What are the most important quiz metrics?

Start with submissions, completion rate and per-question drop-off. Then add leads captured, result distribution, and what your email tool and store report after the quiz, such as opens, clicks and sales by result.

What is a good quiz completion rate?

There is no single number that applies to every quiz. Completion rate depends on the topic, the length and where visitors come from, so set your own baseline and judge changes against it.

How often should I check my quiz analytics?

Give a new quiz a week or two of steady traffic, then check weekly or every two weeks. Checking daily on a low-traffic quiz mostly shows noise.

What does per-question drop-off tell me?

It shows where in the quiz people stop. A question that loses noticeably more people than the ones around it is usually unclear, too personal, too hard or badly placed, and is the best place to start improving.

Can I export my quiz data?

Yes. Quizably analytics can be exported, and the Leads dashboard lets you search, filter and export leads as CSV.

Quiz metrics to track and how to judge them

The quiz metrics worth tracking are submissions, completion rate, per-question drop-off, result distribution, answer distribution and average score, plus what happens after the quiz: leads, email opens and clicks, and sales by result. Each one answers a different question, and none of them means much without something to compare it to.

This guide explains each metric, how to read it, and what to do when it looks wrong. It does not give benchmark numbers, because they vary too much to trust. It shows you how to set your own baseline instead. For the wider strategy, see the quiz marketing guide.

Where your quiz data lives

There are two places to look.

Inside WordPress. Quizably has a site-wide analytics overview and a per-quiz view. They report submission count, completion rate, average score, result distribution, per-question drop-off and answer distribution. The data can be exported. The Leads dashboard shows the people who gave you an email, with search, filter and CSV export. If you’re still comparing plugins, analytics is one of the criteria worth weighting in how to evaluate a WordPress quiz plugin.

Outside WordPress. Your email service reports opens and clicks. Your store, calendar or payment tool reports sales and bookings. To connect those to a quiz, the result has to travel with the lead. Quizably’s webhook sends the result, the score and the lead together, so you can tag people by result and track what each group does. If you are new to that idea, read what a webhook is.

First, set a baseline

Before you read any single number, decide how you will judge it.

A benchmark from a blog post, including this one, tells you little about your quiz. A quiz on a busy, warm audience will behave differently from the same quiz sent to cold visitors from a social post. A ten-question trivia quiz and a four-question product finder are different animals.

So use your own data:

Publish and wait. Let the quiz collect a few weeks of normal traffic without changes.
Write down the starting numbers. Completion rate, submissions per week, leads per week, and the worst drop-off question.
Change one thing. Then compare the next few weeks to that baseline.
Keep the traffic source in mind. If a big email send doubles your traffic, the numbers will move for reasons that have nothing to do with the quiz.

A small sample is noisy. If a quiz got 20 submissions, one percentage point is a single person. Wait for more data before acting on small differences.

Metrics Quizably reports

Submissions

What it is: the number of times people completed the quiz and were recorded.

How to read it: this is your volume. Watch it week by week. A steady climb means more people are finding and finishing the quiz. A sudden drop usually means the quiz is no longer linked, the page changed, or a traffic source dried up.

What to do: if submissions are low, the problem is usually not the quiz. Check where you link to it. A quiz on a page with few visits gets few submissions. Move it to a busier page, or add a popup or slide-in (they load and count a view on every page, but only visitors who begin the quiz count toward completion rate, as explained below). See how to add a quiz to a WordPress page for the options.

Completion rate

What it is: the share of people who start the quiz and finish it.

How to read it: this is the quiz’s health check. A falling rate after a change means the change hurt. A low rate compared to your baseline points to something in the quiz: length, opening, difficulty, form timing or mobile layout.

Quizably counts it among people who started: a submission begins when the visitor clicks Start quiz, picks Resume or the quiz starts by itself, not when the page loads. A popup or slide-in that nobody opens only adds a view, and views appear in the analytics CSV (total_views), not in the admin screens. One thing can still pull the rate down without anyone quitting for good. When a visitor resumes a quiz they left, or starts over, that creates a new submission and the earlier one stays unfinished. So compare the rate to your own baseline for the same placement.

What to do: do not judge the rate in isolation. Look at drop-off by question to find where people leave. Then fix the biggest leak first. I go through a full priority list in how to improve your quiz completion rate.

Per-question drop-off

What it is: how many people leave at each question. Quizably saves answers as the visitor goes, so this counts every started submission, finished or not.

How to read it: some loss is normal at every step, so look for a question that loses clearly more people than its neighbors. Also compare the first question to the rest. A big loss at question one usually points to a weak opening or an unclear promise, and not to a question problem.

