from that data?
Answer: You won’t know until you test it.
Run an AB test with clear and well-defined parameters to measure the impact of adding the self-reported attribution field on conversion rates. Here are some best practices to follow:
- Don’t overcomplicate, keep it simple: The form conversion rate is the primary measurement. I find it very hard to believe that a customer would not purchase an item from a brand because you asked them a simple question, “How did you hear about us?” Don’t make tentative connections to indirect impact. There are many other touchpoints (onboarding, payments, forms) that influence the end result and are not relevant to this test.
- Time is irrelevant: A statistically relevant test is only useful with a large enough amount of data. Consider it the learning phase, and run the test for as long as needed.
- Keep watching Hotjar or other tools: And keep a close eye on results for any anomalies.
- Increase or no change in conversion rates = Positive result.
- A CVR drop of less than 1% would also be considered a successful test.
- A decrease in conversion rate greater than 1% would have to be evaluated on the merits of the actionable data collected or run for a longer period of time.
- Do not connect to revenue: Intent is relevant. Someone who has a high intent to convert, will not not complete a field.
In all the tests we have run, at Outbrain and in collaboration with other brands, I have never seen a direct negative impact on conversion rates or a significant decrease that outways the value of the data collected.
In today’s macroeconomic environment, brands can be averse to experimentation, but testing in a controlled environment is Marketing 101.
“How did you hear about us?” Options
Once you’ve decided to add a self-reported attribution field to your form or checkout, the next step is to create the best setup among the various “How did you hear about us” options. Let’s take a look at the main ones:
Open field (free text) vs Fixed Field options:
Open field (free text) gives the opportunity for more granular data that you would otherwise not be able to collect. For example, instead of “YouTube”, a customer may provide more details, such as “YouTube video by Joe Blogs about the ABC feature.”
On the downside, open fields gather data that must be cleaned up and structured in order to be usable. For example, “Google Ads”, “PPC Ads,” “Google,” “Google search,” “Bing Ad” – all these fall under multiple categories, and there will always be crossover between Google Organic and Google Paid.
Also, not all leads are equal. Be prepared for irrelevant inputs. For example, don’t be surprised if you get the occasional “clkfadsknjadfskj” or a snarky “your mom told me” response.
“How did you hear about us” option: Example of open field (free text)
For Fixed Field “How did you hear about us” options, the big plus is that it is already structured and the data is ready to use. Customers simply choose a pre-defined answer from a menu.
The downside is that you will miss those opportunities for deep insights.
Also, if the customer cannot find the right answer, this may affect the conversion rate. However, this problem is typically resolved by including “Other” as one of the options. All the customers who don’t know what to answer can simply choose “other”.
In addition, if you are running campaigns across multiple and varied sources, having a list of 20 options is not ideal. Too many options may just confuse or tire the customer. On the other hand, limiting the options will also limit your data.
“How did you hear about us” option: Example of fixed field
For smaller brands with low-volume conversions from relatively few sources, I recommend you use the open field.
Larger brands with large volumes of conversion: use fixed fields, especially if you lack flexibility or resources, and do not have a champion of this data.
“How did you hear about us?”: The Data Set
To make solid decisions, you need complete data sets.
Just like any form of digital attribution, self-reported attribution is only truly valuable when you have a complete picture. Therefore, if you are adding self-attribution to your website, make sure to add it to all forms and funnels where the question “How did you hear about us?” is relevant.
Here are some more tips to follow to maximize the efficacy of your self-attribution data:
- Make “How did you hear about us?” a required field. Otherwise, you’ll be kicking yourself once you start using the data only to realize it’s incomplete, and all your assumptions and insights are met with: “Can’t use this, it’s missing data!”
- Connect to revenue and cost. Measure the CAC and LTV per channel for efficient allocation of the marketing budget and to fairly evaluate offline and online activities.
- Digital attribution vs self-reported attribution. Compare digital attribution to self-reported attribution to validate the quality and accuracy of both. Integrate into other attribution models for the ultimate hybrid decision-making capabilities.
How to Use Self-Reported Data
OK, once you’ve got the data, you need to use it for maximum impact.
Here are 7 ways you can use self-attribution data to gain valuable insights:
1. Following trends over time
With self-reported attribution, changes in the marketing mix can be seen in results generated across multiple channels and months.
The impact of a tactical change in a strategic marketing channel (i.e. cutting budget on one specific channel) can and should be measured across your entire marketing mix.
Here’s an example of a trend over time report:
2. Identifying new opportunities
Self-attribution data helps you understand the granular details of impactful marketing, with potential for scale.
While reviewing form submission data, you may find that a new influencer, blog post, or news article is referencing the brand and driving good results that can be scaled.
For example, a new content creator who mentions your brand and is generating buzz can be recruited for co-marketing collaborations.
3. Understanding “anon-omalies”
You’re seeing a peak in results but the reason is unknown – how did this happen?
Often, your best days go by without even understanding how or why. Was it luck, an opportunity grabbed, or some magical mix of marketing activities?
Using self-reported attribution is one of the more reliable ways to understand these anomalies.
4. Measuring un-trackable channels
Self-reported attribution is an important tool for the measurement of channels that cannot be tracked digitally in the usual ways.
This includes podcasts, webinars, billboards in specific locations, word-of-mouth marketing, TikTok, app installs, influencer activity, and more.
5. Understanding the impact of brand & awareness campaigns
Brand awareness campaigns are notoriously difficult to track and measure. Self-reported attribution data helps make the impact of these campaigns more visible.
For example, running YouTube ads to cold audiences with a goal of brand lift is normally measured by direct traffic and brand search term growth. Self-reported attribution adds another layer to complete this trio.
6. Prioritizing your digital marketing strategy
In times of #efficiency, you should be prioritizing what is impactful vs what is not.
Having another data set to rely on for your digital attribution efforts helps to provide a richer perspective.
7. Aligning the company
Self-attribution data is incredibly insightful, so share it internally. It helps everyone see what is working and what’s not, so the company can get aligned quickly around the most impactful strategies and activities.
Self-Reported Attribution: The Time is Now
Self-reported attribution is not going to replace digital measurement. However, it is a powerful tool that, when used correctly, can provide extremely usable and actionable data to drive growth.
Is self-attribution the most meaningful customer touchpoint? Yes and no. The best marketing campaigns are ones that don’t make the audience feel they are being marketed or sold to – rather, they create interest and/or inspiration naturally and capture attention without coercion.
If you are a data-driven marketer who will actually use this data to take action, drive growth and build effective marketing campaigns, I highly recommend you start testing self-reported attribution even today.