Two Types of Search

It would be a joy for online retailers if most website visitor sessions ended with purchases, but that’s far from reality. Only 50% of shoppers immediately head for the product they want to buy, according to the 2018 Reimagining Commerce report. The other half has different intentions. They start by browsing such sections as:

·         Sale items (19%)

·         Shipping information (8%)

·         Payment information (6%)

·         Featured product recommendations (5%).

Online shopping journeys vary widely and don’t always lead to a purchase. Just 17% of customers say buying is their primary purpose when visiting an e-commerce website for the first time.

We can divide all e-commerce website visitors into two major groups:

·         Customers with intent to buy (known-item searchers)

·         Customers with intent to browse (exploratory searchers)

Customers with Intent to Buy

Mary is the fashionista in her group of friends and knows that chunky sneakers are a trend of the season. She’s already found the right pair, so when Mary opens an online store, she types the name of sneakers directly into the search bar. This is an example of a known-item search by a customer who knows exactly what she is looking for.

Such searchers have a particular target of their searches and will recognize the desired product when they see it. When performing a known-item search, customers usually type in the name or title of the item they seek. Some people specify what kind of product they want. For instance, Mary knows that sneakers are available in four colors, but she wants only the white version, so she searches for “FILA Disruptor white size 6” instead of just “FILA Disruptor.” This a long-tail query, and not every on-site search can handle such a search. The smart search, as one FILA official website has, automatically selects the needed filters: “white” in “color,” and “6” in “size.” This automatic filtering ensures the customer receives relevant results that make her happy and satisfied. In that case, autocomplete is also a very useful feature, as it helps searchers type in long titles correctly without too much effort.

When customers look for something with the intent to buy, the ideal search result for them is the desired product. If there is more than one item in the results, users often scan down the page and try to filter out irrelevant results by faceted refinement. In many cases, if they find a product they like, they’ll immediately buy it.

Customers with Intent to Browse

Henry wants to upgrade his Canon 70D but hasn’t decided on what and when he’d like to buy. He opens an electronics store’s site and starts his exploratory journey. Customers with intent to browse don’t have a specific product in mind but want to find items that satisfy one or more criteria. They want to discover something yet unknown to them. During an exploratory search, the customer learns about the landscape of items that match the initial criteria and meet his needs.

Such customers search for categories or for categories combined with attributes. During one browsing session, Henry types “digital camera,” “Canon camera,” and “DSLR camera.” In that case, autocomplete is also helpful because many of these search inquiries match frequent queries. Exploratory searchers are open to product suggestions and interested in more than one target. They usually go beyond the first page of search results. Customers use filters not only to narrow down results but also to discover options and combinations they were not aware of before the search. Also, these customers are typically interested in skimming through “What’s new” and “What’s popular” categories. Henry most likely will use filters to find the variety of digital cameras depending on their prices, brands, weights, dimensions, etc.

The Bottom Line

The key point is that e-commerce on-site search has to figure out the need of a customer and provide relevant results. Even if a user just browsed e-commerce website and left, it doesn’t mean he or she won’t come back. If search results were satisfying and helped the customer learn more about the options and what they need, there is a high probability they will return and purchase the desired product.

The website needs to be optimized for different types of intentions so that both types of customers convert. When you are dealing with intent-to-buy searchers, your e-commerce site should provide the quickest and easiest way to make a purchase. Placing of a search box and gift card in the left part or in the center of the website header is crucial because it’s where known-item searchers expect to find them. To encourage the user to buy one can use product-page-specific overlays and pop-ups with special offers.

Intent-to-browse searchers don’t buy but bring another value. You can get deep learning of behavioral and intent data, and use in future promotional campaigns. What may urge them to return to your website and purchase something is detailed product specifications, seductive images, and social proof like reviews and ratings.