Product Recommendation Quiz: How to Build One That Sells

What is a product recommendation quiz?

A product recommendation quiz (also called a product finder or guided selling quiz) is a short series of questions, usually three to six, about the shopper's needs, preferences and budget. At the end it shows a shortlist of matching products instead of the whole catalog.

Skincare ("What is your skin type?"), coffee ("How do you brew?"), mattresses, supplements and gifts are classic examples: the shopper knows their situation but not which product fits it.

Why online stores use product quizzes

• Shoppers facing too many similar products often leave without choosing; a quiz narrows the choice for them.
• It replaces the advice a shopper would get in a physical store.
• Answers tell you what shoppers want in their own words, which you can use in your product pages and email campaigns.
• A confident choice is less likely to come back as a return.

How to write good quiz questions

• Ask about the shopper's situation, not your product specs: "Where will you use it?" rather than "Which material?"
• Every question should rule products in or out. If an answer doesn't change the results, drop the question.
• Offer only answers that lead to real products. An option with no matching product ends in an empty results page.
• Keep it short: three to five questions is usually enough.
• Let shoppers skip a question or choose "not sure".
• Ask about budget near the end, once the shopper is invested.

How to build a product recommendation quiz

• List the decisions shoppers struggle with, using your support questions and reviews.
• Map each decision to product data you already have: tags, attributes, collections, price.
• Write the questions and answers, and connect each answer to a filter on that data.
• Design the results page: a short list, the reason each product fits, and an easy way to start over.
• Put the quiz where shoppers hesitate: the home page, collection pages and your navigation.
• Track starts, completions and purchases from quiz results.

Common product quiz mistakes

• Too many questions: each extra step loses shoppers.
• Answers with no matching products, which end in an empty or irrelevant result.
• A quiz that has gone stale: new products and attributes are added to the store, but not to the quiz.
• Asking for an email address before showing the results.
• Only one path: shoppers who already know what they want have to click through anyway.

Quiz or conversational product finder?

A classic quiz is a fixed decision tree that someone has to write and maintain. A conversational product finder starts from what the shopper says, in their own words, and asks follow-up questions only when they help.

• Quiz: the same questions for everyone, in the same order.
• Conversational finder: "I need a dress for a summer wedding under $150" already answers three questions, so it doesn't ask them again.
• Quiz: answer options are written by hand and can drift from the catalog.
• Conversational finder: options can come from the live catalog, so they always lead to real products.

Both can work. A quiz suits a short, well-defined decision; a conversational finder suits large catalogs and shoppers who describe what they want.

How agenola's conversational product finder works

agenola's AI shopping assistant works as a quiz that writes itself from your catalog:

• It shows the products it found first, then asks the one question that best narrows them down, such as color or size.
• The answer buttons are values that actually appear in those results, so no option leads to an empty page.
• It asks at most three questions in a conversation, and none at all when there are fewer than six results.
• Answers are remembered as preferences and applied to the next searches in the conversation.
• Shoppers can type, tap or simply ask out loud through a talking avatar.

Because the questions come from your live catalog, new products and attributes show up without anyone editing a quiz. For more on where this fits, see our guide to conversational AI for ecommerce.