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Not every customer who starts your quiz will finish it. Dropoff analytics show you exactly where customers are leaving — so you can fix the questions that are causing them to abandon. This guide explains how to view and interpret dropoff data and how to use it to improve your completion rate.

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What Dropoff Analytics Tracks

For each question in your quiz, Quizify records:
  • Reached — how many customers got to that question
  • Answered — how many customers selected an answer and moved forward
  • Dropped off — how many customers left the quiz at that question without answering
By comparing reached vs. answered across questions, you can see where the biggest drop in engagement occurs. A question with a high reached count but a low answered count has a high dropoff rate — meaning many customers abandon the quiz at that point.

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How to View Question-Level Dropoff Data

  1. Go to Analytics in the Quizify navigation
  2. Select the quiz you want to review
  3. Set the date range for the period you want to analyse
  4. Look for the Dropoff section or the Questions breakdown in the analytics dashboard
  5. Review the reached, answered, and dropoff figures for each question
The data is typically shown as either a count or a percentage of the total who started that question.

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How Completion Rate Is Calculated

Completion rate is the percentage of customers who started your quiz and reached the result page. Completion rate = (Completions ÷ Quiz Starts) × 100 For example: if 500 customers started your quiz and 300 reached the result page, your completion rate is 60%. Quiz starts are counted from the moment a customer begins the first question. Completions are counted when the customer reaches the result page.

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How Conditional Logic Affects Dropoff Tracking

If your quiz uses conditional logic — where customers skip questions or follow different paths based on their answers — dropoff tracking still works, but the numbers need to be interpreted carefully. When a question is skipped because of a logic jump, it is not counted as a dropoff. Dropoff only occurs when a customer reaches a question and then leaves the quiz entirely without answering. This means questions that are frequently skipped via logic jumps will show a lower reached count, which is expected behaviour. Focus on questions with a high reached count and a high dropoff rate — these are the questions being shown to many customers who then abandon.

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How to Use Dropoff Data to Improve Quiz Performance

Once you identify which questions have the highest dropoff rates, consider the following actions: Simplify the question wording. If the question is long or complex, rewrite it to be shorter and clearer. Add or adjust answer options. If customers cannot find an answer that fits their situation, they may leave. Check whether a “None of these” or “I’m not sure” option would help. Move high-dropoff questions earlier or later. Sometimes the position of a question in the flow affects engagement. A sensitive question asked too early (before trust is built) may cause more dropoff than the same question asked after a few easier ones. Remove the question entirely. If a question is causing significant dropoff and is not critical to the recommendation logic, consider removing it. Shorter quizzes tend to have higher completion rates. Check for required questions. If a question is marked required and the customer cannot or does not want to answer it, they have no choice but to leave. Consider whether making the question optional would reduce dropoff at that point.

Aim to keep your quiz to 5–8 questions where possible. Each additional question reduces the proportion of customers who complete it.