5 Best Practices for B2B Site Search

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Only 30% of the e-commerce visitors use the ‘search’ feature. But, according to Econsultancy, customer conversion through site search can be up to 50% or higher than the website’s average. That’s big!

The search feature is one of the most important, perhaps ‘the’ most important tool at the disposal of e-commerce businesses. Yet, a great many of them are completely oblivious to its benefits. As much as 70% of the e-commerce businesses do not support product search using synonyms, while 60% of them do no support spelling corrections. Their inability to optimize their search feature and leverage its many benefits costs them billions of dollars’ worth of business worldwide.

So, why is the search feature so important? Many experts believe that the use of search feature indicates intent on the part of the visitors. They often make use of highly specific keywords, product codes, and even product variant information to search the products. So, they already know what they are looking for. This is especially true in the case of B2B customers, who conduct their own internal research before arriving on the e-commerce site for purchase.

If the e-commerce business helps them find their product in one go, then there is a high probability of landing a conversion right at that instant. When the search throws up irrelevant or generic results, then that is bound to drive away such visitors to competitor websites.

Here are some best practices for B2B e-commerce businesses to leverage the full potential of their site’s search feature.

1. For Starters, Make the Search Bar Prominent

The Search Bar is often a neglected element of web design. It is either too small, too far located on either side, or lost amidst the clutter of other buttons and features.

Display the Search Box prominently in the middle of the page. Perhaps, even write something like “Enter Your Product Name/Details”, “Enter Keywords”, or something like that, so that the customers know what is expected of them.

2. Implement Multi-Tiered Pricing

A great deal of time is wasted in seeking, generating, and sending quotes. The entire process can be streamlined with a nifty little feature – multi-tiered pricing. When the B2B customer makes their search, their search results must mention pricing as per the purchase quantity. In the search results, this translates to something like “Pricing starts at…”. The customer then clicks on the link to find product details, along with the pricing for different purchase quantities.

3. Develop a Superior Autosuggest Feature

25% of the e-commerce visitors click on autosuggestions. It helps the visitors find the specific product they are looking for faster, with less iterations. This not only improves the customer experience on the website, but can achieve instant conversions.

4. Deliver a Richer Search Results Filtering Page

Today’s consumers – individuals and businesses alike – have grown accustomed to the uber-smooth website navigation and experience of Facebook and Twitter. They expect the same level of fluid experience with other websites too. One way to live up to their expectations is to offer them a dynamic page built on JavaScript overlay with built-in AJAX filtering. The visitors should be able to manipulate the search results to their convenience without having to wait for the site to load. In other words, they must be able to filter the search results, sort them, change the view between grid and list layouts for search results, and so on, and their results must update in a matter of milliseconds. Not seconds.

5. Equip Search Feature With Machine-Learning Capabilities

This is arguably the most powerful enhancement that can be given to the search feature. Every visitor makes their own journey to reach their purchases. Often, different customers using the same set of search keywords are looking for different products. Likewise, multiple customers use different search keywords to look for the same product. A one-size-fits-all search engine cannot cater to all of their individual preferences. That’s where machine learning proves useful.

Machine learning algorithms can mine through a wealth of information on the visitors’ past search patterns, behavior, purchase history, and so on, to discover meaningful insights into their preferences. Thereafter, each visitor’s search results can be customized specifically to suit their unique preferences based on their past patterns. Specific SKUs or groups of them that are deemed to be more relevant to the customer can be boosted in their search results, ultimately providing them a smoother, more tailored, and faster shopping experience.

E-commerce businesses must always be on the lookout for what is missing in their customer or potential customer’s purchase journey. For instance, “Zero Results” pages need not be the end of it all. E-commerce businesses can use such results to either improve their search algorithms or stock high demand products that are presently missing on their websites.