Which questions help you recommend the right product?

Start with a decision, then write the question.

Take two recent inquiries or two representative situations for which you would recommend different products. Identify what changes your advice: the application, available space, environment or a documented constraint. That gives you a specific reason to ask a question.

A questionnaire that repeats every field in a product sheet can demand considerable effort from visitors. For each proposed question, complete this sentence instead: ‘We use this answer to…’. If your team cannot explain its purpose, revisit it.

Use words the buyer understands.

Avoid starting with a series name or internal part number when the visitor is trying to discover which product fits. Asking about the application gives that person a more accessible starting point.

Consider a fictional workbench example. ‘Do you need to move your workstation?’ may be easier to understand than ‘Which chassis variant do you want?’. The manufacturer must confirm what that answer changes in its range. The Forma Atelier example lets you explore a journey for this type of product without sending a real request.

Distinguish requirements from option choices.

A constraint that determines whether a product is suitable should be collected early enough to guide the recommendation. Choices that further define the product can then appear as options. This distinction helps avoid asking for the same information twice.

For instance, available space may restrict which products can be considered. The exact size can then be selected from configurations that are actually possible. Limits and combinations must come from your data: a slider or a list of answers does not make a range technically valid.

Decide what happens when the buyer is unsure.

Some answers are easy for specialists and difficult for visitors. Identify which ones can remain open for confirmation with your team. In SmartSelect, that permission is configured on the relevant questions and options; it is not a universal way to skip constraints.

The salesperson needs to see what is known and what is missing. An uncertain answer should not become a confirmed characteristic simply to produce a recommendation.

Review the journey with a short checklist.

You do not need to write a complete questionnaire before starting. Your catalog or website provides a starting point for AI-assisted creation. Try the first version and check that its questions reflect how you advise buyers.

Then ask someone less familiar with your product references to try the draft. Observe unfamiliar words and answers they hesitate to choose. Ask the AI assistant to reword a question or make the change in the editor. Review the result before publishing and sharing your link.

• Can the buyer answer without knowing our internal codes?
• Do we know which decision uses this answer?
• Does the question come before the choices that depend on it?
• Have we checked a different answer and an uncertain case?
• Can the salesperson find the context needed for follow-up?