Fix Your Site Search: 7 Ways to Make B2B Buyers Find What They Need
As B2B eCommerce continues to grow, businesses are seeking ways to make their online stores more efficient and effective for customers. One key aspect of this is configuring search functionality to make it easy for customers to find what they are looking for. In this article, we will explore some tips for configuring search for B2B eCommerce.
- Understand your customers
The first step in configuring search for B2B eCommerce is to understand your customers. What are their needs and preferences? What are the most common search terms they use? Think beyond exact product names—consider what they type when they don’t know what something is called.
By analyzing both successful and failed queries, you can tailor your search functionality to better match real-world buyer behavior. For example, if your customers often search for products by brand name, you can configure your search engine to prioritize those fields. In high-SKU environments, mapping these terms to how your data is structured can uncover gaps that inhibit findability.
- Use facet filters
Filters are a great way to help customers narrow down their search results, especially in catalogs with complex attributes. By allowing customers to filter by product category, price range, brand, material, voltage, or other criteria, you empower them to self-serve quickly.
Make sure your filters are easy to use, clearly labeled, and logically grouped. Ambiguous or inconsistent filters are a common cause of user frustration. One overlooked tip: test your filter combinations—do they return relevant results, or empty states?
- Optimize your product data
Your search functionality is only as good as the product information it can pull from. Descriptions, technical fields, and attributes should be detailed, accurate, and consistent. For example, ensuring that dimensions, materials, and specifications are complete across all SKUs can dramatically improve search relevance.
Don’t stop at completeness—focus on normalization. If half your catalog says “galvanized steel” and the other half says “steel, galvanized,” your filters and search results won’t behave as intended. Structured enrichment here not only benefits search, but also feeds better recommendations and merchandising.
- Use synonyms
Customers may use different terms to search for the same product. Someone searching for “sink” may also use the term “basin.” Similarly, “wire” might be typed as “cable,” or “PVC elbow” as “plastic fitting.”
By configuring synonyms, you improve coverage for varied buyer vocabularies—especially helpful in trades where shorthand, legacy terms, or regional language comes into play. Some teams even use internal search logs to discover which terms users expect but aren’t finding success with.
- Implement predictive search
Predictive search—suggesting search terms as the customer types—is not just about speed. It can also help customers avoid dead ends, discover unexpected options, or see trending items.
What matters most is relevance. If your predictive search isn’t tuned to actual behavior—what gets clicked, added to cart, or refined—it can distract more than help. A best practice is to review your top predictions regularly, treating them like a merchandising surface that reflects buyer priorities.
- Understand when and where to use boosting
Boosting is the act of weighting certain product attributes more heavily in the algorithm. Done right, it helps align search results with business goals and customer needs. For example, you may want to boost in-stock products, top sellers, or items with a high match rate in key fields like brand or model number.
But be careful—overusing boosting can unintentionally bury relevant products. One method we’ve seen work well: regularly test core search terms across personas (e.g., engineer, contractor, purchaser) and adjust boosts based on how well results align with intent. This kind of intent-based tuning is especially powerful when revisited periodically.
- Monitor search analytics
Finally, the ongoing improvement of B2B site search depends on data. Track what your users are searching for, what’s converting, and where searches fail. Monitor metrics like zero-result queries, top refinements, and search-to-cart ratio.
Even simple insights—like a spike in “unavailable” results or repetitive no-match terms—can highlight issues with product data, synonyms, or indexing. Treat search as a performance surface that benefits from frequent testing and adjustment, not a one-time configuration.
Final Thoughts
Configuring search for B2B eCommerce is an essential part of improving product discoverability, reducing friction, and supporting self-service buying. By understanding your customers, applying intelligent filters, enriching data, handling synonyms, guiding users with predictive suggestions, tuning boost logic, and staying close to analytics, you build a search experience that works.
For teams looking to formalize this process, structured programs like Layer One’s Search Fitness Program can help bring consistency to how search performance is tested, measured, and tuned over time, turning search from a set-it-and-forget-it feature into a continuous driver of business impact.
Empower Search is the fourth of Layer One's 
See the other 13 Focus Points for Manufacturers and Distributors here!