Mailtrap made a multi-step survey a required part of signup. Counterintuitively, this added friction had no negative impact on conversion rates. The collected data on user intent, role, and marketing attribution proved invaluable for segmenting users and focusing on high-value cohorts, informing both product and marketing strategy.
Related Insights
To test demand for an 'email campaigns' feature, Mailtrap added a non-functional button to their main menu. Clicking it led to a survey asking users what they wanted. This simple, no-code experiment generated 300 detailed replies in weeks without any incentives, validating the idea and creating a user-driven feature roadmap before any development began.
Despite lower volume, leads from high-intent forms like 'demo request' converted at double the rate of product trials. They also resulted in deals that were twice as large, highlighting a massively undervalued pipeline source that was being ignored in favor of high-volume, low-quality trials.
Mailtrap invested in creating a streamlined, low-friction onboarding experience, assuming it would significantly boost conversions. The change had almost no impact. They discovered their developer audience valued the product's core utility so much that they were willing to complete extra steps, rendering the simplified UX improvements ineffective for conversion.
Instead of focusing solely on conversion rates, measure 'engagement quality'—metrics that signal user confidence, like dwell time, scroll depth, and journey progression. The philosophy is that if you successfully help users understand the content and feel confident, conversions will naturally follow as a positive side effect.
Instead of presenting all form fields at once, use a two-step process. The first step asks only for an email address, a low-friction action. This allows you to capture a lead for remarketing even if the user abandons the second step.
Instead of directing users to a landing page with a form, ask them to simply reply to the email with a keyword to receive a guide or discount. This reduces friction and can exponentially increase the number of people who take the desired action compared to traditional methods.
Instead of manually sifting through overwhelming survey responses, input the raw data into an AI model. You can prompt it to identify distinct customer segments and generate detailed avatars—complete with pain points and desires—for each of your specific offers.
Many founders operate on flawed assumptions about how they acquire customers. Analyzing marketing data often shatters these myths, revealing that sales and traffic come from unexpected sources. This discovery points to untapped growth opportunities and where marketing energy is best spent.
Beyond marketing metrics, actively soliciting replies on non-business topics (e.g., "What's your favorite hobby?") uncovers valuable first-party data about your audience's interests. This enables more relatable and personalized content that resonates on a human level.
As a freemium product with millions of users, Polly struggled to identify its true buyers. By adding simple "book a demo" links and feedback request emails into the onboarding flow, they generated hundreds of valuable conversations that clarified their monetization path and ideal customer profile.
