Search queries in procurement often contain a mix of product names, technical attributes, industry use cases, and application-specific language.

While this flexibility allows users to run rich and exploratory searches, it also introduces ambiguity — making it harder for the system to consistently understand what the user is actually looking for.

To address this, we've introduced the main_topic field: a way for users to explicitly define the core product or concept at the center of their query.

What is `main_topic`?

The main_topic field lets you specify the central product or concept you’re trying to find when running a search query. It serves as an anchor for interpreting your input more accurately, especially in cases where the query includes a mix of product terms, use cases, or broader industry language.

This field helps the search system understand what you're really looking for and prioritize results that align closely with that intent.

You can think of main_topic as a way to answer the question: "What is the main thing I want suppliers for?"

Why is it needed?

Search queries often include a variety of keywords: some describe the product you're looking for, others describe the industries, use cases, or technical specifications. While this flexibility helps broaden the search, it can also lead to ambiguity.

In some cases, the system may misinterpret what you're actually trying to find — especially if all terms are matched, but not in the intended combination.

The main_topic helps resolve this by allowing you to clearly specify the core product or topic you want to anchor the search around. This increases the chances of returning relevant, high-confidence matches — even when the rest of the query is broad or complex.

How it works

The main_topic field works alongside your search filters to guide the system’s understanding of your intent.

While your filters (via match_expression) define the full search logic — including specific terminology, use cases, or industry context — the main_topic focuses on the core product or offering you're trying to find suppliers for.

What you provide

You specify main_topic as a list of keyword variations that describe the main thing you're looking for.

📘
Note
These should be short, keyword-style terms — not long phrases or natural language sentences.

Example:

"main_topic": [
  "solar panel",
  "photovoltaic modules"
]

What the system does with it

Behind the scenes, main_topic is used to help the system:

Interpret the query more accurately
Reduce ambiguity in complex or multi-topic queries
Emphasize product categories that align with your intended focus

📘
Note
This doesn’t override your filters — it complements them. But by anchoring your search around a clearly defined topic, you increase the likelihood of getting more relevant results.

When to use `main_topic`

The main_topic field is optional, but it's a powerful way to clarify your intent — especially in complex, multi-layered procurement queries.

Below are some common scenarios with real-world examples.

1. When your query is broad or exploratory

If you're starting with a wide set of related keywords or trying to capture a full market view, main_topic helps focus the search on the product that matters most.

Example 1: Identifying candidates in green construction tech

Expression:

Product group: "smart glass", "dynamic glass", "solar control glass", "switchable glass", "insulated windows", "glazing solutions", "thermochromic glazing"
Application group: "green building", "LEED construction", "energy-efficient infrastructure"

main_topic:

["smart glass"]

Why it helps: Narrows the results to core technologies and avoids suppliers offering generic energy solutions.

Example 2: Exploring sustainable materials for FMCG packaging

Expression:

Product group: "biodegradable film", "plant-based polymer", "compostable wrap"
Application group: "FMCG", "food packaging", "retail goods"

main_topic:

["biodegradable film", "compostable packaging", "eco-friendly packaging"]

Why it helps: Steers the search toward suppliers of materials, not finished consumer products.

2. When your query combines product and application keywords

If you’re combining product-related terms with industry or application terms, you can use main_topic to clarify what the actual target is.

Example 1: Cocoa butter and specialty vegetable oils used in chocolate and confectionery manufacturing

Expression:

Product group: "cocoa butter", "chocolate fats", "vegetable oils", "fats", "lipid ingredients"
Application group: "chocolate manufacturing", "confectionery", "food processing", "chocolate", "cookies”

main_topic:

["chocolate fats", "confectionery fats", "fats"]

Example 2: Brushless motors for the aerospace industry

Expression:

Product group: "brushless motor", "electric motor", "bldc motor", "dc motor”
Application group: "aerospace", "aviation", "aircrafts", "drones", "UAV", "unmanned aerial vehicles", "planes"

main_topic:

["brushless motor", "bldc motor", "motor", "motors"]

3. When precision matters more than coverage

If you're prioritizing result quality over exhaustive discovery, main_topic helps the system focus more tightly on your intent — even if it means narrowing down the candidate set.