What to do: read the worst question as if you had never seen the quiz. Is it confusing, too personal, too hard or too long? Rewrite it, reorder it, or cut it. If a question is optional in spirit, like short text, consider a simpler format. For help with wording, see how to write quiz questions.

Result distribution

What it is: how often each result is reached.

How to read it: in a personality quiz, you want a spread that makes sense for your audience. If one result takes most of the picks, the answers are probably unbalanced, or that result is very broad. If a result is almost never reached, it may be impossible to reach, or it is too narrow.

What to do: if one result dominates, make the other results easier to reach by adjusting which answers lean toward them. If a result never appears, check that it is mapped to enough answers. Also decide whether it reflects your audience. A skewed spread can be real information, such as most of your readers being beginners. The post on writing personality quiz results covers how to keep results distinct.

Answer distribution

What it is: how people answered each question.

How to read it: this shows what your audience thinks, and also whether your answers are balanced. If nearly everyone picks the same answer to a question, that question tells you little about anyone.

What to do: use it two ways. First, fix questions where one answer is obviously best. Second, use the aggregate as audience research. If most people say they struggle with the same thing, that is your next piece of content or your next offer.

Average score

What it is: the mean score across submissions, relevant for trivia quizzes.

How to read it: an average that is very high suggests the quiz is too easy. A very low average suggests it is too hard or unclear. Either way the score bands stop being useful, because almost everyone lands in the same one.

What to do: adjust difficulty. Mix easy, medium and hard questions so the scores spread out. Check whether any question is one almost everyone gets wrong, since it may be unclear or wrongly marked. If you turned on answer review, people may also tell you which question seemed unfair.

Metrics measured elsewhere

The quiz is the front door. The money is made after it, and that shows up in other tools.

Leads captured

What it is: the number of people who gave you their email. You see them in the Leads dashboard, and the analytics show a lead count. If you use double opt-in, the Leads list includes pending leads, but the analytics lead counts leave them out until they confirm.

How to read it: compare leads to submissions. If many people finish but few give an email, the form may be poorly timed, required when it should be skippable, or asking for too much. If you use double opt-in, also compare leads that confirmed to leads that did not. Fewer confirmed leads is expected, and the ones who confirm are real. See double opt-in for quizzes.

What to do: test the form’s position, whether it is required, and the fields. More on this in where to put the email form in a quiz.

Email opens and clicks

What it is: how people respond to your follow-up emails, reported by your email tool.

How to read it: compare by result, not just overall. If one result group opens far less than others, the emails for that group may not match what that result said. Clicks on the result-matched link tell you whether the offer fits.

What to do: rewrite the weakest group’s first email. Make sure it repeats the result and speaks to it.

Sales or bookings by result

What it is: purchases, booked calls or sign-ups, grouped by the result each person got.

How to read it: this is the most valuable number in quiz marketing, and the hardest to get. It tells you which result is worth the most. If one result produces most of your sales, you may want more traffic aimed at that kind of person, or a sharper offer for the other results.

What to do: set up tagging through the webhook so the result reaches your email or store tool. Then review sales by result every month or so. This needs time, since purchases lag the quiz.

A simple monthly review

You do not need a dashboard full of charts. Once a month, answer these in order.

Submissions: up, down or flat compared to last month? Why?
Completion rate: better or worse than the baseline?
Worst drop-off question: has it changed? Did your last fix help?
Result distribution: is any result dominant or missing?
Leads: how many, and how many confirmed if you use double opt-in?
Follow-up: which result group opens and clicks the least?
Sales or bookings: which result is worth the most?

Then pick one change for next month. Only one. If you change five things, you will not know which one moved the numbers.

Mistakes when reading quiz metrics

Chasing someone else’s number. A benchmark from another site may not describe your audience.
Judging too soon. A few days of low traffic is noise.
Changing many things at once. You lose the ability to learn.
Ignoring the traffic source. A quiz shown to your warmest subscribers will look better than the same quiz shown to strangers.
Only looking at volume. Leads that never open an email are not worth much.
Forgetting privacy. Quizably hashes IP addresses with SHA-256 before storage, and only users with the right capability can view leads, but you still need to tell visitors what you do with their email.

Where to go from here

Open your quiz analytics this week and write down four numbers: submissions, completion rate, the worst drop-off question and the result distribution. That is your baseline. Then read how to improve your quiz completion rate and pick the one fix that matches what the numbers show.

If you have not built a quiz yet, Quizably is free, with no cap on quizzes, questions or leads. Start with how to create a quiz in WordPress.