Hypothesizing why users aren't converting
The difference between a guess and a hypothesis
In the world of experimentation, a "guess" is based on opinion. A "hypothesis" is based on evidence. If you run A/B tests based on guesses, you are just throwing spaghetti at the wall.
The Anatomy of a Hypothesis
A strong hypothesis connects a specific problem to a specific solution using data.
Why this matters for Webflow sites
Because Webflow allows us to build so fast, the temptation is to just "ship it and see." But without a hypothesis, you can't measure success. If you change a headline and a button and an image all at once without a clear theory, you won't know which change caused the conversion lift.
How to gather the "Why" data (Qualitative Research)
Before you write a hypothesis, you need to play detective. You need to gather evidence that proves a problem exists. We rely on three main sources of "Why" data.
Session Recordings
Tools like Microsoft Clarity or Hotjar allow us to watch real users navigate your site.1
- What we look for: Are users scrolling right past your most important section? Are they "rage clicking" on an image expecting it to zoom in, but it doesn't?
- The Insight: If users are repeatedly clicking non-clickable elements, they are signaling frustration.
Behavioral Maps
- Heatmaps: We use Hotjar to see exactly where users move their mouse and click. This often reveals "distraction points." If your primary "Book Demo" button is cold (blue), but an irrelevant footer link is glowing hot (red), your visual hierarchy is broken. Users are searching for information you haven't made obvious.
- Scrollmaps: It doesn't matter how competitive your pricing is if 80% of users stop scrolling before they reach the pricing table. We use Webflow Analyze to track scroll depth and component visibility. If the data shows a massive drop-off at the "Features" section, we know that specific component is boring your audience and killing the conversion path.
- Clickmaps: These show individual clicks (or taps) rather than just density. This is how we spot "Rage Clicks"—when users repeatedly click an element that looks interactive but isn't (like a static image or a bold headline). Every unlinked element that gets clicked is a missed opportunity to move the user forward.
- Movement Maps: On desktop, mouse movement has an 85% correlation with eye movement. By tracking where the cursor hovers, we can see if users are actually reading your value proposition or just skimming the headlines and leaving.
User Polls
Sometimes the best way to find out why users aren't converting is to ask them. A simple, non-intrusive poll on the pricing page asking "Is there anything stopping you from signing up today?" can reveal objections you never considered (e.g., "I can't tell if this integrates with Salesforce").
[Internal link: /webflow-conversion-rate-optimization - reason: overview of the full CRO process]
Leveraging Webflow Analyze for component insights
Most analytics tools (like GA4) are generic. They track URLs. But modern Webflow sites are built with Components—reusable blocks like Navbars, Cards, and Footers.2
The Karpi Studio Advantage
We use Webflow Analyze to drill down into component-level performance.3 This gives us a massive advantage over generalist agencies.
- The Problem: GA4 tells you "The Pricing Page has a 60% exit rate."
- The Webflow Analyze Insight: "The Annual vs. Monthly Toggle component is being clicked 500 times, but the Price Card component is never clicked."
This granular data tells us exactly which part of the design is failing. We don't have to redesign the whole page; we just need to fix the toggle interaction or the price card layout.
How to write a valid testing hypothesis
Once you have your data (e.g., "Users are scrolling past the pricing table"), you are ready to write the hypothesis using the "If, Then, Because" formula.
The Formula:
BECAUSE [Observation/Data Insight]
IF we [Specific Change]
THEN we expect [Specific Metric] to increase.
Real-world Example:
- Observation: Session recordings show users pausing on the "Enterprise" plan but leaving without clicking contact.
- Insight: Users are likely intimidated by the "Contact Sales" button and fear a long sales cycle.
- Hypothesis: Because users are hesitating on the Enterprise CTA, If we change the button text from "Contact Sales" to "Get a Price Quote," Then click-through rate will increase by 15% because it implies a lower-commitment interaction.
Prioritizing your hypotheses
You will likely come up with 10 different ideas. Which one do you build first? We use the PIE Framework:
- Potential: How much improvement can this make? (Above the fold changes > Footer changes).
- Importance: How valuable is this traffic? (Checkout page > Blog post).
- Ease: How hard is it to build in Webflow? (Changing text = Easy; Building a calculator = Hard).
[Internal link: /contact-us - reason: let us help you build your testing roadmap]
8) FAQ Section
How long should I spend on research before testing?
Don't get stuck in "Analysis Paralysis." For a high-traffic site, 1–2 weeks of gathering heatmap data is usually enough to spot the major patterns. The goal is to get to the "Testing" phase quickly, but with aim.
What if my hypothesis fails?
A failed hypothesis is still a win if you learn from it. If you tested "Short Form" vs "Long Form" and the Short Form performed worse, you have learned something valuable: your users actually prefer more context before they commit. That is a permanent insight you can use forever.
Can ChatGPT help me write hypotheses?
Yes. You can feed ChatGPT your qualitative data (e.g., "Users are dropping off at the pricing section") and ask it to generate 5 varied hypotheses based on behavioral psychology. However, you still need a human expert to validate if those ideas are technically feasible in Webflow.
Do I need Webflow Analyze to do this?
You can use third-party tools, but they often require complex "Event Tagging" setup by a developer. Webflow Analyze is superior for Webflow sites because it automatically understands your classes and components without extra coding, making the data cleaner and faster to access.
Why focus on "Friction" vs. "Motivation"?
Motivation (how much they want your product) is hard to change. Friction (how hard it is to get it) is easy to change. We focus our hypotheses on reducing friction (e.g., removing form fields, clarifying confusing copy) because that is the lever we control completely.
9) “Next steps” CTA block
Turn your data into a plan
- Watch 5 sessions: Go to Microsoft Clarity or Hotjar and watch 5 users interact with your pricing page.
- Identify one friction point: Find one thing that stops them (e.g., a confusing headline).
- Write one hypothesis: Use the "If, Then, Because" formula.
We don't just guess. We use Webflow Analyze and deep research to guarantee our experiments are built on facts. Contact us to start your audit.
10) JSON-LD schema
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