Search Capabilities on a Custom eCommerce Platform

Make the Most of Search 

The search function is such a part of everyday life on the web that most people take it for granted. Whether it’s a search engine like Google or a search box on a top B2B eCommerce platform, efficient search is something that all of us expect. That’s why it’s so obvious when the search capabilities of an eCommerce platform don’t live up to our expectations. Many people simply abandon a business if they can’t find what they’re looking for within a few minutes. 

One of the most useful search capabilities of a search engine is to return different results for different users.  The results themselves can be very intuitive and logical to the end-user, or in another scenario, they might just be very frustrating. In short, it can begin the shopping experience by wowing the user, or it could begin the process of disappointing them. 

Because search is so important, it's a key aspect of the workflow for any eCommerce marketplace system to enable a very robust search capability. The underpinning aspects of this are the eCommerce architecture and the data itself, making sure that the data is accurate and effectively incorporated into the system. But you also must consider how that data is tied together and how it's related. It’s also important to address how the search actually functions, as well as how the search in the catalog systems store the data and get at the data once the system incorporates hundreds of thousands, or millions, of records. 

The eCommerce framework and architecture become a key factor in how responsive the site is as well as how accurate the site search results are. Let's talk about some of the key fundamentals of architecture that a custom eCommerce platform developer incorporates into enhanced search capabilities and what you should look for with any eCommerce search system. 

The first concept is the data itself and being able to store the data effectively to allow it to grow and expand and adapt per category and per product type. Fundamentally, this starts with the idea of categories, category tree view, and being able to infinitely expand it and have different depths of categories for different trees and branches. For example, you might have three levels of category depth for one particular topic, and then there might be five levels of category depth for another topic, and there might be ten levels of category depth for another; any more can get overwhelming to the user. The key takeaway is this idea of different levels of category depth per category and the ability to make as many category depths as needed. 

Search Architecture for eCommerce

From a data architecture perspective, a custom eCommerce platform developer has to handle this infinite depth capability, I.e., the ability to have different depths of categories and custom fields and attributes at any level of category. With products, we similarly need to have the ability to provide very intelligent concepts as they apply to products. There are many depths that go into products where a developer needs to be able to account for customer-specific pricing, inventory, location-specific inventory, and regional data. 

Custom Fields and Tags 

As far as the key idea of search, not only do all of these types of concepts above apply, but in particular, some of the most important aspects tend to be the data itself for the product. So we need to have very basic meta information like the meta title and the meta description and the internal title and description used within search internally.   

We can also include custom fields and attributes on each product. This typically includes tags and synonyms so that users can find items based on similar keywords. It also incorporates the idea of being able to have the product's filtered based on different categories and tying products to different categories, more than one category, and being able to filter products as someone goes through a category tree. 

HTML 

In addition, being able to have custom attributes and custom fields per product is very important, and having different data types is very important, so this might include just HTML text that is custom per product for different custom fields. Usually, it includes a list of options that might be by category or by subcategory where we might know that we're going to have a different attribute for similar products. 

Here’s an Example... 

Consider t-shirts that are for sale on an eCommerce site. Those t-shirts might have different types of necks (V-neck, crew neck, turtleneck). And then they might have different sleeve lengths (short sleeve, long sleeve, sleeve). The material will also be variable (cotton, silk, polyester blend). There might be ten colors or 100 colors, and of course the sizes can be different. All of these can be customized depending on a customer’s previous searches. 

For some eCommerce business models, it might make sense for the user to be able to actually upload an image and customize a particular shirt. Will a particular shirt accommodate a certain image? Can a material accept stitching? What about price breaks? All of these variables can be incorporated into enhanced search capabilities. It's very important that this data is able to be imported into the system so that the end-user — and the systems search capabilities —can make full use of it. 

Search can draw customers in or push them away. The largest online companies have taught them to expect the best, and that's exactly what we can incorporate into your eCommerce architecture and framework. 

Clarity has the eCommerce business solutions you’re looking for, whether you need strong search capabilities or an entirely new and custom eCommerce platform built. We’ve worked with hundreds of online businesses to put their site’s abilities far ahead of their competitors’. See what we can do for you.