AI Product Recommendations for Complex B2C & B2B Brands

Your best salesperson knows what to ask before suggesting a product. Flyweight brings that approach to an AI chatbot for complex Shopify brands: understand the use case, check the important details and explain the fit.

A decision matrix connects the criteria your team uses to the options in your catalog. Decision trees turn those criteria into a conversation. Workflows define what happens next, including asking a follow-up question or bringing in a specialist.

Make your domain knowledge part of the decision

Combine product attributes, manuals, compatibility information and your team's guidance in a Knowledge Graph. Then define the questions that materially change the recommendation:

• Which machine, device or existing product does this need to work with?
• Which dimensions, connections, materials or standards are required?
• What is the customer's intended use, quantity and budget?
• Which combinations should be excluded?
• What information is missing before a recommendation can be made?

The aim is a justified recommendation. If the data does not support a match, the next step is a useful question or a handover.

An example decision tree

This is an illustrative workflow. Your products, documentation and configured rules determine the actual recommendation. Try the interactive example on our homepage.

FMW Fasteners: the specification is the product

FMW Fasteners sells professional fasteners in many sizes, materials and quantities. A buyer may know the dimensions but still need help with thread type, grade or the matching hardware.

For a catalog like this, good guidance narrows the specification before recommending a product. In the reviewed customer conversations, questions included metric and imperial sizes, bolt lengths, material choices and matching nuts and washers. An uncertain structural or load-bearing requirement belongs with a qualified specialist.

FeinTech: compatibility across the whole setup

FeinTech sells HDMI switches, splitters, extractors and adapters. Its product range distinguishes soundbar inputs, video formats and different connection arrangements.

Flyweight's existing customer example describes guidance through these products and setup questions. The decision is about the complete setup: the television, source devices, sound system and desired formats. Asking for device models is more useful than suggesting a cable from a single keyword.

Test the decisions that matter

Start with real questions your team answers every week. Include close alternatives, incompatible combinations, incomplete requests and cases that should reach a person. Review both the recommendation and its explanation in Preview before enabling the experience for customers.

Use smart sales handovers for valuable or uncertain cases. For buyers who need an offer, continue into a B2B quote workflow.

Frequently asked questions

Can we bring our own product decision matrix?

Yes. Your criteria and specialist content can guide the questions, comparisons and workflow rules. We review how those criteria map to your actual product data and which cases need a person.

Does this work for B2C as well as B2B?

Yes. The same approach can guide a consumer through a technology purchase or help a professional buyer narrow down a technical specification. Account-specific information and pricing require the relevant connected systems and permissions.

What if the AI cannot confirm compatibility?

Define a follow-up question or handover for that case. A recommendation should be supported by your catalog and documentation; missing information should remain explicit.

We love complex brands

Bring us a product question that makes your team say “it depends.” Book a demo, and we will map the decision with you.