Welcome to the second part of our three-part instructional series about effectively using BigCommerce's built-in search functionality. Part 1 covered configuring the search settings themselves. In this installment we focus on the data those settings act on: optimizing your product details and descriptions so both shoppers and search engines can find the right item.
Why this layer matters so much: BigCommerce's native product search matches against the structured fields you fill in. A product that is poorly named or thinly described is effectively invisible to on-site search even when it is precisely what the shopper wants — and the same fields feed your Google rankings and your Google Shopping product feed. Get this layer right and you improve internal search, organic search, and paid feed quality at the same time.
Product Names
Name products the way customers actually type them, front-loading the words that matter. A store selling phone accessories should avoid a vague "Samsung Phone Case Blue Bedazzled" in favor of a specific, search-shaped "Blue Bedazzled Samsung Galaxy S4 Dual-Layer Case." Shoppers search by attribute and model, not by brand alone. A dependable pattern is brand + model + key attribute + product type — for example, "OtterBox iPhone 15 Pro Rugged Clear Case."
Keep names consistent across the catalog so faceted results stay coherent, and resist stuffing every keyword into the title. BigCommerce indexes the description, brand, and search-keyword fields too, so the title should read like a clean shelf label, not a paragraph. A practical rule: if you read the product name aloud and it sounds like a sentence written for a robot, trim it until it sounds like something a person would say.
Brand
Customers are loyal to brands they trust, so always populate the dedicated Brand field rather than only mentioning the brand in free text. The Brand field does four jobs at once: it powers brand facets and filtered navigation ("show me only Nike"), it drives brand landing pages, it maps cleanly to the brand attribute Google Shopping requires in your feed, and it gives on-site search a strong relevance signal. BigCommerce lets you pick from an existing brand list or add your own — use one canonical spelling consistently so "OtterBox," "Otterbox," and "Otter Box" don't fragment into three useless facets that split your traffic and confuse shoppers.
Product Descriptions
A detailed product description is one of the strongest ways to inform a customer who cannot physically inspect an item. Often the description is the salesperson. Make it earn that role with a repeatable structure: lead with the benefit and the use case in the first sentence, then cover the concrete specifics shoppers and on-site search query — material, dimensions, compatibility, sizing, what is in the box, care or warranty — and close with the one or two questions customers most often ask before buying.
Write unique copy rather than pasting the manufacturer's blurb. Duplicated manufacturer text appears on dozens of competing stores and is routinely filtered by search crawlers, so it helps neither your internal search relevance nor your organic rankings. The same caution applies inside your own store: near-identical descriptions across color or size variants compete with each other, so canonicalize variants to a parent product.
The BigCommerce-Specific Habits That Compound
Two BigCommerce fields are routinely left blank and quietly cost sales. First, the Search Keywords field on each product: fill it with the synonyms and misspellings real customers use — "sneakers" for "trainers," "hoodie" for "pullover," "cell phone" for "mobile" — so native search returns a result even when the shopper's exact word doesn't appear in the title. Second, the SEO/page-title and meta-description fields, plus complete product specifics so structured data (price, availability, reviews) can surface in Google. The same descriptive richness that helps internal search also helps you rank.
One more habit: review the search terms that return zero results. BigCommerce and analytics will show you the queries customers typed that found nothing. Each of those is either a synonym you should add to a Search Keywords field, a product you should stock, or a naming problem you just discovered for free. Auditing zero-result searches monthly is one of the highest-return, lowest-effort routines available to a BigCommerce store.
A Pre-Launch Checklist
Before publishing or auditing a catalog, confirm each product has: a specific, attribute-led name; the Brand field set with canonical spelling; a unique description that answers the common pre-purchase questions; the Search Keywords field populated with synonyms and misspellings; and the SEO/meta fields completed. Then run ten real customer queries through your own search bar and fix anything that returns zero or irrelevant results — that single exercise usually surfaces the biggest gaps before a shopper finds them for you.
A note on faceted navigation: as you enrich product data, BigCommerce's Product Filtering (faceted search) becomes far more powerful, because facets are generated from the structured fields you populate. Well-named brands, consistent attributes, and complete specs turn into clean, useful filters ("Brand," "Size," "Color," "Price") that let shoppers narrow a large catalog quickly. A store with sparse product data gets sparse, near-useless filters; a store with disciplined data gets a navigation experience that does the selling for you. The product-data work in this article and a good faceted-search setup are the same investment viewed from two angles.
In our concluding installment, Part 3, we dig into search keywords in depth — how to discover the terms your customers actually use and how to rescue poorly performing keywords so every search returns useful results. If you'd rather have specialists tune this for you, our BigCommerce SEO team does exactly this work, and a quick ecommerce SEO audit will show where your catalog is leaking search traffic today.