By Artem Korsakov ·
In short: Filters in a B2B catalog only work on well-organized data: shared attribute names, values and units of measurement. Exact part-number search and selection by specifications solve different tasks. Filter parameters are chosen separately for each category. The work is accepted using test queries with a known result, including an empty result.
Equipment catalog filters work when specifications use shared names, values and units of measurement. If the same value is written in different ways, a visitor cannot confidently narrow down the choice. Developing search and filters for a B2B catalog should start with buyers’ questions and a review of the product data. Only after that does it make sense to discuss where elements go on the page.
Separate exact search from product selection
One visitor arrives with a known part number and wants to open a specific item quickly. Another knows the application conditions and is looking for suitable options. For the first, identifiers matter; for the second, specifications and categories. A single search field does not always handle both tasks equally well.
Collect examples of the identifiers your customers use. An internal part number, a manufacturer code and an old name may all differ. Decide which variants should find the same product and prepare a mapping. Do not expect the system to recognize every abbreviation on its own without source data.
Choose parameters separately for each category
Different properties matter for equipment: power, supply, dimensions, material and connection conditions. Not every product card parameter should become a filter. Pick the ones buyers actually use to rule out unsuitable products or compare the remaining options. The same parameters should be visible on the product card.
In a hypothetical pump catalog, the visitor first needs the purpose and operating parameters. Housing color may be listed on the card, but it does not help the technical choice. Too many fields of equal weight make it harder to get started and hide the conditions that really matter.
Run a short check with a salesperson and a product range specialist. Ask them to explain how they would select a specific model and write down the order of clarifying questions. This is a working hypothesis for the filter structure. It should not be presented as full customer research.
Normalize values to shared rules
Consistent units of measurement and formatting are needed for comparison. The values “220 V”, “220” and “0.22 kV” may describe a related property, but they require data preparation. The contractor needs to know who normalizes such entries and who confirms they are correct. How to organize this work is covered in the article on preparing products and a price list for a B2B catalog.
Ranges need rules too. A visitor may be looking for a value no lower than a given one or a specific interval. If a specification is unknown for some products, decide how they behave when the filter is applied. Missing data must not be silently treated as zero.
Plan for the empty result
A combination of parameters may return no products. The visitor needs to see the selected conditions and be able to remove some of them quickly. It is useful to explain that there is no exact match and offer to get in touch for help with selection, keeping the requirements already entered.
Do not replace an empty result with random products without explanation. The buyer may assume they match the query. If similar options are shown, the differences and the need for a specialist to check them must be indicated.
On a phone, check whether the number of items found is visible and whether it is clear that a filter has been applied. The buyer should not have to re-enter parameters after opening a product card and returning to the list. This is part of the selection scenario.
Accept the work based on selection tasks
Prepare several test queries with a known expected result. Include:
- an exact part number;
- a combination of specifications;
- a query with no matches;
- a product with incomplete data.
Compare the items found against the source spreadsheet.
The check should be repeated after any significant catalog update. New categories may need their own parameters, and new values may need to go through shared normalization. Decide in advance who is responsible for data quality so that the filters keep helping after the next price list upload.
To discuss a trike_dev B2B solution, prepare a few typical queries and a small sample of your product range. Working with specific items makes it easier to determine the filters you need and the limits of search than choosing features based on someone else’s catalog.
Частые вопросы ### Does a small catalog need search?
If buyers know the exact identifier, search can be useful even with a small number of products. If the range consists of a few clear categories, clear navigation may be enough at first. The decision is tested against visitors’ typical tasks.
Can filters be launched on an incomplete price list first?
Sometimes, yes, if the limitations are clear and the critical parameters have been checked. But a polished interface does not make up for suitable products dropping out of the results. It is better to prepare the priority range before launch.