B2B buyers know their part numbers by heart. They type the SKU into the search field, expect the right product and want to order. When the search returns no hits or shows the wrong results, they drop off. Revenue is lost and frustration rises.
With release 6.7.11 in June 2026, Shopware significantly improved its search and redirect functionality, especially for B2B scenarios. Manufacturers and wholesalers can now specifically optimize part number search and give buyers exactly the hits they expect. This article shows five concrete rules that make product search in the B2B shop return the right result in seconds.
Why part number search is decisive in B2B
In a B2C setting, customers often browse categories, get inspired by images and compare products. In B2B, the ordering process works differently. Buyers have clear lists, know the products they need and want to reorder quickly. The part number is their primary search criterion.
A poorly configured search costs time and nerves. When a buyer enters the SKU and gets no hits, they may try a second time. On the third failed attempt, they reach for the phone or write an email. The digital sales channel has failed, even though the product would be available.
The consequences are measurable: higher process costs in sales, frustrated customers and missed revenue. A precise part number search is not a nice-to-have but a decisive factor for sales efficiency in the B2B shop.
Rule 1: Make all relevant identifiers searchable
Not all part numbers are the same. In practice, different labels are used: the internal SKU, the EAN, the manufacturer number, the customer-specific part number or even old order numbers from legacy systems. Buyers use what they know.
A B2B shop has to make all these identifiers searchable. In concrete terms: the search must not only look through the product number field but also variants, attributes and metadata. Whoever enters an EAN should find the product. Whoever uses the old order number from the ERP system, too.
In Shopware, this can be mapped via custom fields and the configuration of the search algorithms. It is important that all fields that could contain a part number are stored in the search index. Working cleanly here drastically reduces search drop-offs.
Rule 2: Build in typo tolerance and synonyms
People make mistakes. A swapped letter, a forgotten digit or a transposed number are part of everyday life. In a B2C setting this may be annoying; in B2B it can stop the ordering process.
A modern search function in the B2B shop should tolerate typos and still return the right product. Fuzzy search algorithms recognize similar spellings and suggest alternatives. Shopware 6.7.11 improved this function further, so that relevant hits are shown even with slight deviations.
Synonyms help as well. When a customer searches for "art. no.", the system should also understand "part number", "SKU" or "order number". These synonym lists can be stored in the shop configuration and keep the search flexible without losing precision.
Rule 3: Set up direct redirects to product pages
When a buyer enters an exact part number, they do not want to land on a results page that presents ten possible hits. They want to go straight to the product page and order.
Since the update in June 2026, Shopware offers improved redirect functions. Shops can configure an automatic redirect to the product page when there is a unique match. This saves clicks, speeds up the ordering process and increases the conversion rate.
Balance is important here: the redirect should only happen for exact matches. When several products qualify, a results page makes more sense. Clear filter options and a well-structured display then help the buyer quickly identify the right product.
Rule 4: Use filters and facets deliberately
The buyer does not always know the exact part number. Sometimes they search for a product group or a specific variant. This is where filters and facets come into play.
In a B2B context, these are often technical attributes: size, material, color, weight or connection standard. Whoever maintains these attributes cleanly in the PIM system and provides them as filters in the shop enables precise narrowing. The buyer enters the part number, gets several hits and can then select the right variant via filters.
It is important that filters are logically structured and speak the language of the target group. An electrical wholesaler uses different terms than a mechanical engineering company. Using the right technical vocabulary makes product search in B2B considerably easier.
Rule 5: Measure and optimize search drop-offs
The best search function is useless if no one checks whether it works. Search drop-offs are a clear signal: buyers searched for something but did not find it. This data is worth its weight in gold.
Modern shop systems such as Shopware provide analytics tools that show which search terms return no hits. Whoever evaluates this data regularly recognizes patterns: are there frequently searched part numbers that are not found? Are certain synonyms missing? Are old order numbers not stored?
Optimizing part number search is not a one-off project but a continuous process. Whoever measures search drop-offs learns where improvements are needed. The result: less frustration, more orders, higher sales efficiency.
Technical implementation: what manufacturers should consider
The five rules sound logical, but implementation requires clarity about data sources, system architecture and processes. Many B2B shops fail not because of the technology but because of messy master data.
Part numbers must be identical in the ERP, the PIM and the shop. When different systems use different labels, the search does not work. Whoever tidies up cleanly here saves many problems later.
In addition, manufacturers and wholesalers should test the search function regularly. What happens when a buyer enters an old part number? How does the system react to typos? Are all variants found? These tests expose weak points before they frustrate customers.
Practical example: from search drop-off to conversion
A mid-sized wholesaler for industrial supplies found that a significant share of search queries in the shop returned no result. The analysis showed: buyers entered old order numbers from the ERP system that were not stored in the shop.
The solution: all historical part numbers were stored as custom fields in the shop and added to the search index. In addition, a fuzzy search function that tolerates typos was activated. After the optimization, the search drop-off rate fell noticeably and the conversion rate in the shop improved visibly.
This example shows: part number search is not a technical detail but a direct lever for revenue and customer satisfaction.
Common mistakes in configuration
Many B2B shops make similar mistakes when setting up the search function. The most common: the search is optimized for the product name, not for the part number. This may work in B2C, but in B2B it leads to frustration.
Another mistake: search algorithms that are too strict. When the system only returns hits for an exact match, many orders are lost. A certain tolerance for typos and spellings is indispensable in B2B.
Neglecting synonyms and alternative labels is also a problem. Buyers use different terms for the same thing. Whoever does not reflect this diversity loses customers.
The role of data quality
No matter how good a search function is, it cannot compensate for poor master data. When part numbers are maintained inconsistently, are missing or appear twice, the search does not work.
Manufacturers and wholesalers should therefore check their data quality before optimizing the search function. Are all part numbers unique? Are EAN and manufacturer numbers stored correctly? Are there duplicates or outdated entries?
A clean PIM system is the foundation for a functioning product search in B2B. Whoever invests here benefits not only in search but also in connecting marketplaces, maintaining catalogs and integrating with the ERP.
Measurement and continuous improvement
Optimizing part number search does not end with setup. Regular evaluations show where improvements are needed.
Important KPIs are: search drop-off rate, conversion rate after search, average time to order and the share of direct visits to product pages. Whoever keeps an eye on these metrics recognizes trends and can fine-tune deliberately.
Feedback from buyers is valuable too. Which part numbers are frequently searched but not found? Are there recurring problems? This knowledge feeds into continuous improvement and ensures that the search function grows with requirements.
Technological developments and outlook
The improvements in Shopware 6.7.11 are an example of how search and navigation functions in B2B continue to evolve. In future, AI-supported algorithms will work even more precisely, recognize search patterns and deliver personalized results.
The integration of voice search and mobile search options will also increase. Buyers want to search not only at the desk but also on the go via smartphone or tablet. Whoever invests early here secures competitive advantages.
Part number search remains a central element in the B2B shop. Whoever optimizes it consistently creates a solid basis for digital sales efficiency and measurable revenue growth.
