“Where do your customers come from?”
For eCommerce marketers, this is the all-important question. Knowing which marketing channels perform best allows you to spend marketing dollars effectively and grow revenue efficiently.
Analytics data is helpful for marketing attribution, but it doesn’t always tell the whole story.
For instance, what if customers arrive by organic search, but they searched for you because they heard about you from friends? What about customers who see a Facebook ad, but later visit your site directly? And how do you track the impact of podcasts, radio ads, billboards, TV commercials, or even word-of-mouth?
When it comes to learning how customers get to your site, sometimes it’s best to just ask.
That’s why many brands use How Did You Hear About Us? (HDYHAU) surveys to improve marketing attribution. We cover HDYHAU surveys in our latest video:
Keep reading for an in-depth look at HDYHAU surveys.
What Is a "How Did You Hear About Us" (HDYHAU) Survey?
A "How Did You Hear About Us" (HDYHAU) survey is a one-question survey that asks respondents, well, how they heard about you. It’s a simple survey, but it’s a powerful way to fill in the gaps and give you a clearer picture of your marketing performance.
Some brands choose to deploy HDYHAU surveys to all site visitors. This shows you which channels lead people to your site, but it doesn’t always show which channels lead to customers.
Post-purchase HDYHAU surveys capture insights at the moment customers are most engaged with your brand: while they’re completing a purchase. This allows you to see which channels result in real revenue.
Creating a Successful Post-Purchase HDYHAU Survey
There are countless survey tools, including Digioh’s survey software, that allow you to launch surveys quickly. Knowing your necessary integrations and required level of control will help you choose your ideal solution.
With your tools lined up, consider what channels you’ll use to deploy surveys. You can send post-purchase surveys by email or SMS, but survey pop-ups on your checkout page are a particularly effective, low-friction way to get responses. While not every customer will open an email, every customer who checks out will see the pop-up.
An on-brand pop-up survey can seamlessly fit into your checkout process, leading to better survey UX and higher response rates. In fact, Digioh’s customers see 80% response rates with pop-up HDYHAU surveys.
Next, craft your question wording. Most surveys stick with the namesake question: “How did you hear about us?” Others may tweak copy to match their brand’s voice.
Still, some take a different approach entirely. The survey pictured here asks “Which of these things influenced your decision to purchase?” before allowing respondents to check up to three boxes. While it requires a bit more thinking on the customer’s behalf, it can provide interesting insights into customer behavior and decision making.
Another consideration is which answer choices to include. Too many choices may overwhelm respondents, but include too few options, and you may miss out on data. Adding an “other” option with a text field ensures no customer is left out, and it can even uncover surprise sources. Digioh’s conditional fields allow you to add text fields that appear if users select the “other” option.
Reducing Response Bias in Attribution Surveys
While no survey is completely bias-free, minimizing bias is an important part of good survey design. Unfortunately, it’s tougher than it sounds. Even something as simple as question ordering can skew your results.
Still, even a one-question survey isn’t immune to bias. Response bias refers to conditions that cause people to answer questions falsely.
With self-reported data, response bias is inevitable, and attribution surveys are no different. For example, some customers may forget how they heard about you. They’re not trying to answer falsely; they genuinely don’t know, so they just pick the first answer and hit submit.
In fact, people often gravitate towards the first answer in a multiple-choice question. This is called primacy bias. Recency bias, when people tend to choose the last answer in a question, is also commonly-observed in multiple-choice questions.
To minimize primacy and recency biases in your survey results, randomize the order of your HDYHAU answer choices. While random order won’t eliminate all false answers, it will help prevent them from skewing your data.
Solving the eCommerce Attribution Puzzle
Many survey tools collect HDYHAU survey data anonymously. Anonymized data may tell you which channels lead to customers, but it doesn’t tell you what kinds of customers they create.
Digioh’s post-purchase survey tool ties survey responses to the customer data collected during checkout, including their email address, referring URL, cart items, and other information.
Of course, collecting this survey data is important, but only if you can put it to use. That’s why it’s also important to choose survey solutions that integrate with your analytics and business intelligence tools.
This integrated, identity-based data gives you a more complete view of marketing attribution, empowering you o answer deeper questions about your customers, like:
- Which channels are creating repeat customers?
- What referral sources lead to the highest cart values?
- Are particular offline channels performing better in certain markets?
With these answers at your side, you won’t just improve your marketing attribution; you’ll have the data you need to help improve your marketing performance too.
Add HDYHAU Surveys to Your Checkout Process
Your marketing team is working hard. It’s only fair that you have the data you need to make informed decisions and get the most from your marketing efforts. When combined with your analytics, actionable data from your HDYHAU surveys can help you achieve this.
Digioh’s drag-and-drop survey software integrates with the rest of your marketing stack, allowing you to create HDYHAU surveys with ease. To start learning more about your customers, talk to us! We’ll be happy to help you design and launch a survey that fills in your marketing attribution gaps.